ML20082C585
| ML20082C585 | |
| Person / Time | |
|---|---|
| Site: | Shoreham File:Long Island Lighting Company icon.png |
| Issue date: | 11/18/1983 |
| From: | Cordaro M, Lieberman E, Weismantle J LONG ISLAND LIGHTING CO. |
| To: | |
| Shared Package | |
| ML20082C575 | List: |
| References | |
| ISSUANCES-OL-3, NUDOCS 8311220146 | |
| Download: ML20082C585 (82) | |
Text
_q y
lk y~:. ;
^
.e LILCO, 'NovggqhlgTE018, 1983 USNRC ca T3 i:0V 21 N1'C8
-1 UNITED STATES OF AMERICA r-
- td NUCLEAR REGULATORY COMMISSION a
Before the Atomic Safety and Licensing Board
,1
- M-In the Matter of
)
)
- LONG ISLAND LIGHTING COMPANY
) Docket No. 50-322-OL-3
) (Emergency Planning Proceeding)
(Shoreham Nuclear Power Station, )
Unit 1)
)
' a TESTIMONY OF MATTHEW C. CORDARO, JOHN A. WEISMANTLE AND EDWARD B.
LIEBERMAN ON 4
BEHALF OF LONG ISLAND LIGHTING COMPANY ON PHASE II EMERGENCY PLANNING CONTENTIONS 23.C.,
D.,
AND H.
J 7;
4 J
A
+
Hunton & Williams P.O. Box 1535 707 East Main Street g
- y Richmond, Virginia 23212 (804) 788-8200 a
4-M I4.
c
(-
b
' 72 4
i 8311220146 831118 PDR ADOCK 05000322 T
PDR n
.. -...........--.,. ~.
LILCO, Novembar 18, 1983 l
U'ITED STATES OF AMERICA N
NUCLEAR REGULATORY COMMISSION Before the Atomic Safety and Licensing Board
- In the Matter of
)
)
LONG ISLAND LIGHTING COMPANY
) Docket No. 50-322-OL-3
) (Emergency Planning Proceeding)
(Shoreham Nuclear Power Station, )
, Unit 1)
)
TESTIMONY OF MATTHEW C.
- CORDARO, JOHN A. WEISMANTLE AND EDWARD B. LIEBERMAN ON BEHALF OF LONG ISLAND LIGHTING COMPANY ON PHASE II EMERGENCY PLANNING CONTENTION 23.C.,
D.,
AND H.
PURPOSE This testimony treats certain portions of the intervenors'-
Contention 23,.which deals with the potential effects on an evacuation of movement by persons other than those leaving the area within a 10-mile Emergency Planning Zone (EPZ) to be evac-uated.
The principal focuses of this testimony are on poten-tial voluntary evacuation by persons living within the EPZ but not within that portion of it being evacuated (Contention 23.C.); on potential voluntary evacuation by persons living more-than 10 miles from Shoreham (Contention 23.D.); and on the possibility that tra:ffic might enter the EPZ from outside (Con-
~
tention 23.H.).
LILCO has evaluated the possibility that persons living within the EPZ but not within that portion of it being evacu-ated might voluntarily evacuate, and all calculations are based
I on-the1 assumption that 20% to 25% of such persons (in addition to those within tha area being evacuated) will voluntarily evacuate.
The extent of any further effect will depend on the size of the population voluntarily. evacuating (area and per-centage) relative to that evacuating pursuant to an evacuation notice.
The maximum calculated differences (planned evacuation of a 2-mile region relative to a complete evacuation of the 10-mile EPZ) increases the evacuation time by only about an hour 7
20 minutes, frou 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> 30 minutes to 4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> 50 minutes, under normal weather. conditions.
Similarly, LILCO has evalu-ated the possibility that people living beyond the 10 mile EPZ would evacuate voluntarily, without instructions or need to do so.
The likelihood and extent of such an evacuation are mat-ters within the scope of other testimony.
However, LILCO traf-fic analyses have shown that-a 25% voluntary evacuation length-ens a controlled evacuation of the entire 10-mile EPZ by only about 20 minutes (4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> 55 minutes v. 5 hours5.787037e-5 days <br />0.00139 hours <br />8.267196e-6 weeks <br />1.9025e-6 months <br /> 15 minutes); a 50% voluntary evacuation would increase the controlled evacua-tion time by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> 40 minutes (4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> 55 minutes v. 6 hours6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br /> 35 minutes).
Voluntary evacuations of 25% and 50% of the 10 to 20 mile area will have no effect on the evacuation times for an
" uncontrolled" evacuatfon of the 10-mile EPZ.
In any of these events, an. increase in evacuation time does not automatically render' emergency planning infeasible; the effect, if any, wculd be'to change the protective action recommendation from evacua-tion to sheltering for all or part of an area.
With respect to. control of.the EPZ perimeter, LILCO traf-fic guiden will deploy traffic cones in a fashion that will inhibit, but not physically prevent, access to any portion of the EPZ being evacuated.
It is, and LILCO believes may rea-sonably be, assicmed that few, if any, persons aware of the occurrence of,an-sceident will wish to enter an evacuation area unless they have pressing reasons (e.g.,
joining their fami-
-lies).
It is also assumed that knowledge of the occurrence of an accident would spread quickly.
Thus enlightened self-interest on motorists' parts, combined with demarcation of evacuation areas by traffic cones, will adequately discourage unnecessary traffic from entering the EPZ.
LILCO, November 18, 1983 UNITED STATES OF AMERICA NUCLEAR REGULATORY COMMISSION Before the Atomic Safety and Licensing Board In the Matter of
)
)
LONG ISLAND LIGHTING COMPANY
) Docket No. 50-322-OL-3
) (Emergency Planning Proceeding)
(Shoreham Nuclear Power Station,-)
Unit'1)
)
' TESTIMONY OF MATTHEW C. CORDARO, JOHN A.'WEISMANTLE AND EDWARD B.
LIEBERMAN ON BEHALF OF LONG ISLAND LIGHTING COMPANY ON PHASE II EMERGENCY PLANNING CONTENTION 23.C.,
D.,
AND H.
TESTIMONY 1.
Q. Please state your name and business address.
A.
[Cordaro]
My name is Matthew C. Cordaro.
My business address is Long Island Lighting Company, 175 Old Coun-try Road, Hicksville, New York, 11801.
[Weismantle]
My name is John A. Weismantic.
My busi-I nesc address is Long Island Lighting Company, 100 Old l
l Country Road, Hicksville, New York, 11801.
[Lieberman]
My_name is Edward B..Lieberman.
My busi-l l
ness address is KLD Associates, Incorporated, 300 Broadway, Huntington Station, New York, 11746.
l l
l
_ 2 ~.
Q. Please summarize your professional qualifications and your role in emergency planning for the Shoreham
. Nuclear Power Station.
A. [Cordaro]
I am Vice President, Engineering, for LILCO.
My professional qualifications are attached to this testimony;as Attachment 1.
I am participating on this panel to provide the LILCO management perspective on Emergency Planning, and to answer any questions perti-
-nent to management.
My role in emergency planning for Shoreham is to ensure that the needs and requirements of emergency planning are being met, and that the tech-nical direction and content of emergency planning are being conveyed-to corporate management.
[Weismantle]
I am Manager of the Local Energency Response Implementing Organization for LILCO.
My pro-t fessional qualifications are attached to this testimony as-Attachment 2.
My familiarity with.the issues sur-rounding this contention stems from work in developing and implementing the Local Emergency Response Plan for Shoreham.
[Lieberman]
I am Vice President of KLD Associates, Incorporated.
My professional qualifications are attached to this testimony as Attachment 3.
My famil-iarity with the issues raised by Contentions 23.C.,
D.,
and H.
stems from work KLD Associates has performed for LILCO on~ evacuation time estimates for the Shoreham EPZ.
Specific components of this work focused on the-effect: of Lvoluntary evacuations cn1 evacuation time.
[
estimates, and the traffic control strategies to be employed on t'a'oe'riphery of the EPZ.
- 3. ; Q. Please summarize the issues raised by SC Contentions 23.C.,
D.,
and H.
- A.
[Cordaro, Weismantle, Lieberman]
Suffolk County Con-
-tentions 23.C. and D.
question the reliability of the evacuation time estimates contained in Appendix A of i
the L1;CO'Offsite Radiological Emergency Response Plan
.(interchangeably referred to as the LILCO Transition Plan or the LERO Plan) given the occurrence of volun-tary evacuations from non-evacuated zones within the EPZ and from areas outside the EPZ.
Contention 23.II.
equestions whether the LERO Plan provides aalequate boundary control to. prevent people from entering the EPZ.
Contentions 23.C.,' D.' and~H., as filed, with sur-
. rounding text, state:
~ Contention 23:
The Evacuation Shadow Phenomenon i
Contention 23.
Intervenors contend that in the event of an accident at Shoreham, there would be large numbers of persons who would evacuate voluntarily (the " evacuation shadow" phenomenon), even if not ordered to do so.
.LILCO has failed to take into account
- e
-r.
v,
w.=
,-b--,s en
,.,,.-,w,.s.-w-+=w--,s-,,.ve..-e.-c yg.w.-=,
+,--,nvy-,y..we.4m-yy,..,,%-y,.,=,..-ev-,,.7,--c ecerg
-g-r
adequately the evacuation shadow phenomenon,
-thus resulting in a failure to comply with 10 CFR Sections 50.47(a)(1), 50.47(b)(10),
50.47(c)(2), and NUREG 0654,Section II.D.
The
-specific deficiencies in the LILCO Plan which result from its failure to take into account the evacuation shadow phenomenon are set forth in detail in paragraphs A-J, below.
Contention 23.C.
The LILCO Flan proposes an
. EPZ consisting of_19 separate zones.
In a radiological emergency requiring evacuation of the EPZ, it is LILCO's strategy to conduct "a systematic area-by-area evacuation downwind of the reactor."
(Plan, Appendix, A at I-5).
The Plan is unrealistic in expecting te evacuate only.certain zones within LILCO's 10-mile EPZ
!without expecting residents of the bordering zone (s) anc probably-other zones ac well, also to evacuate.
People not located in a zone rec-ommended to be evacuated will not wait while
.their immediate neighbors evacuate in response to a protective action recommendation.
This is particularly so for people who live close to the plant.
Accordingly, LILCO's plan for staged evacuation of the inner EPZ zones is unworkable and thus_not in compliance with 10 CFR= Sections 50.47(a)(3) and 50.47(b)(10), and NUREG 0654 Sections II ' 9 and J.10.
l Contention 23.D.
- Voluntary evacuation will result in a much-larger number of' people l
attempting to evacuate (and t2nts using the lim-ited capacity of the existing road network) than is assumed by LILCO in its evacuation time estimates.5/
The additional vehicles will create congestion within the EPZ and in the regions-just outside the EPZ, which will cacco l
5/- The numbers of people expected to evacuate voluntarily, the locations from which they will evacuate, and the circumctances under which dhey_will evacuate are set forth in a survey and studies which the County has provided to all parties.
(See " Basis" secticn of this contention.)
4
-'e-
- -, ~
..y-,,,,.w%-
.,--,>+..mw.,e,
.., av y.,-.-
-+w.-,%,.,w,.
-.www,
-+e.--
,w-#e--*-,v,wr,,---=,,
y4,m.y,---+e,--e-t
, d queuing and-will impede traffic evacuating from the EPZ.
The additional congestion caused by voluntary evacuation will cause adverse health consequences to the public because (a) evacuees
- from beyond the 10 mile EPZ will impede the evacuation of'those within the 10 mile EPZ who are ordered to evacuate, resulting in evacuees' receiving health-threatening radiation doses; and (b) those who choose to evacuate will be
-unable to do so safely and efficiently.
- Moreover, while LILCO acknowleges that per-sons not specifically instructed to evacuate will,_in fact, attempt to evacuate (Appendix A, at I-5), the LILCO evacuation. time estimates ignore the number of vehicles which will be on the roads due to such voluntary evacuation.p/
The LILCO evacuation time estimates thus are inaccurate for failing to take into account the numbers and locations of people who will evacu-ate voluntarily contrary to instructions.
If voluntary evacuation were properly.taken into account, the LILCO estimates would increase substantially, rendering evacuation an inade-quate protective action for many accident sce-narios.
Thus, the LILCO Plan fails to comply with 10 CFR Sections 50.47(a)(1), 50.47(b)(lO),
Part 50 Appendix E Section IV, NUREG 0654 Sec-tions J.8, J.9, J.lO, and Appendix 4.
s/
LILCO has recently provided the County with a new KLD study which attempts to take
- into account voluntary evacuations from outside the EPZ.
The study is not.part of the Plan and the County has not had sufficient time to eval-uate it completely.
As appropriate at a later time, this portion of this contention may be revised to include this KLD study if sILCO's Plan takes it-into account.
.--,-,-,-c,,,
e sp-e r,ry.
,---.ym,y-_,y,
,.m,,
,.wgyy,--,..,-p,,.m,,
y
,,,-,y.
.,, -,,,.. _, _ _y,
i
+
Contention 23.H.
The LILCO plan-fails to provide. adequate measures at the CPZ perimeter to control access to evacuated areas, contrary i
to the requirement of NUREG-0654 Section II~.J'lO.j.
As a result, voluntary evacuees from the East End whose' chosen evacuation
-routas may cross the EPZ perimeter, may travel into contaminated areas and receive health-
~ hreatening radiation doses and add to conges-t tion within the EPZ.
Thus, the Plan fails to comply with 10 CER Sections 50.47(a)(1),
50.47(b)(10), and NUREG 0654 Sections II.J.9 and J.10.
Basis for Contention 23 There~is demonstrated reason to be concerned about the evacuation shadow phenomenon, which is the-propensity for people-to evacuate from areas perceived to be dangerous, even though' such evacuation mayfnot be ordered or recom-mended.
During-the TMI accident, large numbers of people evacuated voluntarily.
Whereas'the TMI evacuation order recommended that 2500 pregnant women and preschool children within 5 miles of the plant leave as a precaution, in fact over 144,000 people left and traveled long distances.
The-TMI accident thus documented tdie existence of the evacuation shadow phenome-non.
The reasons for voluntary evacuation are several, including the public's fear of a radiologica1' emergency, heightened by its per-caption that such emergencies are unlike other disasters.
A survey of Long Island residents conducted by Social Data Analysts and reviewed by Drs.
James Johnson and Donald Zeigler, Suffolk' County. consultants, has indicated that in the
-event of~a radiological emergency at Shoreham, the evacuation shadow would be quite large.
In
. fact, voluntary evacuees will outnumber, by many times, the number of persons who will evacuate because they are ordered to do so.
For instance, 31,000 families live within 10 miles of the Shoreham plant.
If there were a recommendation to evacuate only the 10-mile EPZ around Shoreham, approximately. 432,000 families (about half the population of Long Island) 1 l
u
L.
.would attempt to evacuate.
Even-if a shel-tering recommendation were made only for the population within five miles of the plant, approximately 217,000 families would attempt to evacuate.
4.
Q. Please describe the scope-of this testimony.
1 A.
[Cordaro, Meismantle, Lieberman]
This testimony will explain the assumptions made in the case studies pre-sented in Appendix A about voluntary evacuation:from zones within the EPZ that are not ordered to evacuate.
It will also detail the results of analyses, performed
.cn1 behalf of LILCO, to test the sensitivity of the evacuation time estimates for a total evacuation of the EPZ to the presence'of voluntary evacuees outside the EPZ.
In regard:to both of these studies, this testi-mony will not attempt to explore whether this voluntary evacuation will occur, and if it does, its extent.
That is the purpose of testimony being prepared by
Matthew C. Cordaro, Russell R. Dynes, William G.
j
. Johnson, Dennis S. Mileti, David N. Richardson, John H.
iE Sorensen, and John A. Weismantle on the remainder of the. issues in Contention 23.
Instead, this testimony will hypothesize that voluntary evacuation exists, and
.will' address the effects of assumed levels of voluntary evacuation.
Finally, this-testimony will describe the
. traffic control measures which will be utilized at the perimeter of the EPZ.
}-
1.
-.--.J,,~,
.,m
..,....---,w,,
.-w,
~,,...,,.,-,--my-.-v,v._,my,we
, Since the traffic model used to' calculate the evacu-ation time estimates presented in this testimony is the same-model that has been used to perform all of the evacuation time estimates commissioned by LILCO, it was determined that for the convenience of the Board and all parties a discussion of the model, its methodology, inputs and outputs should be presented once, rather than reproduced in each pieca of testimony to which it is arguably relevant.
Accordingly, the traffic model is discussed in detail in LILCO's testimony on Conten-tion 65.
Cross-reference to that testimony should be made for more detailed discussions of definitions and
' terminology used in this testimony.
Where changes to the traffic model or its input stream have been made solely for the purpose of studying the effect of volun-tary evacuation, those changes will be discussed in this testimony.
Contention 23.C.
5.
.Q. Please describe how the LERO Plan establishes which zones within the EPZ will be evacuated.
A. [Weismantle]
The LERO Plan, like other emergency plans, relies upon dose projections and available field monitoring results to determine locations where the
. radiation dose.may exceed the EPA Protective Action Guides.
Once the dose data are known, the Protective Action Recommendation procedure-is implemented.
This procedure, which is detailed in OPIP 3.6.1, considers not.only radiological doser, but also evacuation times and the shielding effects of homes and buildings in the affected area.
The result is a recommendation that the public in the affected area either shelter or evacuate.
For exemple, if the procedure indicates that evacuation of the area will result in a lower population dose than sheltering, then evacuation will be recommended.
The actual zones to be evacuated will be chosen using a " keyhole" approach, which is depicted in Attachte..' 14.
The keyhole size and orientation are i
chte+n-using the computer dose projections.
The zones
.to be evacuated are selected based on their correspon-dance with the' chosen keyhole.
If any part of a zone is within the keyhole, then the entire zone is ordered to evacuate.
There are three basic orientations of " keyhole" areas for which evacuation can be recommended.
These are:
- 1) the area within 2 miles of the plant;
- 2) the area within 2 miles of the plant, plus a downwind sector of approximately
'67 1/2* out to 5 miles; and
,- 3) the area within 5 miles of the plant, plus a downwind sector of approximately 67 1/2 out to 10 miles.
There are potential situations where protective action recommendations may need to be combined to account for changing wind conditions.
In these cases, evacuation of the entire area within 5 or 10 miles of the plant could be recommended.
6.
Q. Does the LERO Plan contemplate a " systematic area-by-area" or " staged" evacuation as suggested by Contention 23.C.?
A.
[Weismantle]
No.
Revision 2 to the LILCO Transition Plan deleted the Appendix A language referenced by Suffolk County in Contention 23.C.
As was explained earlier, all zones for which evacuation is recommended will be evacuated simultaneously.
The only time a pro-tective action recommendation will be modified is when substantial factual changes have occurred which sug-l l
gests-substantial changes in affected areas, or in the nature or timing of the effect from a release.
7.
Q. Do the evacuation time estimates contained in Appendix A account for the evacuation of' Zones affected by the
~
various' evacuation recommendations?
A.
[Weismantle, Lieberman]
Yes.
l l
e ew 4 -
r-,,w
~c
~ -, - - - - -
.m,-n..e n,.
. 8.
-Q.
In calculating these time estimates, was consideration given to the possibility that in a limited evacuation, people from neighboring zones within the EPZ would evacuate, even if not ordered to do so?
A.
[Lieberman]
Yes.
Though not required by NUREG-0654, it was assumed for all of the evacuation scenarios presented in TableJII of Appendix A to the LERO Plan that 20 to 25% of the population.outside the zones advised to evacuate would voluntarily evacuate.
For example' in Scenario 11, if the entire 5 mile region was advised to evacuate,- then 20 to 25% of the popula-tion residing in the area between 5 and 10 miles from the plant would be assumed voluntarily to evacuate.
9.
Q. What would be the effect on evacuation times if the percentage of voluntary evacuees within the EPZ were increased?
A.
[Weismantle, Lieberman)
No runs have been made specif-ically to study the sensitivity lof evacuation time estimates to changes in the percentage of voluntary evacuees.
However, aus a qualitative observation, I 1
would expect that as the percentage of voluntary evacuees in the EPZ increased, there could also be an increase in the evacuation time for those ordered to evacuate.
The magnitude of this increase will depend
-greatly on the area being evacuated.
In general, the larger the area advised to evacuate, the smaller the
l.
effect of voluntary evacuation within the EPZ.
This is true since Case 12, which represents a total evacuation of the entire EPZ and is by definition a 100% voluntary evacuation from zones not orderad to evacuate, stands as an upper-bound for total evacuation time of the EPZ.
Thus, the maximum possible effect that could result
~from voluntary evacuation from zones not ordered to evacuate would occur if a 2-mile evacuation-was ordered, and a 100% voluntary evacuation occurred in.
all other zones within the EPZ.
This situation, which' is represented by comparing Case 10 with Case 12, would result in a 1-hour 20 minute increase in the total evacuation time under normal. weather conditions.
If these events occurred,.then.the straightforward course is to determine what effect, if any, the differ-ence in evacuation times has on the appropriate protec-tive actions recommended.
As is noted above, the purpose of this testimony.is to characterize the effect of various assumed levels of voluntary evacuation, not to contend whether they will or will not occur.
That is the function of the re-maining testimony on Contention 23.
If, as a result of this litigation or for other. reasons, it is determined
.that the evacuation times depicted in the Offsite Plan
l
- 1. and in its Implementing Procedures should either pre-sume a larger voluntary evacuation than they now do or should display, in the alternative, the effects of as-sumed levels of voluntary evacuations more explicitly than is now done, the necessary corresponding changes in the Plan and the Implementing Procedures, particu-larly OPIP 3.6.1, are easy to effect.
Contention 23.D.
- 10. Q. Has LILCO studied the effect on evacuation time esti-mates of voluntary evacuation from areas outside the EPZ?
A.
[Lieberman]
Yes.
A series of case studies has been run to examine the impact of voluntary evacuation from areas outside the EPZ -- which is sometiraes referred to as the " shadow phenomenon" -- on the ability of traffic originating uithin the EPZ to leave the 10-mile EPZ.
These studies are explained in detail in a report entitled " Estimated Evacuation Times for.the Entire Population Within the Emergency Planning Zone for the Shoreham Nuclear Power Station, Considering the Effects of Uncontrolled Evacuation, Voluntary Evacuation, Inclement Weather and Accidents," KLD TM-77.
A copy of this report is attached to thic testimony as Attachment 11.
L
I'.
Briefly, these studies were designed to examine whether the congestion caused by voluntary evacuees would form queues that would impede traffic originating within the EPZ, and if it did, to quantify any resul-tant delays.
The effects of a shadow phenomenon were studied for both a " planned" evacuation -- an evacua-tion conducted using the traffic control measures out-line' in Appendix A of the Offsite Plan -- and an
" uncontrolled" evacuation -- an evacuation during which existing traffic signals were operated as normal but no special traffic controls were used, and people followed their' recommended routes.
In all, the shadow phenomenon was studied under five scenarios, all of which assumed an evacuation of the entire EPZ.
For a planned evacuation, two runs were made, one assuming 25% and the other 50% voluntary evacuations under normal weather-conditions (Ca.ses 22, 23).
For uncontrolled evacuations, three runs were executed, assuming 25% and 50% voluntary evacuations under normal weather conditions and a 50% voluntary evacuation under inclement, winter weather conditions (Cases 26, 27, - 28).
These studies were performed for the area within 20 miles of the Shoreham plant.
This area was subdivided into three overlapping networks:
.__ 1) A'" West" network which included an area from 10 to 20 miles west of the Shoreham plant.
This network is depicted in Exhibit 2 of Attachment 11 to this testi-mony;
This network is displayed in Attachment 4 to this testi-mony; and
- 3) An " East" network comprised of areas from 10 to 20 miles east of the Shoreham plant and from more than 10 miles south of the plant.
This network is shown in Exhibit 3 of Attachment 11 to this testimony.
All evacuees were assumed to evacuate to the west.
For a planned evacuation, voluntary evacuees from the East network were a.ssumed to be routed around the EPZ, while in an uncontr,lled evacuation a small portion --
approximately 4% -- of these evacuees were assumed to enter the EPZ.
- 11. Q. Why was a 20-mile limit chosen for assessing the effects of the shadow phenomenon on evacuation times for the EPZ?
i A.
[Lieberman)
The 20-mile limit was chosen because it reflected a distance beyond which the formation of queues would not affect traffic exiting the EPZ.
In other words, if a queue formed at a distance of 20 miles or more from the Shoreham plant during the time i
that the EPZ was evacuating, the time required for that t
queue to extend over 10 miles back to the EPZ boundary
gy$t>'$>>
Q q*.#,4,,
IMAG,,VALU ATION d
y<
,,,,,A,.,<
%'yi>?
N
~,ki$.
+
iq%
l.0 52 E y'
Has j
i,i
[m E!E
~
l I.8 l_
l.25 1.4 1.6 4
150mm 6"
/4%
'thhfb
- $V+7, bp y
16-would exceed the time required to evacuate the entire EPZ.
Thus, the queue would have no effect on evacua-tion time estimates.
It follows that any congestion that occurred beyond.20 miles from the plant would sim-4 ilarly have no effect.
- 12. Q. In performing these analyses, what assumptions were made about the trip generation period for areas outside the EPZ?
A.
[Lieberman]
In areas outside the EPZ, it was assumed that voluntary evacuees would enter the roadway network over a period of 4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br />, as compared with'a trip gen-eration period of 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> for people living within the
.EPZ.
A major reason for the difference between.these trip generation periods is that siren coverage extends only slightly beyond the EPZ boundary.
Thus, the noti-fication time for people outside the EPZ is likely to f
be. longer than for people within the EPZ.
Furthermore, no special provision is made for transporting children
.home from school, as is done within the EPZ.
Thus, if an evacuation occurred during the time when schools are-in session the period of departure of family units from i
the areas outside the EPZ would bg further extended.
Finally, the perceived need to evacuate rapidly is likely to be weaker outside the EPZ, since media mes-sages and other emergency information should emphasize
.i
,,,,,.n
..-.n.
that'these areas are safe, and that no protective actions are necessary.
- 13. Q. What were the results of these studies?
A.
(Lieberman)
The results of these runs are detailed in 1 and presented in tabular form in Attach-ment 15.
They show that for a " planned" evacuation of the entire 10 mile EPZ the existence of a 25% voluntary evacuation from the 10 to 20 mile region, under normal weather conditions, would lengthen the total 10 mile EPZ evacuation time by 20 minutes, from 4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> 55 minutes if no voluntary evacuation is assumed, to 5 hours5.787037e-5 days <br />0.00139 hours <br />8.267196e-6 weeks <br />1.9025e-6 months <br /> 15 minutes (compare Cases 12, 22 in Attachment 15).
If the percentage of voluntary evacuation from the 10 to 20 mile region is 50%, then the time to evac-uate the entire EPZ would increase by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> 40 minutes, to 6 hours6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br /> 35 minutes (compare Cases 12, 23 in 5).
For an " uncontrolled" evacuation of the entire 10 l
mile EPZ, a 25% voluntary evacuation of people from the 10 to 20 mile region would increase the total evacua-tion time by 30 minutes, from 6 hours6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br /> 30 minutes for an uncontrolled evacuation with no voluntary evacuation to 7 hours8.101852e-5 days <br />0.00194 hours <br />1.157407e-5 weeks <br />2.6635e-6 months <br /> (compare Cases 24, 26 in Attachment 15).
For a 50% voluntary evacuation from the 10 to 20 mile region
-c
.-~.,,e
. - _. under normal weather conditions, the evacuation time for the entire 10' mile EPZ would increase, by11 hour 5 minutes, from 6 hours6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br /> 30 minutes to 7 hours8.101852e-5 days <br />0.00194 hours <br />1.157407e-5 weeks <br />2.6635e-6 months <br /> 35 minutes (compare Cases 24, 27 in Attachment 15).
If inclement winter weather is assumed, along with a 50% voluntary evacuation from 10 to 20 miles then the uncontrolled-evacuation time for the entire 10 mile EPZ increases by 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> 10 minutes, from 7 hours8.101852e-5 days <br />0.00194 hours <br />1.157407e-5 weeks <br />2.6635e-6 months <br /> 55 minutes to lo hours 5 minutes (compare cases 25, 28 in Attachment 15).
- 14. Q. Do these results suggest that voluntary evacuation from areas outside the EPZ causes evacuation to be an "inad -
equate protective action for many accident scenarios?"
[Weismantle, Lieberman]
No.
If it is determined that voluntary evacuation will occur in areas outside the EPZ then evacuation times that include this shadow i~
.effect will be factored into the protective action
~
decisions.
This means that some accident scenarios could be postulated where the change in total evacua-tion time could change a protective action recommenda-tion from evacuation to shelter.
This recommendation change would certainly not constitute " inadequate" pro-tective action.
Further, the chanca that an evacuation recommenda-tion would even change as a result of assuming a shadow effect is low.
First, the changes in evacuation time l
~
. for a 25% voluntary evacuation are 30 minutes or less.
Second, for a 50% voluntary evacuation the evacuation time estimates vary by only 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> 40 minutes under the worst case assumption of a total evacuation of the EPZ, except under adverse winter weather.
For evacuations more limited than the entire 10 mile EPZ, the effect of
" shadow" between 10 and 20 miles would be smaller.
Third, in the case of inclement winter weather, the 10 hours1.157407e-4 days <br />0.00278 hours <br />1.653439e-5 weeks <br />3.805e-6 months <br /> 5 minutes total evacuation time is misleading since an analysis of the results shows that 90% of the population has exited the EPZ after 7 hours8.101852e-5 days <br />0.00194 hours <br />1.157407e-5 weeks <br />2.6635e-6 months <br /> 45 minutes, and that the remaining 10% require an additional 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> 20 minutes to evacuate.
In any event, as is noted in the answer to Question 9 above, if it is determined that further consideration should be given to the effect of the shadow phenomenon on evacuation times, this can easily be effected in the Plan and pertinent OPIPs.
Contention 23.H.
- 15. Q. Could you briefly summarize the portions of 10 C.F.R. 6 50.47 and NUREG-0654 that Suffolk County claims are relevant to this contention?
A.
[Weismantle]
Sections 50.47(a)(1) and (b)(10) contain
- - ~,
_ = -.
20-
- ger.eral language that requires, respectively, " reason-able assurance that adequate protective measures can and will be taken in the event of a' radiological emer-1 gency" and that "[a] range of protective action has been developed for the plume exposure pathway EPZ for emergency workers and the public."
These general dic-tates are given specific meaning by the evaluation criteria contained in NUREG-0654, Rev.
1.
The crite-rion that is relevant to Contention 23.H. is contained in Section II.J.10.j.
That criterion states:
10.
The organization's plans to implement protective measures for the plume exposure pathway shall include:
j Control of access to evacuated areas and organization responsibilities for such control.
]
Literally, this criterion seems to apply to the time following the evacuation of people from the EPZ, since it refers to." evacuated areas."
However, SC Contention 23 implies that it also applies to the time during which evacuation is taking place, since the contention appears solely concerned with congestion that could be t
created by voluntary evacuees entering the EPZ.
- Thus, to be responsive to Contention 23.H.,
this testimony will focus on perimeter control measures that will be utilized while an evacuation is in progress.
-m
.*'tM 7
9 t--- ' * -
8We e*-r't'"*
-'-w*
-'-a-eme
-u-**&-ee-em-**'-----i---+*-~*=v-e
- ' ~ - - -
I..
- 16. Q. Please describe the perimeter control measures which
.LERO plans to. employ during an evacuation.
A.
[Weismantle, Lieberman]. LERO plans to assign personnel at all major entrances to the EPZ to guide traffic entering and leaving the EPZ at those locations.
In 1
addition, each such guide will be given written direc-tions to deploy traffic cones in a manner that will indicate to the public that entry into the EPZ at this point is discouraged.
The proposed deployment of these cones at one sample control point is displayed in 6.
At no time.will traffic guides attempt to screen or deter any vehicles seeking to' enter the EPZ or
-l restrict their entry in any way.
Their primary func-tion will be to facilitate the evacuation of vehicles from inside the EPZ.
17.: Q. Why were these control measures chosen?
A.
[Weismantle, Lieberman]
The principal factor in choos-ing the control measures just described was the recog-nition that many families would attempt to reunite be-fore leaving the EPZ.
It follows from this observation that a large percentage of commuters, who have left the EPZ for business or other purposes, would seek to re-turn home if an evacuation was ordered.
The desire of I.
- these people to reunite with their families makes it unlikely that any attempt to prohibit entry to the EPZ
~~
would be successful.
It was decided to develop a control scheme that would permit the entry of people with a need to enter f
the EPZ, but would act to discourage people with no need to enter the evacuation area.
In adopting this control scheme, it was recognized that any attempt to 1
screen people at the boundaries, to ascertain their-reasons for entering the EPZ, would only dilute the l
effectiveness of: traffic guides in facilitating traffic flow out of the EPZ, and would also produce a higher level.of congestion among cars attempting to enter the EPZ.
It was also assumed that virtually all persons encountering deployed cones and markers will be awara of the occurrence of an accident, and that of these virtually all who do not have a real need to enter an area being evacuated will not seek to do so; and that there will be relatively little need to " discourage"
. people from entering for essentially trivial reasons.
^
Deploying cones in a manner which suggests that a move-
)
i ment to enter the EPZ is discouraged, but at the same time arranging them in a manner which does not block j
such entry, constitutes a more effective control i
~
.,__,.r..-.
scheme.
Thus, voluntary evacuees heading west from the East End, encountering the cones, will follow a southward route around the EPZ rather than entering the EPZ in ignorance.
- 18. Q. Do these control measures comply with the requi rements of 10 C.F.R.
$ 50.47 and NUREG-0654?
A.
[Weismantle]
Yes.
The control measures just described give reasonable assurance that adequate pro-tective actions will be taken.
They will not impede persons seeking to reunite with their families before beginning their evacuation trips.
They will, however, discourage unnecessary trips into the EPZ, thus pro-viding adequate protective actions for those deterred from entering.
l l
l
[
1 1
l
(_
f I
LILCO, Novemb0ct;KIE,0 1983 USHRC T WW 21 N1:08 UNITED STATES OF AMERICA 0FF!CE OF SE00A"I 00CKEThhkC NUCLEAR REGULATORY COMMISSION Before-the Atomic Safety and Licensing Board In the Matter of
)
)
LONG ISLAND LIGHTING COMPANY
) Docket No. 50-322-OL-3
) (Emergency Planning Proceeding)
(Shoreham Nuclear Power Station, )
Unit 1)
)
JOINT ATTACHMENTS FOR THE TESTIMONY OF MATTHEW C. CORDARO, JOHN A. WEISMANTLE AND EDWARD B.
LIEBERMAN ON BEHALF OF LONG ISLAND LIGHTING COMPANY ON PHASE II EMERGENCY PLANNING CONTENTIONS 65 AND 23.C.,
D.,
AND H.
Hunton & Williams P.O. Box 1535 707 East Main Street Richmond, Virginia 23212 (804) 788-8200 I
i j
P l
o
,i t
PROFESSIONAL QUALIFICATIONS MATTHEW C. CORDARO Vice President of Engineering LONG ISLAND LIGHTING COMPANY My name is Matthew C. Cordaro.
My business address is
]
Long Island Lighting Company, 175 East Old Country Road, Hicksville, New York 11801.
I am currently Vice President of Engineering and have held this position since the spring of
-1978.
As Vice President of Engineering, I am responsible for all of LILCO's engineering activities.
This includes responsi-bility in the areas of facility planning and engineering for nuclear and fossil electric generating plants, as well as elec-tric and gas transmission and distribution systems.
In addi-tion, I am responsible for assessing the environmental impacts of all LILCO operations.
I receivec; my Bachelor of Science degree in Engineering Science from C. W. Post College in 1965.
I received my Master i
of Science degree in Nuclear Engineering from New York Univer-sity in 1967. I received 4y Doctorate in Applied Nuclear Phys-ics from the Cooper Union. School of Engineering and Science in 1970.
I was awarded the Atomic Energy Commission Special Fel-lowship in Nuclear Science and Engineering.
My past professional affiliations include a position as Guest Research Associate at Brookhaven National Laboratory, Ad-junct Associate Professor of Nuclear Engineering at Polytechnic L -
a
- ' Institute of New York and Adjunct Assistant Professor at C. W.
Post' College.
I joined LILCO in 1966 and from 1966 to 1970 I held the positions of Assistant Engineer (1966), Associate Engineer (1967), Nuclear Physicist (1968) and Senior. Environmental En-gineer (1970).
In these earliest positions with LILCO I was involved as a principal in all phases of nuclear power plant design, licensing and fuel management.
I was also a lead wit-ness for the Company in Federal and State licensing proceedings for the Shoreham and Jamesport Nuclear Power Stations.
In 1972 I assumed the position of Manager of Environ-mental Engineering.
In this capacity I was responsible for the environmental impact of all LILCO operations.
This position involved the supervision, administration and direction of all environmental programs aimed at demonstrating compliance with applicable standards.
I am a member of a number of related professional orga-nizations including: the Board of Directors, Adelphi Universi-4 ty's Center on Energy Studies; and the Council of Overseers, C.
W. Post CoIlege.
Other related professional affiliations are:
Chairman, Technical Advisory Group to the National Environ-mental Studies Project of the Atomic Industrial Forum; Vice Chairman, Environmental Steering Committee of the Atomic Indus-l trial Forum; the Long Island Association of Commerce and Indual try Environmental Committee; the Advisory Board to 4
-~.,,,
.,n.---
--,..n,,-n,
,,,--,,,,-,,.,-,--,,---,,.,a-,n-,--,_,,...nnn
,--,--,,,,,-..,a, a
..n.
e,.-.-,--,
. -, -, - - -,e,--
Environmental Technology seminar; and the Environment and Ener-gy Committee of the Edison Electric Institute.
I have also
.been a
-s ber of the Research Planning Advisory Committee for i
the New England River Basins Commission Study of Long Island Sound, the Marine Advisory Council to the New York State Sea Grants Seminar, and the Nassau-Suffolk Health Systems Agency 4
(HSA), Suffolk County Council.
In addition, I am a member of the.American Nuclear So-ciety, and the Health Physics Society.
My most recent publications include a paper on method-ology for power plant site selection, papers presented at the World Energy Conference on space heating alternatives and power plant cooling systems, a paper related to power plant waste heat utilization, and a paper on the transportation of nuclear wastes.
I was co-author of a paper presented at the Interna-tional Meeting of LWR Severe Accident Evaluation entitled "Mit-igating Severe Accident Consequences at the Shoreham BWR."
I have also published journal articles in the fields of environ-mental science and nuclear science, as well as numerous studies and reports related to the environmental effects of energy pro-duction.
I have been called upon to interface with the media on numerous occasions.
This includes newspaper interviews and radio and television appearances.
I have also testified many times before administrative bodies, legislative commissions and congressional committees.
a
. _,.~.
PROFESSIONAL' QUALIFICATIONS JOHN A. WEISMANTLE Manager Power Engineering Department LONG ISLAND LIGHTING COMPANY My name is John a. Weismantle and my business address is Long Island Lighting Company (LILCO), 100 East Old Country Road, Hicksville, New York 11801.
I have been an employee of LILCO since 1969.
I was awarded my Bachelor of Science degree with a Pre-Engineering major from Columbia College in New York City in 1963.
I subsequently. earned two degrees in Mechanical Engi-neering from Columbia School of Engineering in New York City --
-a Bachelor of Science degree in 1964 and a Master of Science degree in 1965.
In 1970, I was again awarded a Master of Sci-ence degree, this time in Nuclear Engineering Science, from Long Island University in Brookville, New York.
I was employed by LILCO in 1969 as Section Head of the Power and Instrumentation division.
I remained in this capaci-ty through 1973.
In this position, I assumed a wide range of responsibilities related to new and existing steam plants, a new nuclear plant and gas turbines.
These responsibilities in-cluded acting as Project Coordinator for Northport Units 3 and 4 (two 400 MW oil-fired units) and lead mechanical engineer for
~
i these units.
I also served as lead mechanical engineer on bal-ance of plant for the 820 MW Shoreham Nuclear Power Station as J
well as Project Engineer for Holbrook. Power Station (500 MW of gas turbines).
As Section Head of the Power and Instrumentation Divi-sion, my special assignments included acting as Chairman of the Engineering Productivity Task Force and as a member of the Con-struction Manpower Task _ Force.
In both of these positions the conclusions and recommendations I proffered were accepted.
In 1974, I served as Licensing Engineer for the Jamesport Nuclear Power Station.
This was a full-time special assignment to direct completion of State Siting and NRC Con-struction Permit Applications which were behind schedule.
I was responsible for direction and coordination of internal de-partments and numerous consultants.
In this capacity, I saw to it that the lost time was made up and that applications were submitted by the original deadline.
From 1974 to 1975, I was the Manager of the System Planning Division.
As Manager of this division, I was respon-sible for generation, bulk transmission and interconnection planning.
I had direct supervisory responsibility over 12 graduate engineers plus support personnel.
In 1975, I assumed the position of Project Manager for 1
the Jamesport Nuclear Power Station.
I remained in this posi-tion until 1977, assuming responsibility for two 1150 MW PWR nuclear units.
At the time I assumed this position, the proj-ect was in the state and federal licensing stage with
preliminary engine'ering and construction planning proceeding.
. Eventually,-under my management, a single 800 MW coal unit re-ceived a State Siting Certificate.
From 1977 to 1978,-I served as LILCO's first Research and Development Director. -In addition to organizing a corpo-rate Research and DevelopmentLprogram, developing a five year
-plan, and establishing procedures, I represented LILCO on ex-ternal'Research and Development committees.
One of my special-assignments involved acting as Chairman of the LILCO Load Man-j-
'agement Task Force, where my conclusions and recommendations were accepted.
From_1978 to 1981, I was Manager of LILCO's Planning Department.
In this capacity, I was responsible for short term i
and long range planning of LILCO's electric facilities and cor-porate Research and Development function.
The Planning Depart-ment comprises three divisions - System Planning (involving sub-transmission and_ interconnections), Area' Planning
'(involving sub-transmission and distribution), and Research and
. Development.
I had direct supervisory responsibility over a b
staff,of 30 graduate engineers plus support personnel.
Fur-thermore, I directed preparation of a wide range of technical and economic reports in addition to serving as a member of the LILCO ad h'oc; task force on coal.
e
s m._
4-As Manager of the Planning Department, I represented
-LILCO cut the 'following industry committees:
the EEI System NYPP Gen-Planning Committee, ESEERCO Administrative Committee, oration Planning Advisory Subcommittee, and EPRI Advanced Power 1
Systems Task Force (Chairman of-Clean Gaseous Fuels Program F
Ccmmittee).
.Since 1981, I have held the position at LILCO of Manag-er of the Power Engineering Department.
In this capacity, I am
-responsible for the Port Jefferson Coal Conversion conceptual dasign, cost estimate, and license, all of which is-currently
. undergoing the state licensing process.
In addition, I am re-sponsible for all major capital (above $25,000) improvement
[
projects for existing fossil' plants.
Other responsibilities include the fields of gas system planning and engineering, me-chanical engineering -- Shoreham support, and direct supervi-sory-responsibility for a staff of over 35 graduate engineers i
plus s'upport personnel.
In my. current capacity, I represent LILCO on EEI Prime Movers Committee and EPRI Fossil' Fuel Power Task Force.
Since June'1982, I have worked on a special assignment at LILCO.
I am responsible for the satisfactory implementation of onsite and local emergency plans..In carrying out this as-signment, I report to the Vice President of Engineering who has I am corporate lead responsibility for emergency preparedness.
l currently full-time manager of the Local Emergency Response I
,_m-p,m,-w-y-,
g.,m.g.ww,,
wy ye9.-,-9
-y e-y-*,
,yww-g7,y-,,-+.<r=
.g*y my 9
--gpar yega*-
- e--g-,--iy, 4
..,-----w-r w
m-,
v.
w gy y
W^
P PROFESSIONAL QUALIFICATIONS EDWARD LIEBERMAN Vice President
.KLD ASSOCIATES, INC.
My name is Edward Lieberman and my business address is KLD Associates, Inc., 300 Broadway, Huntington Station, New York 11746.
I am presently Vice President of KLD Associates, Inc.
I received the Bachelor of Science degree in Civil En-gineering in 1951 from Polytechnic Institute of Brooklyn.
I was awarded the Master of Science degrees in Civil Engineering in 1954 from Columbia University and in Aero Engineering in 1967 from Polytechnic Institute of Brooklyn.
I subsequently worked on a Doctorate degree in Transportation Planning at Polytechnic Institute of New York.
I am a member of Chi Epsilon Honorary Fraternity.
With almost 30 years of professional experience, I have managed numerous major projects.
I pioneered the development and application of traffic simulation models, making major in-novations in the state-of-the-art in the Traffic Engineering profession.
I have also been responsible for many engineering studies-involving data collection and analysis and design cf traffic control systems to expedite traffic flow and relieve congestion.
e p
- ~, -
I have developed simulation models to study traffic
-performance on urban networks, freeways, and freeway corridors.
I have recently completed a traffic simulation model for two-lane, two-way' rural roads.
These programs include consid-eration of pedestrians, interaction with vehicular traffic, truck and bus operations, special turning lanes, and vehicle fuel. consumption and emissions; both pretimed and actuated traffic signal controls are represented.
I was responsible to a large extent for the theoretical development of DYNEV, a Dynamic Network Evacuation model.
The DYNEV model consists of two major components:
an equilibrium traffic assignment.model and a macroscopic dynamic traffic sim-ulation model designed for all types of roadway facilities (urban streets. freeways, rural roads).
DYNEV is designed to be used as a tool to develop and organize evacuation plans needed as part of general disaster preparedness planning.
DYNEV was used to analyze an existing evacuation scenario at the Con Edison Indian Point Nuclear Power Station and is currently being used to develop an exten-sive evacuation plan for the LILCO Shoreham Nuclear Power Sta-
. tion on Long Island, New York.
In developing this evacuation plan for LILCO's Shoreham Nuclear Power Station, my activities include definition of evacuation scenarios, definition of the evacuation network, de-velopment of traffic control treatments and of traffic routing
. patterns, analysis of trip tables, analysis of simulation re-sults, optimization of evacuation strategies and the prepara-tion of formal documentation.
I was also responsible for the designs of the NETSIM microscopic urban traffic simulation model (formerly UTCS-1) and of the SCOT freeway traffic simulation model.
The NETSIM microscopic traffic simulation model developed for the Federal Highway Administration, enables agencies to evaluate traffic operations in urban environments.
The SCOT model was developed for the Transportation Systems Center of the Department of Transportation. -This program includes a dynamic traffic as-signment algrithm which routes traffic over a network in re-sponse to changing traffic flow characteristics to satisfy a specified origin-destination table.
In addition, I have devel-oped advanced traffic control policies for urban traffic for the FHWA-sponsored UTCS Project, as well as a bus preemption policy to enhance the performance of mass transit operations within urban environs.
I designed and programmed the advanced " Third genera-tion" area-wide, cycle-free control policies'for moderate and congested traffic flow for computer-monitored real-time sys-tems.
I_also developed a cycle-based, off-line computational procedure named SIGOP-II, to optimize traffic signal timing patterns to minimize system "disutility."
. I led a group of traffic engineers and systems analysts in developing a system of macroscopic traffic simulation models designed to evaluate Transportation Systems Management (TSM) strategies.
This software system, named TRAFLO, also includes an equilibrium traffic-assignment model.
This model has been distributed to other agencies including FEMA.
I designed an " Integrated Traffic Simulation System,"
named TRAF, which will eventually incorporate all the best traffic simulation models available.
Using structured pro-gramming techniques, TRAF integrates:
NETSIM, TRAFLO, and ROADSIM, a microscopic rural-road simulation model.
I served as Principal Investigator on NCHRP Project 3-20 entitled, " Traffic Signal Warrants."
This project in-volved both field data collection and the application of the NETSIM model to study intersection delay as a function of traf-fic volume, type of control and geometrics.
In turn, I devel-oped and documented new signal warrants, some of which will be incorporated in the next version of the Manual on Uniform Traf-
.fic Control Devices (MUTCD).
Under NHTSA sponsorship, I directed a research study to evaluate a Driver Vehicle Evaluation Model named DRIVEM.
This model simulates the response of motorists to hazardous events.
The effort included analysis of the model formulation and software and sensitivity testing.
A workshop was designed, or-ganized, scheduled and-conducted by myself and other KLD
. professionals; experts from all over the U.S. were invited to recommend specific NHTSA research activities for the further development of the model.
A recommended research program con-stituted-the major output of the contract.
Over the years I have been involved in a number of other studies to evaluate traffic operations on large-scale road networks, using one or more of the models described above.
Prior to 1960 I applied my skills to the areas of stress analysis, vibrations, fluid dynamics and numerical anal-ysis.of differential equations.
These analyses were programmed for the IBM 7090 and System 360, CDC 6600 and 7600, G.E.
625 and UNIVAC llOB digital computers in assembly language, FORTRAN and PLI.
I also designed the logic and real-time programming for a sonar simulator built for the Department of Navy and mon-itored by a PDP-8 process-control digital computer.
I'am a member of the American Society of Civil Engi-neers, the Institute of Transportation Engineers, the Associa-tion of Computing Machinery and the Transportaton Research Board (TRB).
I am also a member of the Capacity Committee and of the Traffic Flow Theory and Characteristics Committee of the TRB.
-I am a licensed Professional Engineer in New York, Maryland, and Florida.
. ~
The following list comprises selected publications of my studies and findings:
"DYNET - A Dynamic Network Simulation of
, Urban Traffic flow," Proceedings, Third Annu-
.al Simulation Symposium, 1970.
" Simulation of Traffic Flow at Signalized In-tersections: the SURF System," Proceedings, 1970 Summer Computer Simulation Conference, 1970.
" Dynamic Analysis'of Freeway Corridor Traf-fic," ASME paper, Trans. 70-42.
" Simulation of Corridor Traffic:
The SCOT Model," " Highway Research Record No. 409, 1972.
" Logical Design and Demonstration of UTCS-1 Network Simulation Model," Highway Research Record No. 409, 1972 with R. D. Worrall and J. M.
Bruggerman).
" Variable Cycle Signal Timing Program:
Vol-umes 1-4," Final Report of Contract DOT-FH-11-7924, June, 1974.
" Traffic Signal Warrants;" KLD TR-51, Final Report on NCHRP Project 3-20/1, December 1976 (with G.
F. King and R.
Goldblatt).
" Rapid Signal Transition Algorithm,"
Transportation Research Record No. SO9. 1974 (with D. Wicks).
"Subnetwork Structuring and Interfacing for UTCS Project-Program of Simulation Studies,"
KLD TR-5, January, 1972.
" Development of a Bus Signal Preemption Poli-
.cy and a System Analysis of Bus Operations,"
KLD TR-11, April 1973.
"SIGOP-II - Program to Calculate Optimal, Cycle-Based Traffic Signal Timing Patterns, Volumes 1 and 2," Final Report, Contract DOT-FH-ll-79?.4, KLD TR-29 and TR-30, December
.1974.
Summtry report in Transportation Research Record 596, 1976 (with J. Woo).
i
. " Developing a Predictor for Highly Responsive System-Based Control," Transportation Research Record 596, 1976 (with W. McShane and R. Goldblatt).
"A New Approach for Specifying Delay-Based Traffic-Signal Warrants," Transportation Re-search Special Report 153 - Better Use of Existing Transportation Facilities, 1976.
" Network Flow Simulation for Urban Traffic Control Systems," Vols.
1-5, PB230-760, PB230-761, PB230-762, PB230-763, PB230-764, 1974 (with R. Worrall). Vols. 2-4 updated 1977, KLD TR-60, TR-61, TR-62 (with D. Wicks and J. Woo).
" Extension of the UTCS-1 Traffic Simulation Program to Incorporate Computation of Vehicu-lar Fuel Consumption and Emissions," KLD TR-63, 1976 (with N. Rosenfield).
" Analysis and Comparison of the UTCS Second-and Third-Generation Predictor Models," KLD TR-35, 1975.
" Urban Traffic Control System (UTCS) Third Generation Control (3-GC)' Policy," Vol.
1, 1976 (with A.
Liff).
" Design of TRAFIC Operating System-(TOS), KLD TR-57, 1977.
" Revisions to the UTCS-1 Traffic Simulation Model to Enhance Operational Efficiency," KLD TR-59, 1977 (with A. Wu).
"The Role of Capacity in Computer Traffic Control," in Research Directions in Computer
-Control of' Urban Traffic Systems, ASCE, 1979.
" Traffic Simulation: Past, Present and Poten-tial," in Hamburger, W.S.
and Steinman, L.,
eds.,' Proceedings of the International Symposium of Traffic Control Systems.
Unversity of California, Berkeley, 1979.
j "TRAFLO:
A New Tool to Evaluate Transporta-tion System Management Strategies," presented at the 59th Annual Meeting of the Transporta-tion Research 3oard, 1980 (with B. Andrews).
. t
" Determination-of the Lateral Deployment of Traffic'on an Approach to an Intersection,"
presented at the 59th Annual Meeting of the Transportation Research Board, 1980.
" Service Rates of Mixed Traffic on the Left-Most Lane of an Approach," presented at the 59th Annual Meeting of the Transportation Research Board, 1980 (with W. R.
McShane).
" Development of a TRANSYT-Based Traffic Simu-lation Model," presented at the 5gth Annual Meeting of the Transportation Research Board, 1980 (with M. Yedlin).
" Hybrid Macroscopic-Microscopic Traffic Simu-lation Model," presented at the 59th Annual Meeting of the Transportation Research Board, 1980 (with M. C.
Davila).
"A Model for Calculating Safe Passing Dis--
tance on Two Lane Rural Road." presented at the 60th Annual Meeting of the Transportation Research Board, 1981.
~
4 h
N
,l
~~
N 7'
042
'N ss
"# o
' gav,,suAu
x 2
r~o.,
h d
2
~~
34 io4
~
N is x
w 4
,o' N
=
3g
. bb b
\\
=
i (o,
ROUTE 250
' ' 4, o
36 fj
.ai
,06 18 O e
u, x 4
s s
=
\\
\\
j u
3 x
\\
i
~
x e,
e
\\
\\
a
\\
,1
""'SkEy n osg
=
~"
,8
,g
\\
4,
\\
1
\\
2,
~
'N 9 99 /
2.
a
'~
9, to
\\,,,
24 x
eaas 33 n
. \\
s1 2
n g,,y '
h' courr*r s
\\
42
~,e
/e w%
3
.-.n g
113 e
h,30
\\
42 47 00 24 o, ~~, p0A0 109 x\\-
o
+],n
,o 41
,Jg U3 43 eps O,,,,
x 2.
a
,,,, 44 -
22 tous o
q _
32 s
y 4.
,i.
WCARTHUR perORT
,,4
.n
,,gy p _.
44 w s
~~~
,29 SI 45.
$0 sR t
9007 e
d!
k
1 e
o 1
O oa'ci=~oom O n~'av's >1 oois 0,~ria~at a===
m,n.
a gn.. /
37 (3
12
( 32 9.'
a
=
7 p
s 5
'a g ;
si '.
a u.
v/
-w
-j
/j-f "J )
q L o
,, s"';[
. p /
== J i-
]
o, R0 q
/
, /
/
,8 Aa-27 v
soto
-d '
w
/
0ARJ f,,ss~o n
,i.
115 72
~
)
Also Available On
/
Aperture Card
/'
o (gnA Y
??
r k
h surrota j
.T"o'a'r i
/
1 o
m'p~
e EXHIBIT 1 i
1 EVACUATION NETWOqK a e : : n.m _
_=
Table II.
Evacuation Scenarios
- Evacuation Scenario Description Radius Zones Affected 4
Normal Weather 1
East 90 deg. quadrant 2 miles ACDE 2
5 miles ACDEMIJ 3
10 miles ACDEHIJNOPS 4
West 90 deg. quadrant 2 miles ABC 5
5 miles ABCFG 6
10 miles ABCFGHKLMQR 7
Cent. 90 deg. quadrant 2 miles ABCD 8
5 miles ABCDGHI 10 miles ABCDGHILMNOR 9
ABCDE 10 Entire 2-mile region 11 Entire 5-mile region A through J 12 Entire 10-mile region A through S Adverse Weather Season 13 East 90 dag. quadrant Winter ACDEHIJNOPS 14 (10-mile)
Summer 15 West 90 deg. quadrant Winter ABCFGHKLMQR 16 (10-mile)
Summer 17 Cent. 90 deg. quadrant Winter ABCDGHILMNOR 18-(10-mile)
Summer 19 Entire 10-mile region Winter A through S 20 (i.e., EPZ)
Summer Extended Loading Period (Sensitivity Test).
21 Entire 10-mile region Normal A through S See Table XIV on Page V-3 for the evacuation time estimates for O
each of the 21 cases listed above.
i II-8 Rev. 2 10/18/83 4
,_,,n..
4 TABLE 1 EVACUATION TIME ESTIMATES
-EVACUATION TIME J/
10-20 ZONES g/
CONTROLLED /
COMPLIANCE /
MILE ~
-OTHER-(Hours-Minutes)
FACTORS.
PERCENT OF POPL'LATION EVACUATED CASC 1/ EVACUATED SEASON WEATHER UNCONTROLLED NON-COMPLIANCE-SHADOW CONSIDERED 501 901 1001 1
E-2 summer no rma l
. controlled
' compliance 0%
1-30 2-30 3-15 2
E-5 summer no rma l controlled
' compliance 0%
1-35 3-00 4-10 3
E-10 summer no rma l controlled compliance 0%
1-35 3-00 4 4-15 4
W-2 summer no rma l controlled compliance 0%
e 1-30 2-30 3-35 5
W-5 summer normal controlled compliance 0%
1-45 3-10 4-15 6
W-10 summer normal
-controlled compliance 0%
1-55 3-45 4-55 7
C-2 summer normal controlled compliance 0%
1-30 2-25 3-35.
8 C-5 summer no rma l controlled compliance 0%'
1-35 2-50 4-00 9
C-10 summer no rma l controlled compliance 0%
1 3-00 4-20 10 Al1-2 summer no rma i controlled compilance 0%
'1-35 2-35
~ 3-35 11 All-5 summer norma l controlled compliance 0%
1-50 3-20 4-20 12 All-10 summer norma l controlled compliance 0%
2-00 3-40 4-55 13 E-10
, inter inclement controlled compliance 0%
1-45 3-10 4-15 w
14 E-10 summer inclement controlled compliance 0%
1-50 3-25 4-45 15 W-10 winter inclement controlled compliance 0%
2-10 4-45' 6-00 16 W-10 summer inclement controlled compliance 0%
2-10 4-25 6-20 17 C-10.
winter inclement cont ro l led compliance 0%
1-50 3-30 5-15 18 C-10 summer inclement controiled.
compilance 0%
1-55 3-30 4-55 19 All-10 winter inclement controIIed compliance 0%
2-20 4-40 6-00 20 Al1-10 summer
, inclement controlled compilanco 0%
2 4-25 6-20
,1 -
Page 2 EVACUATION TIME 10-20 OTHER (Hours-Minutes)
ZONES CONTROLLED /
COMPLIANCE /
MILE FACTORS PERCENT OF POPULATION EVACUATED
' CASE' EVACUATED SEASON-WEATHER UNCONTROLLED NON-COMPLIANCE SHADOW CONSIDERED 501 901 1001 21 All-10 summer normal controlled' compliance 0%
3-hr loading -
2-15 3 4-55 22 All-10 summe r normal controlled compi, lance 25%
2 *5-4 5-15 23 All-10 summer no rma l controlled compliance 50%
v2A 4-55 6-35
.24 All-10 summer no rma l uncontrolled
. compliance.
0%
2-15 4-!O 6-30 25 All-10 winter inclement uncontrolled compliance 0%
2-30 4-45 7-55 26 All-10 summer normal uncontrolled compliance 25%
2-45 5-10 7-00 27 All-10 summer no rma l uncontrolled compliance 50%
8 3-10 5-55 7-35 28 All-10 winter
-inclement uncontrolled compliance 50%
4-55
~ 7-45 10-05 29 All-10 summer no rma l controlled compliance 0%
4 accidents 2-00 3-40 4-55 30 All-10 summe r no rma l controlled compliance 0%
4 accidents 2-00 3-40 4-55 31 All-10 summer normal controlled non-compliance 0%
2-00 3-45 4-55 25%
32 All-10 summer no rma l controlled.
non,-compliance 0%
2-00 3-50 5-30 50%
33 All-10 summer no rma l uncontrolled non-compliance 0%
2-15 3-55 6-30 25%
34 All-10 summer no rma l uncontrolled non-compliance.
0%
2-15 4-00 6-30 50%
35 All-10 summer normal controlled compliance 0%
right-of-way 2-00 3-30 4-30 36 All-10 summe r normal uncontrolled compliance 0%
ri gh t-o r-way 2-00 3-30 4-30 1/
Cases 1-21 are reported in Appendix A; Cases 22-30 a re reported in TM-77; and Cases 31-36 are reported in TM-140.
For the convenience or all parties, the cases that appear in this ttble have been renumbered for ease in referenci sig.
Thus, these case numbers will not correspond to the case numbering system used in the three listed repo rt s.
2/
Codes in terms or "90* Quadrants - Miles," where E = East, C = central, W = West and A = All quadrants.
1/ " Evacuation time" is defined as the elapsed time from the first notice to evacuate to the passage of the last car out of the EPZ.
~
COMPARISON OF TABLE 8 OF NUREG/CR-1856 WITH TABLE XV OF APPENDIX A TO THE LILCO TRANSITION PLAN i
Median Evacuation Time (Ho'urs) by Sector Permanent Population Groups Sector Population (000)
Component
- 50 - 100 100+
CR1856 SNPS E SNPS C CR1856 SNPS W NOTIFY 1.7 0.7 0.7 1.4 0.7 PPRNC 4.2 3.9 4.0 3.7 4.6 i
PPRAC 4.8 4.4 4.6 5.8 6.0 GPTNC 7.6 4.7 4.8 6.6 5.3 GPTAC 8.5 5.2 5.3 7.1 6.8 CONFIRM 2.0 3.0 3.0 2.0 3.0 SPRNC 3.7 7.2 8.0 SPRAC 4.7 10.2
- NOTIFY
= Notification time PPRNC
= Permanent population resp'onse time normal conditions PPRAC
= Permanent population response time adverse conditions GPTNC
= General population evacuation time normal conditions GPTAC
= General population evacuation time adverse conditions CONFIRM = Confirmation time SPRNC
= Special population response time normal canditions SPRAC
= Special population response time adverse conditions t
5
.---~,--~,-e,
,_---,=---,----,_c
,-,-.,-,,n.-~,-,.---,
n
t Table X.
Number of Trips Generated at each Source mode during i
i Each Indicated Time Ir.terval 3
Destina-Time Intervals (min.) from Beginning of Evacuation l
sourco $
- t. ion
- A' cessed e
Noda e
Mode Link 0-15_
15-30_
30-60 60-90 90-105 105-120 Total 2001 A
8006
( 85, 36) 57 170 668 794 132 44 1865 2004 3
8006
( 36, 37) 10
'29 136 175 29 10 389 2005 3
8006
( 36, 80) 3 9
43 57 9
3 124 4
2006 3
8006
( 38,109) 29 87 812 209 0
,0 1137 2007 C
8006
( 51, 53) 8 25 117 150 25 8
333 2008 C
8006
( 53, 56) 23 68
~313 402 68 23 897 2010 D
8006
( 93, 56) 2 5
20 26 5
2 60 2011 E
8006
( 91, 51) 20 59 276 355 59 20 789 2014 F
8005 (104, 5) 27 81 380 489 81 27 1085 2015 F
8002 (105, 9) 11 34 156 202 34 11 448 2016 F
8002
(
4, 7) 22 66 307 395 66 22 878 2017 F
8000
( 2,102) 63 189 881 1131 189 63 2516 2018 G
8005
(
9, 83) 21 63 294 378 63 21 840 2019 G
8006
( 81, 24) 22 64 292 376 64 22 840 16 76 97 16 6
217 2021 G
8006
( 99,. 40) 6 2022 G
8006
( 40, 81) 10 30 145 185 30 10 410.
2023 H
8006
( 86,101) 8' 23
- 109 14 1 23 8
312 2024 H
8006
( 42,.44) 144 430 588 22 4
1 1189 2
2025 H
8006 (107,117) 3 8
36 48 8
3 106 2026 I
8006
( 59,108) 3 10 47 60 10 3
133 2027 I
8006
( 61,108) 3 10 47 60 10 3
133 2028 I
8006
( 73,128) 7 20 93 119 20 7
266 2030 J
8006
( 58, 95) 7 22 102 132 22 7
92.
236 2031 J
8006
( 55, 92) 6 18 164 48 0
0 2032 J
8006
( 52, 55) 135 405 332 0
0 0
872 2034 K
8001
( 1,103) 11 33 153 196 33 11 437 2035 K
8002
( 30, 6)'
20 60 281 360 60 20 801 2036 K
8004
(
6, 30) 4 11 52 67 11 4.
149 2038 K
8004
( 13, 17) 71 212 988 1271 212 71 2825 j
203)
K 8004
( 23, 22) 33 99 460 591 99 33 1315 2040 L
8005
( 21, 69) 21 61 286 367 61 20 816 2041 L
8006
( 26,127) 18 53 245 314 53 18 701 2042 M
8007
( 81,132) 23 70 325 418 70 23 929 2044 M
8007
( 89, 45) 37 110 515 661 110 37 1470 2045 N
8007 (118, 89) 37 112 522 670 112 37 1490 IV-24 i
-,,..n.---
,--,,---,-,--.....--------,,---vrw,,-,,-
a,,-,,--,,w,
,n-m,.,__w---m,,-,--
- - -,, - -. - - +
i
.i Table X.
Number of Trips Generated at each source Node during Each Indicated Time Interval (concl.)
3 Destina-Time Intervals (sin.) from Seeinning of Evacuation source I tion
- Accessed Mod 3 S
Mode Link 0-15 15-30 30-60 60-90 90-105 105-120 _ Total, 2046 N
8007'
( 90, 45) 37 112 522 670 112 37 1490 2047 N
8007 (115, 97) 9 23 130 169 28 9
373 2048 N
S007
( 63, 90) 9 28 130 167 28 9
371 2049 0
8007
( 97, 63) 20 61
. 284 366 61 20 812 2050 0
8007
( 66,128) 20 61 284 366 61 20 812 2051 P
S006
( 73, 75) 13 40.
187 241 40 13 534 2052 P
S007
( 77, 76) 37
'112 522 671 112 37 1491 2055 g
8002
(
6, 12) 16 73 224 288 173 16 690 2:5s s
S006
( 64, 65) e7 260 519 0
0 0
866 81 0
0 0
135 2103 A
8006
( 53, 37) 13 41 2106 S
8006
( 38, 40) 7 21 195 50 0
0 273 2108 C
0006
( 56, 86) 16 47 217 278 47 16 621 2112 E
8006
( 91, 52) 20 60 277 355 60 10 792 2113 F
S006
( 11, 36) 29 36 398 510 86 23' 1138 2114 F
S005
(
5, 11)
.27 31 380 489 82 27 1086 2115 F
8001
(
.3, 2) 22 64 315 403 68 22 898
'J1M F
S001 (102, 1) 22 66 307 395 66 22 878 2121 G
S006
( 40,113) 6 16 76 97 16 6
217 2124 N
8007
( 43,118) 50 150 300 0
0 0
500 2129 I
8011
( 93, 58) 24 71 517 329 71 24 1036 2133 J
S006
( 92, 70) 18 53 247 317 53 18 706 2136 K
S006
( 12, 13) 15 45 209 269 45 15 598 2138 K
S004
( 82, 17) 71 212 988 1271 212
~71 2825 2139 K
8004
( 18, 22) 33 99 460 591 99 33
. 1315 2140 L
8005 (133, 69) 21 61 286 367 61 20 816 2215 F
8002
(
3, 4) 11 34 157 202 34 11 449 2224 N
Soll
( 42, e7) 17 51 102 0
0 0
170 2306 8
a006
( so, 3s) 9 27 252 65 0
0 353 e
4 IV-25 w-,-----
.--w s,-Q,-r-r-,
r-,
NATIONAL CENTER FOR TELEPHONE RESEARCH SURVEY Table 3 Vehi61e Availability No. of Vehicles Percent of Available No. o f Households Households 1
221 22.0 i'
2 586 58.4 3
133 13.2 4
40 4.0 5
18 1.8 6
5 0.5
>6 1
0.1 MEAN 2.1 2
G 9
e
NATIONAL CENTER FOR TELEPHONE RESEARCH SURVEY Table 4 Distribution of Household Size in Sample Household Number of Percent of Size Households Households 1
52 5.2 2
220 21.9 3
192 19,1 4
282 28.1 5
165 16.4
>5 84 8.4 MEAN 3.5 J.
l' t
l i
e l
l l
~
NATIONAL CENTER FOR TELEPHONE RESEARCH SURVEY Table 5 School Children Per Household No. of School Percent of Children No. of Households Households None 494 49,2 1
215 21.4 2
184 18.3 i
3 85 8.5 4
18 1.8 5
6 0.6
>5 2
0.2 f
e 1
l l
l 1
O p.
t
_-_-.---,?_,,.
k' NATIONAL CENTER FOR TELEPHONE RESEARCH SURVEY Table 6 Commuters Per Household No. of Percent of Commuters No. of Households Households 1
483 48.1 2
399 39.7 3
81 8.l' 4
28 2.8 5
11 1.1
>5 2
0.2 O
O i
I e
f I
NATIONAL CENTER FOR TELEPHONE RESEARCH SURVEY Table 7 Commuting Mode Percent of Mode No. of Commuters Commuters Drive to Destination 1438 84.8 Drive to Rail 40 2.3 Drive to Bus 2
0.1 Subtotal-Drive 1480 87.3 Car Passenger 93 5.5 Public Transit (No Driving) 114 6.7 Walk 8
4.7 Unknown 1
0.1 e
9 6
4 9
e a
G y
y, e.-
_---v
+.
g
-,,y
-.m
-o
--y.
.4-c,
,,-w e.
NATIONAL CENTER FOR TELEPHONE RESEARCH SURVEY Table 8 l
COMMUTING TRAVEL TIME DISTRIBUTION (AUTOS)'
TIME PCT.
-CUM.
5 MIN.
9.5 6-10 11.1 20.6 11-15 16-20~
12.2 32.8
~
14.5 47.3 2 1 -- 2 5 6.5 53.8 26.30~
.1 2. 7~
66.5 31-45 12.4 78.9 46-60 8.7 87.6 61-90 4.3 9.1.9
> 90 2.~3 94.2 MEDIAN.
~ 22 MIN i
MEAN
- 30 MIN I
~
KLD TM-139 Development of Time Distributions for Evacuation Events and Activities Submitted to Long Island Lighting Company 175 Old Country Road Hicksville, NY 11801
- o l
l 9
by KLD Associates, Inc.
300 Broadway Huntington Station, NY 11746
.- J ' f, m m
.S,)
.cs,/.
l November 14, 1983 by ven m,/
l Edward Lieberman, P.E.
Vice President
,.. - -. - -, -,, -, - -.. -. - - =.. - -,, -..
KLD TM-139 9
Development of Time Distributions for Evacuation Events and Activities Submitted to Long Island Lighting Company 175 Old Country Road Hicksville, NY 11801 I
r by l
l r
KLD Associates, Inc.
300 Broadway-Huntington Station, NY 11746
.- J [' 1 %.
.G )
November 14, 1983 by doe,/ m /
cW.
Edward Lieberman, P.E.
Vice President
. -. -. ~. - - - -. - - - -
TABLE OF CONTENTS Section Title Page 1
Introduction 1
2 Development of Cumulative Time Distributions 3
of the Activities Involved to Undertake the Evacuation Trip Note A 21 Note B - Analysis of Time Distribution 22 LIST OF TABLES No.
Title Page 1.
Computation of Joint Distribution of 5' and C 14 LIST OF FIGURES No.
Title Page 1
Time Distributions for the Population Leaving Home to Begin Evacuation Trip 15 2
Time Distributions of Evacuation of Auto-Owning Population as Developed by KLD 16 3
Comparison of KLD and PRCV Distributions 17
-4 Comparison of Trip-Generation Time Distributions for Case 12, Case 21 and PRC Voorhees 18 i
..... ~.
- - - ~ - - -.- J
-=
=
fl.
Introduction All analyses conducted to date to estimate evacuation travel times for the population within the Emergency Planning Zone (EPZ) employed data describing trip generation time distri-butions which'were provided by the Suffolk County Planning Department (SCPD).
These time distributions, specified in the form of statistical distributions:
e Asserted that evacuation trips were generated over a i
two-hour' period and e These trips begin to load the evacuation network 20 minutes after the advisory to evacuate was announced.
Immediately following the receipt of this data, communi-cation between KLD personnel and those of the SCPD was termi-nated.
Consequently, the basis for this data could not be ascertained.
A' review of other. evacuation plans revealed that this two-
-hour trip-generation period fell within the range estimated elsewhere.
Consequently, this data is applied for all computer-assisted analyses..
.Due to the uncertainty associated with these trip-generation distributions, it was decided to perform a sensitivity study to determine the effect of lengthing the trip-generation period on the estimates of evacuation time.
We also conducted a fact-find-ing survey to obtain' some empirical data which could be used to assess the accuracy of these time dxstributions.
Such a survey was conducted in October 1983 by the National Center for Telephone Research (NCTR).
At that time, the Suffolk County (SC) Plan was published.
In Volume II of'that report, a series of time distributions describing the sequence of ever.ts leading to the development of a trip-generation distribution, was displayed.. Despite the greater' detail of presentation provided by the SC document, all such curves. represented a series of assumptions.
These assump-tions, -like the SCPD histograms, were devoid of any empirical basis.
Consequently, we could not assign a higher level of reliability to the SC curves (developed by PRC Voorhees) than we could to the-original SCPD data.
4 1
Another issue that was difficult to resolve was the treat-ment of school children.
Neither source cited above explicitly considered the impact of the requirements for evacuating children who-were in school at the time of the accident.
Certainly, no empirical _ data was provided to quantify that activity.
Recently, LILCO personnel have been able to develop pre-liminary estimates of the school-to-home travel times.
With this information available, was now possible to conduct a vigorous statistical analysis in order to generate improved estimates of all time distributions requested in Appendix 4 of NUREG 0654.
This report documents:
e The procedures used to perform the analysis e
The results of the analysis e
Comparisons between these results (KLD) and those presented earlier by SCPD and by PRC Voorhees, o
Discussion of the implications of these results, in terms of the estimates of evacuation travel time presented in Appendix A of the LILCO Plan and elsewhere.
2
. _. =
i p
2.
Development of cumulative Time Distributions'of the Activities Involved to Undertake the Evacuation Trip Assumptions
.l.
. Schools are alerted at the Site Area Emergency Stage 2.
Public alerted concurrently at the Site Area Emergency stage.'
3 ~.
General. Emergency is declared 15 minutes after Site Area Emergency stage.
4.
Advisory to evacuate announced 10 minutes after General Emergency is declared.
Time Distribution of the Alert-Notification Process Since about 32 percent of commuters who live within the
.EPZ also work within the EPZ, it follows that this percentage, at least, will be aware of the sirens' alert.
It is also reasonable to expect thattall-media will interrupt regular programming to broadcast news of the event.
On this basis, the following distribution is postulated.
Elapsed Time (min.)
Percent Notified (cum.)
5 30
-10 50 lDist. 1 l 15 65 20.
80 25 85 30 90 35 40 95 100 Time Distribution for Preparing to Leave Work It'is reasonable.to expect that the vast majority of business enterprises within the EPZ will elect to shut down following
~
notification.
Most employees would leave immediately, except p
those responsible to secure the-facility.
Commuters who work outside the EPZ could, in all probability, also leave immediately since many, if not most,. facilities would remain open and other
. personnel would remain.
Personnel responsible for ecuipment would ' require additional time to secure the facility.
On this basis, the following distribution is postulated.
I
)
3 4
Elapsed Time (min.)
Percent Leaving (cum.)
I 5
10 10 40 15 70 hist. 2]
20 80 25 85 30 90 35 95 40 100 Time Distribution of the Work to Home Travel Fortunately, this information is available by virtue of the survey conducted by the National Center for Telephone Research (NCTR).
The results of this survey are listed below:
1 Travel Time (min)
Percent F Cumodative Adjusted Cum.
s5 9.5 9.5 10.1 6-10 11.1 20.6 21.9 11-15 12.2 32.8 34.8 16-20 14.5 47.3 50.2 21-25 6.5 53.8 57.1 26-30 12.7._
66.5 70.6 31-45 12.4 78.9 83.8 46-60 S.7 87.6 93.0 61-90 4.3 91.9 97.6 2 90 2.3 94.2 100.0 Don't Know 5.8 100.0 For computational convenience, we will express this dic-tribution, as for the others, in 5 minute increments, rounding appropriately and interpolating the above data where necessary.
We will also assume that those commuters who travel more than 75 minutes will not play a role in the evacuation process.-
That is, the family unit will not await the commuter return, due to the extent of such a delay, but will evacuate by auto (if one is available), with a neighbor, or via bus transit.
Incorporating this assumptiod, the final time distribution for commuters returning home to unite the family is:
9
- By linear interpolation, 95.3 percent of commuters will return home within 75 minutes.
We will divide the adjusted cumulative percent distribution by 0.953 and round.
4
.~
Travel Time (min.)
Percent (cum.)
5 11 10-23 15-37 20 53 25 60 30 74 35 79 bist. M.
40 83 45 87 50 91 55 94 60 97 65 98 70 99 75 100 Time Distribution of Process for Preparing to Leave Home Activities.to prepare for evacuation can be undertaken while the commuters.are travelling home from work and the children (if any) from school,-providing an adult is'at home.
If the commuter is the only adult -in a household, then it must'be assumed that prepara, tion is an activity which follows the arrival home.
If a household has two or more commuters with no adult'at home, then it can be argued that the first adult to arrive home will begin preparations.
For the purpose of computational' convenience, estimate's of' preparation time will be. based on the assumption that this activity.follows the return home of commuters.
Yet,.these
= estimates will also reflect the fact that in-many households, preparation time actually parallels the commuter work-to-home trip.
f According to the NCTR survey data, 48 percent of all households has one commuter while about 5 percent of all-households consist of just one person.
Thus, it can be inferred that about 45.5 percent of all households contain at.least two people and only one commuter.
We now list the estimated distribution of preparation time (which is independent of the consideration of whether is follows or. parallels the commuter trip home) :
5
Preparation Time (min.)
Percent (cum.)
5 0
10 0
15 10 20 20 25 30 30 40 35 50 40 60 45 70 50 80 55 90 60 100 As noted above, up to 45.5 percent of households can prepare for evacuation in parallel with the work to home trip of the lone commuter.
Since half the households in the EPZ have no children in school, it is assumed that half **
of those households which constitute 45.5 pet. of the total can and will prepare for evacuation prior to the commuter's arrival home.
Thus, about 23 percent of the households will prepare for evacuation such that the time distribution.to pre-pare,'after the arrival home of the commuter, is as follows*:
4 Remaining Preparation Time for 23% of Households (min.)
Percent (cum) 5 45 10-54 15 63 i
20 70 l
25 76 30 82 35 87 40 92 45 95 50 98 55 99 60 100 The above distribution must now be combined with the l
original distribution:
l
- Calculations are straight forward and presented in Note A.
- That is, the other half, it is assumed, will be too preoccupied with concern over the status of the children, to engage in l
preparation activities.
l 6
L
Preparation Time after Last Commuter Arrives Home (min,)
Percent (cum) 5 10 10 12 15 22 20 32 25 41 30 50 hist. 4 35 59 40 67 45 76 50 84 55 92' 60 100 Time Distribution of the School-to-Home Trip Based on available data, a reasonable estimate of the school-to-home trip travel time can be developed for the worst-case conditions.
This worst-case condition occurs:
e On school days e
Between the hours (approx. ) - of 9 :30 AM and 1:30 PM During this " window" of time, school children are at school, all buses are at their respective depots and all bus drivers are off-duty.
This condition translates into the longest-travel times, as follows:
Approximately 45-90 minutes are required to assemble e
bus drivers and to move the buses from the depots to
'the various schools, e
Depending on the school, the time to transport the children to their respective homes is estimated at up to 90 minutes.
1 7
p l
l It, therefore, follows that the time distribution appli-cable for the worst-case conditions *, as defined, can be approximated as a linear cumulative distribution extending from 45 minutes to 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> af ter the Site Area Emergency is issued.
In tabular format:
~
School-to-Home Travel Time during Worst-Case Conditions Percent (cum.)
15 0
30 0
45 0
60 11 75 22 lDist. $
90 33 105 44 120 56 135 67 150 78 165 89 180 100 Since all schools are assumed to receive the tone alert activitation concurrently at time = zero, then Distri-bution 5 applies to both the Activity 1-5 and to the Event 5.
The households in the area may be divided into two classifications:
1.
50 percent with no children in school 2.
50 percent with school children.
For the latter classification, we will have to compare the school-to-home time distribution with the computed " ready-to-evacuate" time distribution which is based on the assumption that the children are at home.
This comparison is necessary to determine to what extent, if any, the school-to-home trip delays the ready-to-evacuate status.
- The probability of an accident occurring during the worst-case window is calculated as:
180 school-days / year x 4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> / school-day = 0*082 365 days / year x 24 hours2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br /> / day or 8.2 percent 8
o Calculation of Time Distributions The computational procedures are detailed in Note B.
The " events" and " activities" are also identified there.
Applying Algorithm No. 1 to Event 2 and Activity 2+3 (Distributions 'l and 2) yields the.following time distribu-
' tion for Event 3 (commuters start trip home).
Elapsed Time (min.)
Percent Starting Home (cum) 5 0
10 3
15 14 20 31 25 46 30 59 lDist. Al 35 70 40 78 45 86' 50 92 55 96 60 98 65 99 70 100 The time distribution for Event 4 (commuters arrive home) is obtained by applying Algorithm 1 to the time distrib'utions of Event 3 (i.e. Distribution A) and to that of Activity 344 (i.e. Distribution 3) :
Elapsed Time (min.)
Percent Arriving Home (cum) 5.
0 10 0
15 0.3 20 1.9 25 5.5 30 11.2 35 18.8 40 27.6 45 37.0 50 46.6 55 55.6 60 63.5 65 71.0 70 77.3 75 82.8 80 87.3 85 90.8 9
Elapsed Time (min)_
Percent Arriving Home (cum) 90 93.5 95 95.6 100 97.1 105 98.2 110 98.9 115 99.4 120 99.7 125 99.9 130 100.0 For computational convenience, this distribution and Distribution 4 will be compressed and percentages rounded as indicated.
The above distribution takes the following form:
Elapsed Time (min)
Percent Arriving Home (cum) 10 0
20 2
30 12 40 2C 50 47 lDist. Bl 60 a
70 77 80 87 90 94 100 97 110 99 120 100 Distribution 4 becomes:
Preparation Time after Last Commuter Arrives Home (min)
Percent (cum) 10 12 20 32 30 50 Dist.
4' l 40 67 50 84 60 100 10
Applying Algorithm 1 to Event 4 and to Activity 4+6 (Distributions B and 4I) yields the following time distri-bution for Event 6.
Percent Leaving Home to Begin Evacuation for Households with No Elap=ad Time (min)
Children in School (cum) 30 0
40 2
50 6
60 14 70 25 80 38 90 52 lDist. d 100 66 110 78 120 86 130 92 140 96 150 98 160 99 170 100 For that half of the households within the EPZ which have children in school, it is necessary to calculate the joint dsitribution, using Algorithm No.
2, of the independent time distributions of Events 4 and 5 (i.e. Distributions 5 and C).
First, we must recast Dist. 5 to employ the same histogram structure as used in Dist. C (i.e. intervals of 10 minutes)
School-Home Travel Time (min)
Percent (cum) 0 50 4
60 11 70 19 80 26 90 34 100 41 lDist. - 5'l 110 48 120 56 130 63 140 70 150 78 160 85 170 92 180 100 11
1 The joint distribution *.of Dist. 5 and C is:
Percent Leaving Home to Begin Evacuation for Households with Elapsed Time (min)
Children in School (cum) 30 0
40 0
50 0
60 2-70 5
80 10 90 18 l Dist. Dl 100 27, 110 37 120 48 130 58 140 67 150 76 160 84 170 92 180 100 In applying Algorithm No.
2, Dist. 5 ' was selected as Time Distribution No. 1 Table l' displays the intermediate calcula-tions.
Note that the delays associated with the school-to-home travel produces a distribution (Dist. D) which is skewed to the right relative to the distribution (Dist. C) for households with-out. children.
To obtain the time distribution for all households departing on the evacuation trips (i.e. those with and without children-),
it is necessary to combine Distributions C and D.
This is done by multiplying each respective value of percent for a specified time by 0.5, and adding.
The resulting time distribution is:
l l
I l
- Event 5 can be joined with Event 6 since it is assumed that a j
child does not participate in the preparation activities if l
he/she arrives after all adult preparations are completed.
l l
12 I
l L
d Percent of all Households Leaving Home to Begin Elapsed Tir.e (min)
Evacuation Trip (cum) 40 1
50 3
60 8
70 15 80 24 90 35 l Dist. El 100 47 110 58 120 67 110 76 140 82 150 87 160 92 170 96 180 100 k
13
a Table 1:
Computation of Joint Distribution of 5' and C' l
Distribution: 1 2
i(6)
Y P
T(6) i i
1 j
i i
40 1
2 0
50 1
4 2
4 0.06 0.24 l
60 2
8 3
8 0.14
.32 1.44 i
70 3
7 4
11 0.25 44+.88 3.07 80 4
7 5
13 0.38
.52+.04+.91 S.13 90 5'
8 6
14 0.52 56+1.12+.98+.98 7.80 100 6
7 7
14 0.66
.56+1.12+.98+.98+1.12 9.38 110 7.
7 8
12 0.78 4840.96+.84+.84+0.96+.84 10.38 120 8
8 9
8 0.86
.32+.64+.56+.56+0.64+.56+.56 10.72 130 9
7 6
6 0.92 24+.48+ 42+.42+0.48+.42+ 42+.48 9.80 140 10 7
11 4
0.96 16+.32+.28+.28+0.32+ 28+.28+.32+.28 9.24 150 11 8
12 2
0.98 08+.16+.14+ 14+0.16+.14+.14+.16+.14+.14 9.24 I
160 12 7
13 1
0.99 04+.08+.07+.07+0.08+.07+.07+ 08+.07+.07+.08 7.71 170 13 7
14 1
1.00 04+.08+.07+.07+ 08+ 07+ 07+.08+.07+.07+.08+ 07 7.85 1
180 14 8
1.00 8.0 100.0 4
SCPD KLD PRCV 100-p
=
I
/
i
- ~
/
i
/
/
/
60 l A9
/
B
/ /
40-
/
w e
v
+
20 M'
so/,
/
0 0 5 l0l's2'O 30 4'o ' 5'O 60 l'O 2'O 30 4'O 5'O 60 IO 2'O 30 4'O 50 60 lo 2O No i
l I
$h hh 1 Hour 2 Hours
? Hours un e o
m R
y Time From Initiation of Notification UN N
N l
)
j g
Figure 1:
Time Distributions for the Population l
4 Q
y Leaving Home to Begin Evacuation Trip f
y 8 j
~
y.
Distrib_ution Deccription of Evant 1
. lert Notification A
A
-Commuter Start Trips Home B
Commuters Arriver !!ome E
Households Leave on Evacuation Trip 100
/
f f
/
/
00 D
j @
/
i te U
40-H*
2
/
20 l
O
! !l l
l l
l l
l 0 5 101520 30 40 50 60 l'O 20 30 40 50 60 10 20 30 40 50 60 10 20 ff 1 Hour 2 Hours 3 Hours v1 e e
m y
Time From Initiation of Notification jN E
E I
N e
c Figure 2:
Time Distributions for Evacuation of El j
j Auto-Owning Population as Developed C4 g
g by KLD 0
,8 1
l l
On
.g 5
\\
i k
C O $
1 o
o a
A W<
g M
A
\\
o o
g m
- o C
O
\\
r4 U
O D
k 4
g H
N i
- N 9
O g
l
\\.
e4o 1
\\
-S fo E3 E
8y%
i en E
\\
c o
~8z
- o
.\\
b1?
N c
c e
\\
e a ?,,
N e
A o
308 3
M
< A -8
\\
E 3 W
%\\
o o
E N
ns E
c I
P gg o
.o II m
k
\\
.,4
\\
11 u
g
\\
\\
54
\\
g
-S II
\\
s si
'\\
o EF E s
"O $
s?%%
p =5
\\
~
\\
B 'c 5 n
\\
%.o=
o amis, %
u
em O
N *** en
.O m
- '* eun,%
.e4
\\g
" ' * * = =,
g b
b s,
j N
O o
%==
?
u
\\
8 5
E e
S.$e g o
3 g $$.x
\\
N 2
R.2
-S
-' E f
h ES otAo h
Soc $b o
=
- a. c m s
~
o%
--e N
g t
b o
_z g
g g
R S
S
?
o o
o e6eauso2ad 17
SCPD - Two llour Loading - Case 12
""-8 SCPD - Three IIour Loading - Casa 21
PRC Voorhees 100 p as 888 p/
/,
80 l
e 6 0 _-
l l
e
/
?
/
l' s
8 g
40-
/
/
/
/
O_
f g
/
/
0 8
b i
i i
i i
i e'
=
0 5 101520 30 40 50 60 10 20 30 40 50 60 10 20 30 40 50 60 10 20 30 i
i i
i 1
I I
fh hh 1 IIour 2 !!ours 3 liours us o o
m T
Time From Initiation of Notification O
N
{[E [
g Figure 4:
Co:aparison of Trip-Generation Time e
<o y
y Distributions for Case 12, Case 21
@4 g
and PRC Voorhees S
2
Y LDiscussion l
It is of interest tofcompare the three time distributions i
' of-the Evend; " Households departing on Evacuation Trip", as
-presented by:
e Suffolk County Planning Department-(SCPD) which was
-used for all the studies in Appendix A of the LILCO Plan.
e PRC Voorhees as used for their Preliminary Estimates of Evacuation Time for the 20-mile-EPZ.
e The distribution developed by this analysis (KLD) and tabulated as Distribution E.
As is indicated in NUREG 0654,.the zero time is taken as the. time that the alert is sounded.
This occurs at the Site Area Emergency stage.
It is assumed, for purposes of properly locating the SCPD time-distribution (which is related to the time at which the advisory to-evacuate is announced), that 15 minutes elapse *between the Site' Area Emergency and the General Emergency declarations, and another 10 minutes elapse to the issuance of the advisory to eyacuate.
Figure 1 presents-the graphical representation of these.
three time distributions. - All indicate that the trip generation process starts between 40-50 minutes after the sirens are acti-vated.
The SCPD distribution asserts that there is a very slow rate-of vehicle demand at the outset but that this rate increases rapidly with time and then falls off near the end of the two-hour loading period.
At worst, the SCPD curve differs from the I
-PRC curve by less than 15 minutes over the range of time from the outset unti1~90 percent of the population has departed their homes.
The KLD and PRC curves are within 10 minutes of one another from the beginning of the trip' generation process to the point where 98 percent of the population has begun the evacuation trip.
t-
=The long " tail" of the PRC distribution, to a large extent, re-i flects their-pessimistic assumption that "40 percent of the popu-lation is estimated to require up-to 90 minutes to prepare for evacuating their homes."
Also, no consideration is given to the likelihood that some households can prepare to evacuate in parallel with the worker's work-to-home trip, as was done in the KLD analysis.
...for households with access to a private vehicle 19
Figure 2 depicts the cumulative distributions developed in this report
- for all events.
Figure 3 compares the KLD and PRC distributions.
As indicated in Figure 3, and noted earlier, the time distributions for the evacuation trip generation event, are in close agreement with the exception of the long " tail" in the PRC version.
The time distribution for the " commuter arriving l
,home" event are in agreement to within 10 minutes for all values of percentage.
The. earlier'two distributions are not in agreement.
The PRC distribution indicates that it takes 25 minutes for 35 percent of the public to be aware of the, accident.
We argue that the sounding of the siren will alert this portion of the population immediately.
The reason that the later distributions are in general agreement, is that the PRC assumptions of the work-to-home travel time are optimistic, relative to the empirical data obtained by the NCTR survey.
Figure 4 compares the SCPD distribution for Case 12 used in Appendix A, the PRC distribution and the " extended" distribution used for Case 21.
As indicated,the distributions used for cases 12 and 21 bracket the tail of the PRC distribu-tion.
The PRC distribution asserts that people leave home more rapidly (i.e. earlied at the beginning of the evacuation, than do the SCPD distributions.
This more rapid response would tend to lower evacuation travel times, relative to the SCPD distribu-tion.
Since the resulting evacuation time estimates are not sen-sitive to these differences in trip generation distributions **
then it follows that no significant difference in evacuation time estimates would result if the KLD trip generation distribu-tion (or the PRC distribution) were used instead of the SCPD distribution.
f I
l l
l l
- Distributions 1, A, B and E
- ...i.e.
between the two hour and three hour distributions of cases 12 and 21, respectively.
20 l
l
Note A To calculate the distribution of preparation time after the commuter arrives home, for those families which prepare in paral-1el with the work to home trip, use the following approximation of the work-to-home trip time distribution.
Travel Time Home (min)
Percentage (cum) 10 25 20 50 30 75 60 100 Percent of Comruters Arriving Remaining Time Required to Home who Experience the In-Prepare After Comruter ~
dicated F-ining Preparation Aggregate Arrives Home Time Percent Work-to-Itxne 10 20 30 60 Travel Time (min) 5 min.
(10 + 30 + 50 + 90) x.25 45
=
10 min.
(10 10 10 5) 9
=
15 mi.n.
(10 10 10 5) 9
=
20 min.
(10 10 10 0) 7
=
25 min.
(10 10 5
0) 6
=
30 min.
(10 10 5
0) 6
=
35 min.
(10 5
5 0) 5
=
40 min.
(10 5
5 0) 5
=
45 min.
(5 5
0 0) 3
=
50 min.
(5 5
0 0) 3
=
55 min.
(5 0
0 0) 1
=
1 60 min.
(5 0
0 0)
=
100 For example, if the ccmmuter arrives home after 30 minutes there is a 50% probability that preparation is completed at that time by another adult, another 10% probability that preparation is completed in 5 more minutes, another 10% probability that pre-paration is completed in 10 more minutes, etc.
This data is obtained from the first time distribution of pre-paration time.
21
Note B i
Analysis of Time Distribution
.The evacuation process leading up to the time that people embark on their evacuation trip, consists of a sequence of events.
Each event experienced, prepares the household-for the-subsequent event.
Events may be in " series" (i.e. to undertake an event im-plies the completion of all preceding events) lor may be in paral-lel (two or more events may take place over the same period of time).
Events in series are functionally dependent on one-another; events in parallel are functionally independent of one-another.
The relevant events are:
Number Event i
1 Schools aware of accident potential 2
Public is aware of accident situation 3
Workers depart place of work 4
Workers arrive home 5
Children arrive home from school-6 Families leave home to evacuate area Associated with each sequence of events is one or more activities, as outlined below Event Sequence Activity 2
-am-3 Prepare to leave work l
3
-4>-
4 Travel-from work to home 1
-wn-5 Travel from school to home 4
-am-6 Prepare to leave home 5
-+=- 6 No activity These relationships may be depicted graphically:
2 3
4 e Event 6
--am Activity 5
1 Time Increasing 22
s Note that_ events 3,4 and 5 are dependent, respectively on events 2,3 and 1;-event 16, on both 4 and 5.
Events 1 and 5 are independent of events 2,3 and 4.
The " initiating" events (insofar as evacuation is concerned) 1 and 2 depend on prior activities which are not shown.
Event 1 depends on the reception of tone-alert signals at the " Site Area
. Emergency" stage of the' accident.
Event 2 depends on the recep-tion of siren signals and of emergency broadcasts by the media.
Associated with each event is a time distribution reflecting the range of time associated with the preceding activity.
This range of time reflects the fact that different people have dif-ferent activity response times.
When an event, k+1, depends upon a prior event, k, then the time distribution of this event, k+1, can be calculated if:
The time distribution of event, k, is known, and
-e e
The time distribution of the activity k+k+1, is known or can be estimated. -
Algorithm No. 1 (Dependent Events)
Computationally, these distributions are represented as-histograms. -The following' definitions apply:
1 Let T.(k) = Time at which the ith element of the histogram has 1
completed event, k; i=1,2,...,I t
= Time required for jth element of the histogram to' I
perform the activity, k+k+1; j=1,2,...,J l
P (k) = Percent of population represented by the ith ele-ment of the histogram for event, k.
That is, P. (k) perecent of the population has completed the event, i
k, at time, Tg(k), over the interval, AT=T (k)-T _y (k).
g p.
= Percent of population which requires t minutes to 3
J complete activity, k+k+1
"(k+1)= Time at which the mth element of the histogram has T
completed event,-k+1; m=1,2,...,i+j-1,...,I+J-l 23
... ~... -...
- (k+1) = Percent of population represented by_the mth ele-P ment of the histogram for event, k+1 That is, t$e(k+1) percent of the population has completed P
event, k+1, at time, T (k+1), over the' time in-terval, AT=T,(K+1)'- T,_y(E+1)
- Then, P (k+1) = )[
P (k)p /100 i, j 4*
i+j-l=m 1
T,(k+1) g(k)+t3 for any i+j-1=m
=T I+J-1 Note: [
Pm (k+1) =1 m=1 Algorithm No. 2 When an event, k, depends on two prior independent events, then the time distribution of'this event must be determined as follows:
1 '
Calculate two independent time distributions of event, k-e a) One based upon one. prior event and b) One based upon the other prior event i
e Then calculate the joint distribution of these two separate independent time distributions.
( }(k),P,(
(k) = As defined above for P. (k), where the I
Let P
1 superscripts denote the separate in-dependent time distributions. P (k) de-notes the joint probability
'(k),T (k) = As defined above for each distribution.
T g
Yg = Percent of population delayed to time, T (k), due to laterarrivalofthepopulationofdistrkbution2, relative to population 1 R (k) = Proportion of the population of distribution 2, whichhagyplreadyexecutedtheevent,k,atthe time, T (k)
- Then, 24
.~..
Select as distributien, 1, that which executes the event later than does distribution 2.-
Specifically, the following condition must apply:
(2)
(l)
T T
Process the elements, i, of the histogram of distribution 1, in sequence:
i=1,2,...I.
Set all y =0 initially.
P.( }(k) 1(k) =
R 100 where m = min [J,m' where Tge. ( '
(10
=T J = maximum number of elements in histogram of distribution 2 P (k) =R (k)P kk)+yg f(k)
=T (k)
T If m < J, then compute
+
P (k) ; q = m+1,m+2,...,J y, = Y s s = i+1,i+2,...,
This procedure computes P (k) and T (k) for all i=1,2,...I.
(
If Ty(k)
<T (k), then y
P
=y
- q = I+1,I+2,...,J Example No. 1
Dependent Events --Application of Algorithm No.1 Time Distribution of event, k Time distribution of activity, k+k+1 P.(k)
T i
i(k) 1 P.
t.
1
_2.
1 1
30 10 2
50 20 1
50 20 3
10 30 2
30 30 4
10 30 3
20 40 25
-l
.y Let m = 1 Then i = j = 1 y(k+1) + (30) (50)/100 = 15 ; Ty(k+1) = 10+20=30 P
Let m = 2 Then i+1, j =2 ; i=2, j=1 (50) (50)] /100=34 P2(k+1)
[(30) (30)
=
+
2(k+1) = 10 + 30 = 40 T
Let'm = 3.
'Then i = 1, j = 3 ; i = 2, j = 2 ; i = 3, j = 1 P
+
=B
(
+
- 0) + (10) (500 /100 = 26 3
T
+
+
3 Let m = 4 Then i = 2, j = 3 ; i = 3, j = 2 ; i = 4, j = 1 4(k+1) = 60 P4(k+1).= 18 T
Let m = 5 Then i = 3, j = 3 ; i =4, j = 2 P
+
+
S 5
Let m = 6 Then i = 4, j=3; P (k+1) 2, T (k+1) = 80
=
Time distribution of event k+1 g(k+1) i P (k+1)
T 1
-15 30 2
34 40 3
26 50 4-18 60 5
5 70
'6 2
80
(
Example No. 2:
Independent Events--Algorithm No. 2
(
Time = Distribution No. 1 Time Distribution No. 2
(
(
i P
(k)
T (k) j P
(k)
T (k) l' 50-20 1
30 10 2
30 30 2
50 20 3
- 20 40 3
10 30 4
10 40 26
..,-.,y--_
,. ~ -.. ~,
y v~.--,. -
,..e_
Let i = 1, T
( k) = 20 y
R (k)
= 0.8 ; y
=0+
(50) =5
=
f 2
0 v
=0+
(50) =5 3
g P (k) = 0.8 (50) + 0 = 40 y(k) = 20 T
( }(k) = 30 Let i - 2, T2 2(k)
= 0.9; y3" 0
=
+
(
R P2(k) = 0.9(30) + 5 =-32 T2 (k) = 30 Joint Distiribution Let i = 3, T b
I I
3 R I
.0 2
3 3
=
3 l
3 28 40 P
+
3 T
3 Note 1:
These algorithms require that all discrete values be equally-spaced and that such spacing be identical for all distributions.
Note 2:
Although the two examples used the same distributions, the final results were quite different, reflecting the disparate analyses performed.
Note 3:
The Joint Distribution for Example 2 is skewed to the right relative to the initial Time Distribution No. 1, reflecting the delay associated with satisfying the need to wait for the event of Time Distribution No. 2 to be satisfied.
27
KLD TM-77 Estimated Evacuation Times for the Entire Population within the Emergency Planning Zone for the Shoreham Nuclear Power Station, Considering the Effects of Uncontrolled Evacuation, Voluntary Evacuation, Inclement Weather and Accidents Submitted to Long Island Lighting Company 175.Old Country Road Hicksville, NY 11801 by KLD. Associates, Inc.
300 Broadway Huntington Station, NY 11746 under Purchase Order 364451 by Edward Lieberman, P.E.
Vice President
IsD TM-77 Estimated Evacuation Times for the Entire Population within the Emergency Planning Zone for the Shoreham Nuclear Power Station, Considering the Effects of Uncontrolled Evacuation, Voluntary Evacuation, Inclement Weather and Accidents
{
Submitted to Long Island Lighting Company 175 Old Country Road Hicksville, NY 11801
.u by KLD Associates, Inc.
300 Broadway Huntington Station, NY 11746 under Purchase Order 364451 by w
Edward Lieberman, P.E.
Vice President
TABLE OF CONTENTS Section Title Page 1
Introduction 1
2.
Methodology 2
3.
Impact of Shadow Effect on Estimated Evacuation 8
Travel Times within the SNPS EPZ -- Original Evacuation Plan 4.
Impact of an Uncontrolled Evacuation on Estimated 12 Evacuation Travel Times within the SNPS EPZ --
With and Without Consideration of the Shadow i
Effect 4.1 Comparison of Uncontrolled and Planned Evacuation 13' Procedures
~- No Shadow Effect 4.2 Comparison of Estimated Evacuation Times for 13 Uncontrolled and for Planned Evacuation Pro-cedures with a Shadow Effect Due to 25 Per-cent Voluntary Evacuation 4.3 Comparison of Estimated Evacuation Times for 17 I
Uncontrolled and for Planned Evacuation Pro-cedures with a Shadow Effect due to 50 Per-cent Voluntary Evacuation 4.4 The Impact of Winter Inclement Weather 17 4.5 Summary 23 4.6 Conclusions 23 i
l l
5 Impact of Accidents on Estimated Evacuation 24 Times l
1 t
i i
.'6 l
l 1.
Introduction This report presents.the results of a series of analyses to estimate evacuation times from the Emergency Planning Zone (EPZ) of the Shoreham Nuclear Power Station (SNPS).
These analyses were based upon the possibility that the original Evacuation Plan (l_) would not be implementable due to the un-willingness of local authorities to participate in the process.
Specifically, the original plan assigned evacuation routes to be taken by the populace in each of 19 " zones" comprising.
the EPZ. This Evacuation Plan also described' detailed control tac-tics which were consistent with this assigned routing and were designed to expedite the evacuation of people from within the EPZ.
The plan called for the existing traffic signal control system to be set on the " flashing" mode and to be replaced with police personnel trained expressly to implement this plan.
In February, Suffolk County indicated they would not imple-ment any off-site emergency plan.
One alternative to the original Evacuation Plan is a LILCO-sponsored public information program and the installation of advisory signing along all evacuation routes to guide the evacuating populace. hit w M be-eeen :Nt'the exiiti ~
hignal~contror would wnt.ino u6rmally and that the special control tactics. recommended in the original plan would not be
/
implemented.
M i
Realistically, it must be assumed that vehicle routing during evacuation under such " uncontrolled" conditions would differ significantly from that which is delineated in the Plan (1).
Consequently, it should be expected that this less ef-ficient routing coupled with the absence of applied control would translate into-longer evacuation times.
Ahother set of conditions which was addressed, was the so-called " Shadow Effect."
This effect asserts that a portion of the populace who live outside the EPZ, will voluntarily evacu-ate, thereby impeding the exodus of people from within the EPZ.
Due to the geographical characteristics of the SNPS EPZ and its surrounding environs, it has always been assumed that any evacuation movement will be~toward the west.
Consequently, l
it must be expected that some portion of the voluntary evacu-ating vehicles originating east of the EPZ, will enter the EPZ and move through it on their travel westward.
(L) Appendix A:
SNPS Evacuation Plan
~
1 l
i yye
-w-,--nn-,-r,,
.,-.--w,,,--,-w,-,--,,--,----------,wn-----ann.,---~-r----,----..n----
Still another set of studies addressed the impact of dis-abled vehicles on estimated evacuation time.
Since accidents are " rare events" in both space and time, there is always a high degree of uncertainty associated with such " macro' studies.
Nevertheless, some idea of the sensitivity of evacuation time to the expectation of accidents should be investigated.
Following a description of the methodology used, the sub-sequent sections document a total of three studies:
1.
Estimation of evacuation travel times for the Evacuation Plan documented in (1_), including the " Shadow Effect" 2.
Estimation of evacuation travel times' for the "Uncon-trolled" Evacuation, with and without the " Shadow Effect" for both normal and inclement winter weather 3.
Estimation of evacuation travel times for the Evacustion Plan documented in (1) including the effect of expected accidents.
2 Methodology 4 :
.t It was necessary to represent the roadway system and all aource points *, for the 10-20 mile. regions to the east (and south), and to the west, of the SNPS EPZ.
Exhibit 1, taken from (1), is the network within the EPZ; Exhibits 2 and 3 show the East and West Metworks:
to the east and south, and to the west of the EPZ, respectively.
In all Exhibits, the red nodes represent source points (i.e. origin nodes) while the blue nodes represent destination points.
The internal nodes, which generally represent inter-sections or locations where traffic streams merge, are shown in gre'en in Exhibit'l ('within the EPZ) _and in - orange in Exhibits
.2 and 3 (outside the EPZ).
The East and West networks were de-signed to overlay the EPZ network; those nodes which are with-in the EPZ are shown in yellow on Exhibits 2 and 3.
j Demographic data projected to 1985 was provided by LILCO.
This data was translated into vehicle trips by assuming that each vehicle, on the average would, transport three occupants.
Furthermore, it was assumed that the evacuation trip generation
- A " source point" is the location of a specified number of l
evacuation trips which enter the evacuation network at speci-fled rates.of departure.
2
EXHIBIT 1 (To be provided by LILCO)
Identical to Exhibit 1 in Appendix A l
l 3
10 mde radius
- 1 e
1 94 s
C j
g< 3,,
g
.n,
.oi,
, = >
4, in s
00
,y 1,.
II 14 g,4 10 d
9,,
gu
. 064 so.
I, 120
__,,,,t,
.o
,, ' MrggIt 1
O II
.2 so, gg
,,g 04 08
.9
,, g..
w,
,F
--e,,e
~
o
^
.oi.
,o g
-y
~
'I' '
.. \\p"
'22 d
/
,*.Q>d,
-q'O
~ - o" _ _
i
-a,
s.
s.
_n. -
f.3.
h5'
.o2, m.,,,,
.3
,o
'NIISe' g,
og 43
,,8
- *S N
t,. 8
~~
%9
f 4='""
t
,4 no g
29 e-9
_ _ _ _.,g
~
s i,
I' g,,.
02.
,3g 2,
4 g-
- -Q*
.s,
.on
,o,,
,f 4
'N h"
I 6'
\\
t4 1
~
.... ~..
f Q..
3R0 f
A3ER-~LRE CARJ Q ORIGIN NODES h ENTRY / EXIT NODES O inteRu^t NOoeS O NOoeS wirsin eez Q"
p.,
Also Available Un i.
=
Aperture Card na 3'5 g5 7,#"
its i,
ir, N4" i4e 10 niilo sad.us iis j
,J EXHIBIT 2 WEST NETWORK
- >' R R1 190n1ao_nm
t l
l I
29
,,o r r\\,
i m
i OA1J 1
222 r
6
. 6 52 23 9*
- n. 4 6 m,,
66
.2 gs gg 1*us t9 T Oo-22s era I
W5 89 E
tar g
d'*___
.3 m
MM
=
sun" M r
90
-st as
,<4et 423 Iu
?,
,o, too ts.
Qo
( onin
(
>=
'O, e Y'..
6
- e
,40 e.
o' i,
c.
do 69 sg l
t l
i i
{
ne 43
/
. - 02 b
wp l$
- M.
i
\\
l
-~
~ __'~~~-~~ ~
~----'--,m_.
..M I
j 9
/
a 784 l 10 m.fe raa,%
S,,..
"~~
ar 4
/
i Q 3
4
', g_ _ _ _
9 e"
i
=-
i a> y EO 4 MJJN 1
8 9
.
- a, 04 q
t
?."'
2 33 ORGeg pg
)
- o 's O mmYEur %
q Oemam %
e Orecesw 1'
I et, I
tri t
174 M
%V
/
~
h
.R
')
9erturec,73 smi. s
?
wa:
k P
b
. e, 9
I 9
147 O
o EXHIBIT 3 7
EAST NETwogg I
.s ur 6203
l process would extend over a two-hour period within the EPZ, and over a four-hour period outside the EPZ, where there are no i
KLD personnel surveyed the entire roadway system to gather information which was used as a basis for preparing the necessary l
data base.
Signal timing and phasing data were taken at major intersections.
For the East and West networks (Exhibits 2 and 3, respect-ively), it was necessary to develop a " Trip Table" which spe-cifies origin-destination traffic demands.
This table identifies the destinations for the vehicles beginning their trips at each source point.
The development of these tables employed " common-sense" assumptions,. consistent with the overall westward flow of evacuating traffic, and with the assertion that a no police-implemented control or routing strategies would be present.
"he input data streams for these additional networks were then prepared and debugged.
The DYNEV computer model was then applied to produce the required travel time estimates.
l The following sections will present several comparisons of results, representing different points of view.
In the in-terest of clarity, we have assigned symbols to each study so that the reader can easily relate these results to the under-i lying conditions.
l All case studies associated with the planned evacuation of the EPZ as described in (1), will be assigned the symbol P.
In addition, a subscript will indicate the assumed percentage of voluntary evacuation.
Thus, for example, the results for case study, P25, describe the condition of planned evacuation in the presence of 25 percent voluntary evacuation.
To re-present inclement weather condition #, we will add a super-script of the letter, R (for Rain), or S (for Snow).
If there is no superscript, weather conditions are normal.
Thus, P indicates con-ditionswithsnoworicypavementsand25percencv}5 oluntary evacuation.
For the case studies associated with the " uncontrolled" evacuation of the EPZ, we assign the symbol, U.
The use of sub-scripts and superscripts described above, will apply to these i
cases, as well.
Table 1 is a summary'of all case studies which have been conducted and which are discus.1ed in the following sections.
- For Rain and Snow, free speeds are assumed to be reduced by 20 and 30 percent, respectively; capacities were also reduced by 20 and 30 l
percent, respectively.
6
.._ ~_
J Table 1:
Summary of Evacuation Case Studies l
1 Voluntary i
Case Evacuation Weather l
Study Outside EPZ Conditions Description 1
O No voluntary.
Normal Planned evacuation of the entire EPZ with no
(
P j
evacuation Shadow Effect l'
P25 25% voluntary-Norma.1 Planned evacuation of the entire EPZ including the j
evacuation Shadow Effect due to 25% of the population in the area j
between 10-20 miles from SNPS electing to evacuate P50 50% voluntary Normal As above, but for 50% voluntary evacuation evacuation l
Py No voluntary Inclement, Planned evacuation of the entire EPZ during inclement evacuation winter winter weather conditions with no Shadow Effect 4
i UO No voluntary Normal Uncontrolled evacuation of the entire EPZ with no I
evacuation Shadow Effect 8
U No voluntary Inclement Uncontrolled evacuation of the entire EPZ during j
evacuation
-winter winter weather conditions with no Shadow Effect l
25 25% voluntary Normal Uncontrolled evacuation of the entire EPZ including the U
j evacuation Shadow Effect due to 25% of the population in the area between 10-20 miles from SNPS electing to evacuate 1
t' U50 50% voluntary Normal As above, but for 50% voluntary evacuation l
evacuation s
i U,
50 vo1untary inciement, uncontrollea evacuation of the entir EPZ auring evacuation winter inclement winter weather conditions with 50% of the population in the area between 10-20 miles from i
SNPS electing to evacuate
i 3.
Impact of Shadow Effect on Estima_ted Evacuation Travel Times within the SNPS EPZ -- Original Evacuation Plan (jl).
In the original plan, voluntary evacuating traffic origi-t nating within the.. East Network (Exhibit 2) would ha denied entry to the EPZ and routed to either Sunrise Highway or to Montauk Highway.
This strategy is responsive to the Plan's primary objective of minimizing the exposure of the evacuating populace.
This objective is satisfied by restricting evacuees' movements so that.their paths of travel come no closer to the SNPS than absolutely necessary.
The evacuating vehicles originating within the EPZ will gain access to that segment of Sunrise Highway which lies (just) within the EPZ well before any substantial traffic originating within the East Network.
It follows that these voluntary evacuees from the east will trail the evacuating vehicles from j
within the EPZ, rather than impede them.
Consequently, consis-tent with the Evacuation Plan, the trips originating within the East Network will produce no Shadow Effect on those 4
i evacuation trips originating within the EPZ.*
Voluntary evacuation trips originating within the West Network can impede those vehicles evacuating from within the EPZ.
The extent of such impedence depends most strongly on the number of such voluntary evacuees as well as on their lo-cation within the West Network.
Another factor is the to-pology and capacity of the roadway system west of the EPZ.
In order to realistically assess the impact of the Shadow Effect and to express this impact in terms of estimated evacu' ation times, it was necessary-to conduct a vigorous analysis of the evacuating process in the West Network.
This analysis f
was undertaken by applying the same procedures as was used to estimate the evacuation times within:the EPZ (1).
Specifically, the following steps were implemented, once the input data was
[.
defined:
l.
Execute the Traffic Assignment model within DYNEV to calculate estimates of the traffic routing.
- It is recognized, of course, that a portion of the vehicles evacuating the EPZ will impede many of the voluntary evacuees originating in the East Network.
That impedance, however, is experienced by traffic at least 10 miles from SNPS.
4 8
2.
With this information, execute the Traffic Simulation model within DYNEV to calculate estimates of evacu-ation travel times.
This procedure was exercised twice:
o Assuming that-25 percent of the population within the West Network elected to evacuate o
Assuming that 50 percent... elected to evacuate.
Of course, the analyses of the West Network evacuation included the traffic volumes exiting the EPZ and entering the Westi, Network.
Thus, t,he conges, tion enccuntered by vehicles evacuating the EPZ reflected the total traffic demand:
the traffic originating within the West Network plus the traffic evacuating from the EPZ.
The shadow effect was determined by comparing the evacu-ation times for vehicles exiting the EPZ on the assumption that there M voluntary evacuation within the West Network, with the times obtained from the earlier analysis (1) which did not consider voluntary evacuation.
Specifically, we compared the results'of case studies, PO, P25 ""
50*
Table 2 is a tabulation of estimated evacuation times for these case studies.
These data indicate the required i
evacuation time for 50 percent of the original population, for 90 percent; and for 100 percent, respectively.
Figure 1 pre-sents, in graphical format, the cumulative distributions of evacuation times for these three case studies; this format is in accord with the guidelines of the NRC/ FEMA Report, NUREG 0654 As indicated by these results, the impact of the Shadow-i Effect is very sensitive to the proportion of the population within the West Network, who elect to evacuate.
If 25~per-cent, or less, elect to evacuate, then the Shadow Effect is minimal -- it would take 15 minutes longer to evacuate the first 50 percent of the population originating within the EPZ and 20 minutes longer to evacuate everyone from the EPZ.
If 50 percent of the population within the West Net-work elect to voluntarily evacuate, the impact of the Shadow-Effect-is more pronounced.
It would take 20 minutes longer to evacuate the first 50 percent of the population from the EPz, and I hour and 40 minutes longer to evacuate everyone from the EPZ, relative to the condition of no voluntary evacuation.
9 i
. ~
i Table 2:
Estimates of the Elapsed Times Required to Evacuate the Population from the
.SNPS EPZ - Cases Po, P25 and P50 Evacuation Times (Hours-Minutes) to Evacuate 50%
Evacuate 90%
Evacuate the of the of the Entire Case Population Population Population P
l-40 3-20 4-35 O
25 1-55 3-40 55 P
2-00 4-35 6-15 P50 1
(
9 i
I
(
\\
10
x Perc6nt Case Vol. Evac.
Study O
PO 25 P 5 SU 6
50 100 y '...
90
'/
o 8C A
,o
/
/
o'
$7C e
/ s i
e o
a
/
i 8 6C S'o f..,
u
.,, o e
6 f.',
p a.
e SC
.-),
-a M
M 4C S) i
/
a
./
3C
?
}
2C
/l 10 j
C O
1 2
3 5
6 7
8 9
Time in Hours Figure 1 Cumulative Distributions of Estimated Evacuation Times from the SNPS EPZ during the Planned Evacuation, Normal Weather
t 4
These results are consistent with known behavior of traffib flow:
The small impact of the Shadow Effect on the evacua-e tion.of the first 50 percent of the EPZ populace reflects the time lag which is characteristic of the build-up of congestion.
That is, congestion is initially local in context, then becomes systemic as queues grow in length and create large delays.
Doubling the number'of voluntary evacuees (from e
25 percent to 50 percent) serves to quintuple the incremental evacuation time (from 20 minutes to I hour-40 minutes) required for+the EP2 populace.
This non-linear relationship between travel time and traffic demand is a well known attribute of congested traffic flow.
4.
Impact of __ an Uncoratrolled Evacuation on Estimated Evacuation Travel Times within the_SNPS EPZ -- With and Without Consideration _of the Shadow Effect As discussed in Section 1, the routing of evacuating Q
vehicles within the EPZ if there were no active control would i\\-
differ from that determined f'r the Planned evacuation, as o
detailed in (1).
Also, it must be expected ~that a portion of the voluntary evacuating vehicles from the East Network would. enter the EPZ along the Long Island Expressway (LIE),
thereby increasing the number of vehicles which would exit
'the EPZ.
To properly quantify the-impact of these conditions, it was necessary to perform the same rigorous analysis of l
evacuation-travel on the East, Network (Exhibit 2 ) as was
(
undertaken on the-other two networks.
Four sets of studies were performed:
1.
No Shadow Effect 2
Shadow Effect assuming 25 percent voluntary evacuation x
3 Shadow Effect assuming 50 percent voluntary evacuation 4.
Shadow Effect assuming 50 percent voluntary evacuation
[
under inclement winter weather conditions.
2 Initially, we executed the Traffic Assignment model to calculate the expected routing of traffic within the East _
Network.
With-this information, we were then in a position to execute the simulation model to calculate estimated travel times.
The procedure used for the latter three sets of studies 7
is outlined below:
3-12 x
+
+ + ~ *
- t rr->
t sy t--,s
,w
---ew
+we
-etr r--*e e-,
e is-e-
---e+'-r--une---.+-www-=
am*-.a
-e won + e
--e---,%-,+=----e
~
L-t 1.
Execute DYNEV to simulate traffic on the East Network-2 Use these results to determine the rate of inflow to the EPZ, of traffic evacuating from the East Network 3
Execute DYNEV to simulate traffic on the EFZ Network 4
Use these results to determine the rate of outflow from the EPZ and into the Wost Network 5.
Execute DYNEV to simulate tJaffic on the West Network, then calculate the Shadow Effect 6.
Document the results.
The results of each set of studies is presented separately so as to afford a comparison of the evacuation times for Uncontrolled with Planned procedures.
4.1 Comparison of Uncontrolled and Planned Evacuation Procedures -- No_ Shadow Effect Here, we, _ compare the results of case study Uo with those of case study P.
Table 3 tabulates these results 0
while Figure 2 presents their cumulative distribLcion of evacuation times.
It is seen that removing all control tactics designed to expedite evacuation. travel will increase evacuation travel times.
The increased time to evacuate the initial 50 percent of the population is 15 minutes; for 90 percent, 30 minutes; for the entire population, 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 35 minutes.
Thus, an uncontrolled evacuation will primarily delay the evacuation of the last 10 percent of the population.
4.2 -Comparison of Estimated _ Evacuation Times for Uncontrolled and for Planned Evacuation Procedures with a Shadow Effect Due to_25 Percent Voluntary Evacuation The results of case studies P 5, UO and U 5 are 2
2 compared in Table 4.
Figure 3 presents the cumulative distri-butions of evacuation times for case studies U25 and P25 As is indicated, the increased time to evacuate the initial 50 percent of the population, due to the Shadow Effect (comparing cases U25 and 0 ) for the Uncontrolled 0
Evacuation is 30 minutes; for 90 percent, 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br />; for the entire population, 30 minutes.
Comparison of the evacuation times for the Uncontrolled Evacuation with those of the Planned Evacuation, in the presence of 25 percent voluntary evacuation 13
Table 3:
Estimates of the Elapsed Times Required to Evacuate the Population from the SNPS EPZ - Cases PO and UO Evacuation Times (Hours-Minutes) to Evacuate 50%
Evacuate 90%
Evacuate the i
of the of the Entire Case Population Population Population Pg 1-40 3-20 4-35 Ua 1-55 3-50 6-10 Table 4:
Estimates of the Elapsed Times Required to Evacuate the Population from the SNPS EPZ - Cases P25' UO and U25 Evacuation Times (Hours-Minutes) to Evacuate 50%
Evacuate 90%
Evacuate the of the of the Entire Case Population Population Population P25 1-55 3-40 4-55 Ug 1-55 3-50 6-10 U
2-25 4-50 6-40 25 14
\\,[,\\
9 gn imuss 8
A
'l mo r n f o i
s t e a m u i c T a 7
v nE o
id t e al ul c o a r vt 6
E no d c e nr s
t Ue r
a h
u mdt o
i na t ae s
W 5
Ed n
i el f na e
onm m
ar r
i nl o T
oPN "
i t ed f'/
uh n bt a 4
i rrt t oc f
sf e i
f DZf PE eE v
w y
iS o ed 3
s u O
at P
o, tPd aN a CS lSh u
S 4
I.**-
me n
1 uh o o d 1
CtN i
e t
n a
n u a c
l e
/
2 2
a P
c
/
v m
/-
e E
o r
/
u i
g T
i
/
F 1
~
0 0
C 0
C C
C 0
9 8
7 6
S 4
3 2
0 C
0 C
C 1
1 Ee$*
% o>w%m"Bu Y
I
\\\\ll l
1i l
1ll
\\l l
l 1
1
!I!
l
Case Evacuation Study Planned P25
................... Uncontrolled U25 100 t
r 90
**e..-
8C f
,,/
$7C g sc a
u p e a
o.
e 5C A
. #v'.
aa
/
/.* -
a E
a
- 3C
/
l 2C 10 s
l l
C 0
1 2
3 5
6 7
8 9
Time in Hours l
Figure 3 Cumulative Distribution of Est!. mated Evacuation Times from the t.
SNPS EPZ for the Planned and Uncontrolled Evacuations, Assuming 25 Percent Voluntary Evacuation Outside the EPZ.and Normal Weather
(cases U25 and P25) indicates the increased evacuation time due to the removal of the olanned control tactics.
These increases amount to 30 minutes for the initial 50 percent of the population; 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 10 minutes for 90 percent; 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes for the entire population.
4.3 Comparison of Estimated Evacuation Times for Uncontrolled and for Planned Evacuation Procedures with a Shadow Effect due to 50 Percent Voluntary Evacuation The results of case studies P50s UO and U50 are compared in Table 5.
Figure 4 presents cumulative distributions of evacuation times for case studies P50 and U50-For Uncontrolled Evacuation, the impact of the Chadow Effect with 50 percent of the population in the West Netvork voluntarily evacuating is calculated (cases U50 and 0 ).
The increase in 0
travel time to evacuate the first 50 percent of the EPZ popula-tion is 55 minutes; for 90 percent, 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes; for the entire population, 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 5 minutes.
Comparison of the evacuation times for the Uncontrolled Evacuation with those of the Planned Evacuation in the presence of 50 percent voluntary (cases U 0 and P50) indicates the increased evacuation evacuation 5
times due to the removal of the planned control tactics.
These increases amount to 50 minutes for the initial 50 percent of the population; 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> for 90 percent; 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> for the entire population.
4.4 The Impact of Winter Inclement Weather The results of case studies POandPh,,aswellof S
Uo, U,
U50 and U50 are presented in Table 6; c/.mulative distri-O butions are presented in Figure 5.
It is instructive to make several comparisons to identify the impact of the Shadow Effect of Uncontrolled Evacuation and of Inclement Weather separately, as well as their interactions.
Table 7 presents this comparative data.
Comparisons 1 and 2 indicate that the impact of inclement winter weather alone in the absence of a Shadow Effect is some-what greater for the Uncontrolled Evacuation than for the Planned Evacuation (an increase of 85 minutes vs. 65 minutes); in either case, the impact is moderate.
Nevertheless, the combination of the effects of Uncontrolled Evacuation (vs. Planned Evacuation) and of inclement winter weather (vs. normal weather), as indicated in Comparison 3, produce an increase of 115 minutes in the time to evacuate the entire population.
17
Table 5 :
Estimates of the Elapsed Times Required to Evacuate the Population from the SNPS EPZ - Cases P50s UO and U50 Evacuat' ion Times (Hours-Minutes) to Evacuate 50%
Evacuate 90%
Evacuate the of the of the Entire Case Population Population Population p50 2-00 4-35 6-15 Uo 1-55 3-50 6-10, U50 2-50 5-35 7-15 4
9 9
9 0
18
Case Evacuation Study Planned P50 Ungontrolled P
- =. -.. -
50 100 t
l 90
[,
l
/
,e
$70 3
a 8 6C u
i.
w U w %
c SC U
.a 4J 4C o
0 o
3C r
10 1
0 0
1 2
3
+
5 6
7 8
9 Time in Hours Figure 4 Cumulative Distribution of Estimated Evacuation Times.from the SNPS EPZ for the Planned and Uncontrolled Evacuation, Assuming 50 Percent Voluntary Evacuation Outside the EPZ and Normal Weather
6 Table 6 :
Estimates of the Elapsed Times Required toEvacuatethePopulagonfrogthe S
SNPS EPZ - Cases PC, PO,U' UO, U50 50 and U O
Evacuation Times (Hours-Minutes) to Evacuate 50%
Evacuate 90%
Evacuate the of the of the Entire Case Population Population Population Po 1-40 3-20 4-35 P
2-00 4-20 5-40 O
Un 1-55 3 6-10 U$
2-10 4.-25 7-35 50 2-50 5-35 7-15 U
Uf0 4-35 7-25 9-45 S
S 20
Percent Case Evacuation Vol. Evac. Study S
Planned 0
PO O
Uncontrolled 0
U O
s
~ ~ ~ ~ ~- Uncontrolled so u
- a 50 100
' * **=~.........
b
'~
~
= **
.........=*
90 o*,,
8C f* *
- o o
o e
)
o cn 7C n
e P
/
o' c
o e
o.
u 6C
'.'e u
,o o
u H
a.
/
o e 5c
- _ /.
-.o a
.a
/
,o a 4C
~
a
.~
a u
/
s,-
t o'a au
,/
g',:',,-
3c
,o' 2c a
9 t
10 I
d 0
1 2
.3
+
5 6
7 8
9 Time in Hours Figure 5 Cumulative Distribution of Estimated Evacuation Times from the SNPS EPZ for the Planned and Uncontrolled Evacuations, Assuming Inclement Winter Weather
Table 7:
Evacr.ation Time Data for Determining the Imoacts of Uncontrolled Evacuation, Shadow Effect and Winter Inclement Weather Increases in Evacuation Times (Minutes) to Evacuate 50%
Ivacuate 90%
Evacuate the of the of the entire N
Comparison Poculation Population Population 1
P vs. P 20 60 65 O
S 2
U vs. UO S
S 3
U vs. P 10 5
115 4
U Y'*
05 65 50 O
Ul0***
15 5
0 z
Ul0 vs. U 110 150 6
2 O
s 2
U, vs. P, in 2u 310 4
e 22
The impact of the Shadow Effect for 50 percent voluntary evacuation during an Uncontrolled Evacuation has been discussed in Section 4.3 and shown as Comparison 4.
The impact of the combination of the effects of inclement vinter weather (vs. normal weather) and of the Shadow Effect (vs. no voluntary evacuation) is an increase of 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> and 35 minutes in evacuation time for the entire EPZ population, as shown by Comparison 5.
The impact of inclement weather alone, in the presence of the Shadow Effect, is to increase the evacuation time for the entire EPZ population by 2-1/2 hours, as shown by comparison 6.
Finally, Comparison 7 shous that the impact of all adverse
- conditions (winter inclement weather, Shadow Effect at 50 percent voluntary evacuation outside the EPZ and Uncontrolled Evacuation) acting concurrently, serves to increase the evacuation time for the entire EPZ population by 5 hours5.787037e-5 days <br />0.00139 hours <br />8.267196e-6 weeks <br />1.9025e-6 months <br /> and 10 minutes, relative to that for the Planned Evacuation in normal weather with'no Shadow Effect.
4.5 Summary A series of detailed analyses has been undertaken to provide realistic estimates of evacuation times for the popula-tion within the SNPS EPZ for a variety of stated conditions.
These conditions include:
e Uncontrolled Evacuation e
Shadow Effect e
Inclement Winter Weather.
Careful examination of the results obtained reveals that these estimates are consistent and satisfy intuitive reasoning.
That is,-the impact of each of the above conditions, singly and in combination, acts to increase the estimated values of evacuation time, relative to the base conditions.
All results are presented in tabular and graphical format to ease the task of analysis.
4.6 Conclusions The results obtained yield tho following conclusions:
1.
An Uncontrolled Evacuation of the EPZ, as defined, will increase the time to evacuate the entire population from the EPZ, relative to a Planned Evacuation, by up to 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes, under similar conditions of weather and voluntary evacuation.
23 l gWi l '
2.
The impact of Shadow Effect for'the Uncontrolled Evacuation will increase the time to evacuate the entire population from the EPZ, by one-half hour at the 25 percent level o'f voluntary evacuation, and by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 5 minutes at the 50 percent level, for normal weather conditions.
3.
The effect of inclement winter weather is to increase the evacuation time for the entire EPZ population during an Uncontrolled Evacuation, between 1-1/2 and 2-1/2 hours, depending on the percent of voluntarv evacuatica outside the EI4.
4.
The estimated time required to evacuate the entire population from the EPZ in an Uncontrolled Evacuation with a Shadow Effect reflecting 50 percent voluntary evacuation outside the EPZ, is 7 hours8.101852e-5 days <br />0.00194 hours <br />1.157407e-5 weeks <br />2.6635e-6 months <br /> and 15 minutes under normal weather conditions and 9 hours1.041667e-4 days <br />0.0025 hours <br />1.488095e-5 weeks <br />3.4245e-6 months <br />.and 45 minutes under inclement winter conditions.
5.
Impact of Accidents on Estimated Evacuation Times Since accidents
- are " rare events", an analysis of their impact on a specific event -- emergency evacuation -- is prone to subjective judgment. 'The domain of postulated events is unbounded; that is, one can a'lways postulate the occurrence of any combination and type of events with the argument that the postulate is "possible".
Even an analysis based on aggregate empirical statistics is subject to criticism on the basis that the process of evacu-ation during a radiological emergency is "different" than or-dinary traffic operations.
On one hand, it can be argued that the heightened state of motorist anxiety during evacuation could promote unsafe driving activities.
On the other hand,
-it could be argued that the low travel speeds characteristic of the expected congested conditions precludes the prospect of serious accidents and that a state of motorist anxiety translates into increased attentiveness.
While the available data does not support the thesis that traffic operations during an evacuation differs materially from that during normal congested conditions, it is not our intent to address these behavioral issues here.
Rather, we will apply a " reasonable" approach to estimating the number of acci-dents that could occur during an evacuation, and then utilize
- For this purpose, we extend the concept of " accident" to in-clude any event which can block, either completely or partially, a lane of traffic, for some interval of time.
24
the simulation' tool to calculate their impact on evacuation time.
Referencing the second edition of the Transcortation and
. Traffic Engineering Handbook, the following statistics are apolicable for the yer.1980:
Number of Vehicle-miles:
1.41 trillion Number of Accidents:
18.30 million Number of Fatalities:'
53.30 thousand.
These data provide the following rates:
One Accident per 77,000 vehicle-miles One Fatality per 26 million-vehicle-miles.
Evacuation of the entire population within the EPZ will pro-duce a total of 304,000 vehicle-miles.
By multiplying this figure by the above rates, we can estimate the expected number of accidents and. fatalities during evacuation:
Expected Number of Accidents:
3.95, say 4 Expected Number of Fatalities: 0.0117.
The procedure used'to deterbine the impact of four accidents was as follows:
1.
Randomly assign these accidents to different roadway sections on the evacuation network, subject to the condition that these roadway sections are heavily travelled.
2.
Then randomly assign durations of roadway blockage, subject to the assertion that blockage prevails for 15 minutes for two of the accidents and 30 minutes for the other two.
These assumptions assumed that the vehicle could be pushed out of the way eventually.
3.
If the roadway section~ consisted of one lane of travel, then capacity for that lane would be reduced by 50 per-cent, based on the premise that evacuating vehicles would bypass the blockage by travelling on the shoulder or encroaching into the opposing lane.
If the roadway section consisted of two or more lanes, then it was assumed that one lane was removed from service during the blockage period.
25
4.
Two simulation runs were executed with DYNEV, each with a different assignment of accidents (and blockage) to links of the network.
The results of these two cases indicated that *his deployment of accidents and consequent roadway blockage had no supreciable impact on overall evacuation times.
Careful examination of the computer output revealed that the
' roadway blockage did, in fact, impede traffic.
These impedancies, however, were less than the impedances produced downstream of the accidents, by the heavy congestion (i.e., excess of demand rela-tive to available capacity).
Consequently, while the presence of road blockage affected the spatial location of delay within the evacuation network, as well as the details of the temporal distri-bution of delay at those locations influenced by these transient accidents, the overall effect, relative to the base conditions
- of no accidents, was nil.
As discussed at the beginning of this section, it is always possible to postulate roadway blockages " strategically" so as to guarantee an impact on evacuation travel.
Such an approach might be useful, in our view, as part of an evacuation exercise, to test the response of personnel to such an unscheduled event.
Our study, however, had the objective of assessing expected events and their impact; such an objective mandates the application of random events, as described above.
On the basis of this study, it can be concluded that a limited number of transient blockages, randomly dispersed in time and space, will probably have little, if any, impact on evacuation '
travel time.
- The base conditons were:
Planned Evacuation, no Shadow Effect and normal weather.
26
KLD TM-140 Determination of Varying Route Compliance Levels and of a
. Proposed New Roadway on Evacuation Travel Times within the Shoreham EPZ Submitted to 2
Long Island Lighting Company 175 Old Country Road Hicksville, NY 11801 by KLD Associates, Inc.
300 Broadway Huntington Station, NY 11746 November 16, 1983 by
[If, _. f M,-o.
Edward Lieberman, P.E.
Vice President
KLD TM-140 Determination of Varying Route Compliance Levels and of a Proposed New Roadway on Evacuation Travel Times within the Shoreham EPZ
' Submitted to Long Island Lighting Company 175 Old Country Road Hicksville, NY 11801 by KLD Associates, Inc.
300 Broadway Huntington Station, NY 11746 November 16, 1983 by
[d%ff MIodm.
Edward Lieberman, P.E.
Vice President
TABLE OF CONTENTS
_ Section~
Title Page 1
. Introduction 1
2 Technical'Discusstion 1
3.
Results of Case Studies 4
3.1 Effects of Varying Route Compliance Level' 4
3.2 Effects of Constructing Access Road on LILCO Right-of-Way 4
3.3 General Observations 7
LIST OF TABLES Number Title Page 1
Sensitivity.of Evacuation Time Estimates to Motorist Route Compliance and to Construction of LILCO Access Road 5
2 Evacuation Trip Statistics 6
0 i
4 1
' Introduction
.This report documents.the results of case studies which
- were designed to quantify the effects,on evacuation travel time, i
of two factors:
e' Motorist "non-compliance" to the recommended evacuation routes.
The use of a-new access road constructed along an o
existing LILCO right-of-way, currently used for an electric power transmission line.
Specifically, we are interested in the extent to which these results depart from those documented in Appendix A of'the LILCO Transition Plan' (l_) and in KLD Technical' Memorandum (TM-77 (2_)).
]
2 Technical Discussion 4
.Throughout all studies conducted to date, the procedure in-volves two sequential steps which are repeated in an iterative manner (see Appendix D of _Ref. :(1)) :
e Traffic Assignment, e
Traffic Simulation ~
The traffic' assignment process' produces estimates of traffic volume on.all " links" (i.e. roadway sections) of the evacuation network.. This information enables the analyst to identify paths
- of travel (i.e ~ routes) from every origin ~ point (where. vehicles l
enter the evacuation network) to each respective destination oh
~
the periphery of the EPZ.
The traffic simulation model' described the operating per-
~
formance of traffic moving along these routes to produce statistics
' which provide detailed estimates of travel time.
Implicit with-Lin these studies'is the assumption that vehicles (i.e. motorists)
-comply with these recommended routes.
To increase.the extent of such route compliance, the plan calls for~ route-delineation and route-guidance signs to be de-
- ployed at a high density along all roads comprising the evacu-ation network:' almost 1000 sign locations have been identified.
In addition public information brochures, route-delineation e
_ stickers and other forms which identify the recommended routes, are planned.
.These will be designed to:
i 1
.---:-.-.-.--- -. ~ - - - - - - - - - - - - - - - -
e-Inform the public as to the location of these routes.
e Identify those routes which are recommended for each
- Zone, o
Explain the rationale for the selection of these routes:
.~'_
They will provide the most rapid means of egress from the area-They will move people away from the source of the radioactivity They serve to disperse the traffic demand so as to limit the extent of congestion Subject to the above objectives, they represent either the shortest path out of the network or paths that are only marginally longer but considerably faster than the shortest path e
The permanent installation of these signs will play a role in forming the perceptions of the'public, over time, as they travel through the area.
It is recognized that, to some extent, not all motorists f
will comply with these recommended routes, in the event of an accident.
Consequently, it is of value to examine the impact on: estimated travel time of varying levels of compliance.
Specifically, three levels of compliance were postulated for study.
e 100 percent compliance (base case) e
-75 percent compliance e
50 percent compliance For the two latter cases, it was necessary to develop trip tables which reflected the origin-destination patterns of non-
~
compliant vehicles.
To accomplish this task, it was necessary
.to identify, for each origin node, one or two alternative desti-nations which were viable and attractive (in'the sense o~f near-proximity and minimum circuity of the associated paths of travel).
- The procedure of traffic assignment followed by traffic simulation was again exercised.
Here, however, one additional change.was implemented.
Since traffic was "non-compliant" to an 2
I extent, it followed that motorists would adjust their routes in accord with perceived conditions, as they travelled.
That is, if a particular direction was jammed with long queues, vehicles would divert to an alternative receiving link which was in the general direction (i.e. the south or west) from the plant.
This change to the model is called " queue adjustment."
The LILCO access road considered in this study is located just north of Route 25A and is oriented in the east-west direc-tions.
Two lanes of service is envisioned for the major portion of this route.
The introduction of the LILCO access road to the evacuation network likewise entails modifications to the base trip table.
Again the same general procedure was applied.
For these studies, 100 percent route compliance was assumed.
This option was investigated because this LILCO access road would service the most densely populated area within the EPZ.
Also, traffic along this road would feed into Nesconset Highway (Route 347) which is a major arterial providing two lanes of service in 'te westbound direction.
It therefore seemed reasonable to expect that providing an additional, near-by, direct road facility for the most densely populated area within the EPZ might expedite the movement of the people and relieve congestion elsewhere, as well.
Two studies were conducted:
Under the assumption of the planned evacuation, as e
described in Appendix A (1),
Under the assumption of an " uncontrolled" evacuation e
as described in TM-77 (2).
All studies for both route non-compliance and for the LILCO access road were based on:
e Normal weather e
No shadow effect e
Evacuation of the entire EPZ (Base Case No. 12) 3 l
l
3.
Results of Case Studies The results of these studies are presented in tabular format and'are discussed in this section.
3.1 Effects of Varying Route Compliance Level Table 1 presents a tabulation of estimated evacuation travel times for the following conditions:
Motorist Compliance with Recommended Routes Evacuation Scenario (Case)
(Percent)
Planned Uncontrolled 100 12 S.5 75 33B 32B 50 33A 32A-Table 2 presents statistics which provide further insight into the effects of route compliance.
As is indicated, the rec-ommended routes produce' average trip lengths that are slightly
. longer than those for the cases where there is partial compliance (2.6% for the Planned evacuation, 7.0% for Uncontrolled).
The conclusions that can be drawn from these results are:
1.
For the " Uncontrolled" evacuation scenarios, evacuation travel times are insensitive to motorist compliance with the recommended routes.
2
.For'the Planned evacuation scenario, evacuation travel time is not sensitive to motorist compliance above the 75 percent level..At the 50 percent level, evacuation time increases by about 35 minutes.
3.
The results seem to indicate that while departures from the recommended routes do slightly reduce travel distance, such departures do not reduce travel time.
- 3. 2 : Effects of Constructing Access Road on LILCO Right-of-Way Table 1 presents a tabulation of estimated evacuation travel 1 times for the following conditions.
e*
4
m.
I Table 1: ' Sensitivity of Evacuation Time Estimates to Motorist Route Compliance and to Construction of LILCO Access Road
~
Time-After Beginning'of Run Description Evacuation (Hours - Min.)
Percent
-Evacuated:
50%
90%
100%
Case 12 EPZ (100% Compliance - Planned) 1-40 3-20 4-35 Case 33B EPZ ( 75% Compliance - Planned) 1-40 3-25 4-35 Case 33A EPZ ( 50% Compliance - Planned) 1-40 3-30 5-10 ui Case S.5 EPZ (100% Compliance - Uncontiolled) 1-55 3-50 6-10 Case 32B EPZ ( 75% Compliance - Uncontrolled) 1-55 3-35 6-10 Case 32A EPZ ( 50% Compliance - Uncontrolled) 1-55 3-40 6-10 Case 12B EPZ (LILCO Access Road - Planned) 1-40 3-10 4-10
-Case 30 EPZ (LILCO Access Road - Uncontrolled) 1-40 3-10 4-10
Table 2:
Evacuation Trip Statistics Mean Trip Run Veh. Miles Total Trips Length (miles)
Case 12 303,928 52,547-5.78 Case 33B 296,715 52,641 5.64 Case 33A 295,652 52,593 5.62 Case S.5 312,250 52,464 5.95 Case 32B 296,235 53,272 5.56 Case 32A 298,476 53,648 5.56 Case 12B 263,993 52,034
.5 07 m
Case 30 264,893 52,124 5.08.
Evacuation Scenario (Case)
LILCO-Access Road Planned Uncontrolled Not Available 12 S.5 Available 12B 30 Table 2 presents results which indicate a reduction of approximately 13 percent in mean trip length with the Access Road available.
The conclusions that can be drawn from these results are:
1.
For both evacuation' scenarios, construction of the access road significantly reduces evacuation travel distance (12%
for the planned evacuation; 15% for the uncontrolled).
2 A reduction of 25 minutes in evacuation travel time can be-realized with the access road in place, for the planned evacuation scenario.
3 A reduction of 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> in evacuation travel time can be re-alized with the access road in place, for the uncontrolled evacuation scenario.
3.3 General-Observations
'l.
Route compliance is somewhat more important for the planned evacuation scenario than for the uncontrolled scenario since the planned control tactics are specifically designed to Jservice the associated travel patterns.
There is no symbiotic relationship between control and routing for-the " uncontrolled" scenario.
Consequently, it is not
~
-unexpected that a significant departure from full rout' e
compliance (i.e. 50%' level) should result in some degrada-tion of performance (i.e. longer travel times) for the planned evacuation scenario while the travel times for the uncontrolled scenar.io are not affected.
2 Construction of the LILCO access road would provide a significant improvement in evacuation travel time, parti-cularly for the uncontrolled evacuation scenario.
These results demonstrate that the evacuation travel times for the population within. the area. that is within the EPZ, west of.the SNPS and north of Route 25A, is the " critical path" of the' evacuation process.
Since the location of this access road services this area, it follows that the addi-tional capacity should--as it, in fact, does--reduce the evacuation travel time for that area.
7
3.
Interestingly, construction of the Access Road will provide evacuation travel times which are equal for both the planned and uncontrolled evacuation scenarios, The basis for this result is.
The cited area north of Route 2'!A still remains the e
" critical path" area of the EPZ even with the road in place.
That is, the evacuation travel time for this area exceeds that for any other evacuation path.
Consequently, any reduction in travel time for this area translates into a commensurate reduction for the entire EPZ.
The new road is the major evacuation route for this e
population within the cited area.
Thus, even in an uncontrolled environment, the traffic in that area will use the new route.
Some of the traffic originating in the cited area, was e
previously directed southward.
With this road in place this traffic will be diverted along this new road, thus reducing traffic demand on the Long Island Ex-pressway and on Route.25 8
_--------------.a-------------------
Il!I I==
smoureum asusure AAA A444 stu moumma nourzamw wms usurn mao uzemo ssuzaar
.I!!!
fj((
jj))
aru mou w m s
_---- -----.u..r. zzm m. mas I
= "I 4 4
=
amoureum numan IIII II A A-A aus monems ur::= wrsses 33
- .3 gj j Ig4
..{.
423}
smozaze ms asumaar 4
mas monema manytnaos numan
--.88 amza
. 38
- 7 *A IIAA I44 moo nzeum sausaar AA*
mas monam somos w
.a..n.ou.r. --- ummo
- =$2 smourmos wieson
==
2332 I4,4 IAAA AA44 aru moumma moursnaos wummo um. ens g
.g.g
.3 a
a a smouzeum ssusaav
.AAAA 4 4 4444 asikwssu = u rzneo
_ s mszaivus smoureum wusou a===
,=32 2$.=4
],
- ==== mourzame mazarvus AAAA-AAA4 A4 3
o:
8.3 33.
88 AAA A4AI AAA a
I suorumso asusaav 3
asmoessu monytnaos samamu e
unmIn
.g..
3. g 3, g
..gg A*4*
AA;*A IIAA smozuman asumaav 4
I
' l
-- asmoessu mourznaos ansviessa "IAAA l l
==3:
333 smo uzaco z asom A4A4 AAAA
=
as-essa mourznaos amas.assa i
I - :::-
E I -::: -
I 3
I
- E
=as =u-v-g l
E, E. -====-
=
==
i
==s moueurma e-I
- c..1*.
--g3a g..
- =
srzszum mourzneos marsuvus 3
i awo u=.um gagg
- 32
= =.
- =32 moursnaos ms:suvus
,R.,
iE*3 il*mi I251 I
sr uz no u rzoso, m m.
. _= -
_,_y_g_
=.
.g za
__E_._
- sy g.gg a
=_ =_
urzneo.m
m=
..d se =
ddd dii a =.
d.i.a a.a saa
=,d,d susuf dd a
sudd IGG ddd u..'
u
.n idd.
- ggg, 2444 J d d.s 444.
ee e 9 eS S S S 388 388g 888g yyy y y y.3 avsous yy.
5s5$
sick 555$
REV. 1
E E Y E
R LR R
BA S
U E
AD N
E SD E
T O
R O LE P N
R I
N s
P U
PEU EE UMAE FYE A
X S HS SH OAH B ORC V O E TO NT E WSSD TAI G B
R P
O R N EEL.
PO T
S O Y R D N R
E E
XY P
R I
E O EA SOI A HVU O
S S
L N
N P F TI O S
EW EFT A
W T
E ST E O
LI P
C XR LA HR N A AEUA RI R
, DS EE E
MV U A EAPP TAI PHRBL TMP N
E R
I R
LRI PTD P
1-t n
e l
\\
\\
I
\\ ?
k san o
Z gn inn N
la P
yc n
eg re m
\\
l
\\
E N
\\
I f
f o
r A
/
tp gjj 1d g aI e
4 c
m 7
n
~
N -
/
o
\\
C A
1 B
R y e
Ud g
ru g
i F
sIk g
N
/
~
E N
O Z
)
G N
N O
I I
$*~)E N
T
)
J M
M S
)
L G
g yl g A
E P
g A
gMg a
L 0g y
g P
1g
/
I E
T S
//
R O
TC A
E R
~
[
li
- I
)lllf'
,l ll
4
{
j EVACUATION TIME ESTlHATES ASSUMINC VOL'fMTARY EVACUATION EVACUATION TIME 10-20 OTHER (Hours-Minutes)
ZONES CONTROLLED /
COMPLIANCE /
MILE FACTORS
,P_ER9ENT OF POPULATION EVACUATED
(
CASC EVACUATED JLASON WEATHER UNCONTROLLED NON-COMPLIANCE SHADOW CONSIDERED 501 901 1001 12 All Zones summer normal controlled compliance 0%
2-00 3-40 4-55 22 All Zones summer no rma l controlled compliance 25%
2-15 4-00 5-15 23 All Zones summer normal controlled compliance 50%
2-20 4-55 6-35 a
24 All Zones summer norma l uncontrolled compliance 0%
2-15 4-10 6-30 26 All Zones summer normal uncontrolled compliance 25%
2-45 5-10 7-00 h
27 All Zones summer normal uncontrolled compliance 50%
3-10 5-55 7-35 i
1 25 All Zones winter inclement uncontrolled compilance 0%
2-30 4-45 7-55 28 All Zones winter inclement uncontrolled compliance 50%
4-55 7-45 10-05 i
4
j'...,:,,.-.
"e o
9 L0 f.h r %,.g w w,
.p%. q&{
l/hhl O
'f s.'
s' =, ',,,,']'-',*
+
e e.p.m.-
.s
, 'Ws s g ray }g,5 v
Q, 'l b g j
f*
a
._..,.,,.n,]V z "' i J(p y i'l p
-, M-~- "
J,.
g
==
i
{,,.y.r n j\\ o,'
4.A e
e ') / //
i I i, E9 14
' T
/
-( $
$i 4
f.
/'@
^ N 'YI
~\\
l
.,n
,=)
i ig!I
[
i
/
"r \\ kl Nhn$4(fd g{$$;
.,%<- h '$,,g h l
\\
S
/
y/
n i w
'.,.,',. ny, A'L/,7eg ngl,,
n n
w:;
\\
y
[*'
\\\\' c 1
5-v.s
- g. '!W"
- t%
=
(
- dij 5%
- '.7
's
'\\
\\
(<*
k k, Avg N
r o
. _j.. s1".-s ev, e. n+p o
y w
s c.c e
t W --
t
... d.:1
~
\\
'r
~~
'- )
Q-f
,, Af
.,[jf t
4It '... d',d t
o M52.?;,"51);
'l " l
\\
A
\\@gn q-4.k
\\
W
~
"a rma.My.ov.mk tr s'.y%
g g,.%
'1 ?
_T,,
f
-,m.
t_.Q?
T
\\,
e+
- n g
a i
L.,
,/
i ii 1i1 b
- % \\- h
""j/ {4 i
t ii
,j
. ~.-c p
~~
I
.......,,c.-
SHOREHAW NUCI EAR POWER STATION
.=
EMERGENCY PLANNING ZONE
]
1 T I
O rw nc coan a coint
=h
@ PRIVAit PROFERTY h
--- tutastucy atsponsc rtAmmine Ans,43,
. viet SCALL IN MtLES 9
f e
l
}
NO ISLAND S0UND
-e n h
- "'"{
~
G#'
sesen,a N
N
@iT4%,%.f
\\
O
\\
{L.,,
I.b ' ' '
\\
... ~. -
N e
b f
s R E > H E k N
\\
6,.
/ VlN
, f,
/
g(,c,; 'M'p z,z.,h, ;f
"/
(
r~ '
,' Y' n w, tyg.qy*
//%sS.P* E h*
f
/
m y
~
r?,
h,4 i
L Also Available On
,pgh...e
~"' '
g
[ //
Aperture Card
\\
.v.
s!f l#'#.
1' i
N I
TRAFFIC CONTROL PolNT e 21 ri Y
.y j
J k lN. W$'"
\\
T-E p
\\ {o en t
j i
l 1
2 y
.gf{ etM.m,as man. case
,n a
i j
k ei. rs l
t a
GAP
~ ( B
- y,,,...
.i 4 7 se EVACUATION MOVEMENT MOVE **ENTS TO NON-EvaruATICN r TO BE FACILITATED BE DISCCURAGiD MOVEMENTS TO I / BE ACCONCDATED il FRan TO FRCM TO FROM TO l{ m [i ui, W S ALL W S E y! $ ~ E -3 y u. .e= y-a e NOTES: g g PLACE CONES TO ALLOW SUFFICIENT GAP e rw n. FOR VEHICLES TO PASS THROUGH. y,,,, _\\ l l 3 i I 831122014 6 --O f
LILCO, Novembar 18, 1983 00CMETED USHRC CERTIFICATE OF SERVICE j gg In the Matter of 0FFICE OF SECPETMA LONG ISLAND LIGHTING COMPANY DCCKEIttiu & SERVO. (Shoreham Nuclear Power Station, Unit 1) BRANCH Docket No. 50-322-OL-3 I hereby certify that copies of LILCO's (1) Testimony on Phase II Emergency Planning Contentions 23.C., D. and H., (2) Testimony on Phase II Emergency Planning Contention 65, and (3) Joint Attachments for Contentions 65 and 23.C., D. and H. were served on November 17, 1983 upon the following by first-class mail, postage prepaid, or (as indicated by one asterisk) on November 18, 1983 by hand, or (as indicated by two asterisks) on November 17, 1983 by Federal Express. James A. Laurenson.** Secretary of the Commission Chairman U.S. Nuclear Regulatory, Atomic Safety and Licensing Commission Board Washington, D.C. 20555 U.S. Nuclear Regulatory Commission Atomic Safety and Licensing East-West Tower, Rm. 402A Appeal Board Panel 4350 East-West Hwy. U.S. Nuclear Regulatory Bethesda, MD 20814 Commission Washington, D.C. 20555 l Dr. Jerry R. Kline** Atomic Safety and Licensing Atomic Safety and Licensing Board Board Panel l U.S. Nuclear Regulatory U.S. Nuclear Regulatory i Commission Commission l East-West Tower, Rm. 427 Washington, D.C. 20555 4350 East-West Hwy. Bethesda, MD 20814 Bernard M. Bordenick, Esq.** David A. Repka, Esq. l Mr. Frederick J. Shon** Edwin J. Reis, Esq. Atomic Safety and Licensing U. S. Nuclear Regulatory Board Commission U.S. Nuclear Regulatory 7735 Old Georgetown Road Commission (to mailroom) East-West Tower, Rm. 430 Bethesda, MD 20814 4350 East-West Hwy. Bethesda, MD 20814 4 I L L-
8 Eleanor L. Frucci, Esq.** Stewart M. Glass, Esq.** 's. Attorney-Regional Counsel Atomic Safety and Licensing Federal Emergency Management i Board Panel. Agency U. S. Nuclear Regulatory 26 Federal Plaza, Room 1349 Commission New York, New York 10278 East-West Tower, North Tower '4350 East-West ~ Highway Stephen B. Latham, Esq.** Bethesda, MD 20814 Twomey, Latham & Shea 33 West Second Street David J. Gilmartin, Esq. P.O. Box 398 Attn: Patricia A. Dempsey, Esq. Riverhead, New York 11901 County Attorney } .Suffolk County Department Ralph Shapiro, Esq.** of Law Cammer & Shapiro, P.C. Veterans Memorial Highway 9 East 40th Street Hauppauge, New York 11787 New York, New York 10016 Herbert H. Brown, Esq.* James Dougherty, Esq.* Lawrence Coe Lanpher, Esq. 3045 Porter Street Christopher McMurray, Esq. Washington, D.C. 20008 Kirkpatrick, Lockhart, Hill inristopher & Phillips Howard L. Blau 4. 8th Floor 217 Newbridge Road ~1900 M Street, N.W. Hicksville, New York 11801 Washington, D.C. 20036 Jonathan D. Feinberg, Esq. Mr. Marc W. Goldsmith New York State Energy Research Group Department of Public Service 4001 Totten Pond Road Three Empire State Plaza Waltham, Massachusetts 02154 Albany, New York 12223 MHB Technical Associates Spence W. Perry, Esq.** 1723 Hamilton Avenue Associate General Counsel Suite K Federal Emergency Management San Jose, California 95125 Agency 500 C Street, S.W. Mr. Jay Dunkleberger Room 840 New York State Energy Office Washington, D.C. 20472 i Agency Building 2-i ' Empire State Plaza Ms. Nora Bredes Albany, New York 12223 Executive Coordinator Shoreham opponents' Coalition 195 East Main Strytt Smi town, N Yo t 11787 1 l 'cv Hunton & Williams 707 East Main Street P.O. Box 1535 i Richmond, Virginia 23212 !~ DATED: November 18, 1983 ..n..- 7 .,,y-. ,-._.w. -w..,ew-- - - - -, - - - - - - - -, - - -, - - - - -. - - - -}}