ML20205P553
| ML20205P553 | |
| Person / Time | |
|---|---|
| Site: | Seabrook  |
| Issue date: | 03/25/1987 |
| From: | Lieberman E KLD ASSOCIATES, INC., PUBLIC SERVICE CO. OF NEW HAMPSHIRE |
| To: | |
| Shared Package | |
| ML20205L804 | List:
|
| References | |
| OL, NUDOCS 8704030311 | |
| Download: ML20205P553 (41) | |
Text
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I h-Dated:
March 25, 1987 UNITED STATES OF AMERICA NUCLEAR REGULATORY COMMISSION before the ATOMIC SAFETY AND LICENSING BOARD
)
In the Matter of
)
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PUBLIC SERVICE COMPANY OF
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Docket Nos. 50-443-OL NEW HAMPSHIRE, et al.
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50-444-OL
~,
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Off-site Emergency (Seabrook Station, Units 1 and 2) )
Planning Issues
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AFFIDAVIT OF EDWARD B.
LIEBERMAN (SAPL 31) 1 I, Edward B.
Lieberman, being on oath, depose and say as follows:
1.
I am Vice President of KLD Associates, Inc. and am responsible for the development of the Seabrook Station Evacuation Time Study, Volume 6 of the NHRERP.
a In response to SAPL Revised Contention 31, I submit the following response and comment:
2.
Item 1.
The SAPL contention number 31 extracts the j
number 3000 from the Volume 6 text out of the context for which this estimate is given.
On page 2-27 it is clearly stated that these are external-external trips which are already on the highways at the time of the accident.
On 4
page 10-3 it is noted that these " additional 3000 'through' 8704030311 B70325 gDR ADOCK 05000443 PDR
e o
i vehicles not otherwise counted, are on the highway when the alert is sounded".
[ emphasis added].
These external-external trips that are on the highway at a given point in time should not be confused with the total volume on I-95 over a 24-hour period.
By way of detailed response to this basis, the primary routes servicing external-external trips through the Seabrook Station EPZ are the Interstate Routes 95 and 495.
All other routes within the EPZ, which could be interpreted as through routes (e.g., Routes 1, 107, 108), are two-lane roads which are not relatively attractive to through travelers.
About 230 lane-miles are provided by these express routes:
I-495:
2 miles @ 4 lanes; 5 miles @ 6 lanes I-95:
21 miles @ 8 lanes; 4 miles @ 6 lanes The calculations of ETE for the summer scenarios assume that the accident takes place when the beaches are at maximum usage, roughly at 2:00 PM.
When developing the inputs to the IDYNEV model, it was estimated that 3000 through vehicles, not otherwise counted, would be on the network at this time.
This estimate was based on observations made while traveling the network.
Specifically, it appeared that volumes on I-95 and on I-495 were traveling at Levels of Service (LOS) that did not exceed LOS B or C.
The associated range of density is 13-30 - -
r o
passenger cars-per mile per lane.
Thus, the total number of vehicles on these highways is between 2990 and 6900, many of which are not through vehicles.
Of course, this estimate of 3000 through vehicles represents'those who entered the EPZ prior to the implementation of access control and have not as yet completed their travel through the EPZ by the time the Order To Evacuate (OTE) is given.
At that-time, the number of through vehicles within the network could be substantially less than the number which occupied the network at the time the access controls are applied.
Thus, it is seen that the.
number of external-external vehicles on the EPZ network at the OTE should not exceed the 3000 estimate, and may be substantially less.
Direct observations of traffic flow on these major routes supported by aerial films taken on July 4 and 5, 1986 at approximately 2:00 P.M. (after the ETE calculations were undertaken) indicate that traffic volume is very low - LOS A and B.
The associated range of traffic density is less than 20 passenger cars per mile in each lane.
Thus, based on these later observations, the total number of vehicles on these highways at this time is less than or equal to approximately 4600 passenger cars (20 x 230).
Many of these cars, of course, belon'g to EPZ residents, tourists and employees who have already been -
counted.
It is seen, therefore, that the estimate of 3,000 through vehicles -- not already counted -- is realistic.
Traffic on these highways during the off-season generally does not exceed the volume associated with LOS C, regardless of time of day.
Thus, the estimate of 3000 through vehicles is applicable throughout the year.
The NHEERP calls for access control points to be established at the periphery of the EPZ which will divert traffic from entering the EPZ from points outside except, of course, those vehicles which will participate in the evacuation (Vol.
1, 2.6-16).
The 3000 vehicles estimate as through travelers are included in the ETE calculation.
For example, the computer analysis for Region 1, Scenario 1 indicated a total of 99,398 trips.
This figure compares with the total number of 96,524 shown in Figure 10-11c.
It is also noted that the cited figure of 99,000 vehicles over one day (i.e.,
24 hours2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br />) and pertaining to normal peak conditions is essentially irrelevant to the issue of the 3000 through vehicles estimated at a point in time.
The statistics are therefore not directly comparable.
The contention states that the estimate of 300 cars on the highway in Hampton Beach is not identified as to time of day.
This is not true.
Volume 6, Page 10-15 references Appendix E, Item 7 which indicates that aerial photos uued to determine estimates of parking capacity and vehicle --
a 6
counts were taken on Sunday, August 11, 1985.
Page 10-16 (which in fact is referenced in the contention), states the following:
"at the time of maximum parking occupancy (about 2 p.m. ), however, moving vehicles are few in number relative to those parked.
For example:
a total of about 300 moving cars was counted in Hampton Beach from the aerial films..."
It must be emphasized that few, if any, of these 300 cars are "through" vehicles.
It is highly unlikely that any vehicles moving through the area would leave an Interstate Highway such as I-95 to travel along the coastal roads which would significantly increase their travel time.
Thus, these 300 vehicles are most likely in the process of either leaving or are destined for parking locations along the coast.
Since our estimate of vehicle population along the coast is based on parking capacity, these vehicles have already been included in that count.
This approach is in consonance with NUREG-0654, page 4-2 which cautions that
" Care should be taken to avoid double counting."
3.
Item 2.
The contention that there has been "significant growth" (in seasonal accommodations) in the EPZ area over the past 5 years is unsupported'1n any way, and presents a presumption on the part of the intervenor only.
The KLD report does not depend on the report by Kaltman for an estimate of vehicles per dwelling at seasonal housing units.
On page E-lO it is stated:
"KLD's on-foot survey recorded an average value of 2.6 vehicles per dwelling." -
r 4.
Item 3.
There is no current regulatory requirement to project into the future when establishing ETE.
The planning process is a continuing one in which all elements of the plan, including the ETE, must be kept current.
(NUREG-0654, Appendix 4, states that "the evacuation time estimates should be updated as local conditions change".)
5.
Item 4.
This basis complains that the ETE assumes that traffic control measures will be in effect at the time the evacuation is ordered.
This statement is based on the high probability that there will be sufficient time between official notification to man TCPs and the public Order to Evacuate, allowing the traffic control personnel to be mobilized and positioned.
In addition, each traffic control point (TCP) has been assigned a priority which indicates the sequence in which these TCPs are to be manned.
The TCPs given a priority of 1 (highest priority) are considered to be those which have the most potential for expediting the movement of traffic.
Those TCPs which are assigned lower priority are considered less important, although they are helpful in expediting traffic movements and in reassuring the public that the evacuation is under control.
Sensitivity runs have been performed to quantify the effects of non-compliance with traffic control measures.
These tests indicate a reduction of about one hour in ETE within 2 miles of the station, a smaller reduction in ETE I )
a a
for those within 5 miles of the station and.no change in ETE for the EPZ as a whole during the summer.
Those reductions in ETE. reflect the fact that some evacuees from the beaches to the south of the station will use Route 1, southbound; under the controlled evacuation, these evacuees are restricted to use I-95.
This. restriction, in turn, is responsive to requests made by police chiefs in Newburyport and Newbury, to limit the amount of southbound traffic on Route 1, from the north of these communities.
As noted in Item 8, computed analysis of non-compliance cases reveal that the ETEs are not adversely impacted by non-compliance with traffic control measures.
The argument presented that an immediate general emergency would extend the ETE by more than 20 or 30 minutes is not supported, and is non-persuasive.
For example, a reduction in the elapsed time of 25 minutes between the Alert stage and the Order to Evacuate, which is assumed under the scenario of an immediate general emergency, can increase the ETE by only that amount, and no more.
In this scenario, the Order to Evacuate, which is the starting point which defines the ETE, is advanced by 25 minutes.
Since the i
highway system in the beach areas and their service roads l
l are operating at the capacity very quickly after the Alert stage due to precautionary beach closings (for the summer scenarios), it therefore follows that the total elapsed time to clear the area from the start of the alert is insensitive -
O to the extent of the elapsed time to the Order to Evacuate.
Thus, the ETE would increase by the amount of time that the starting (i.e.,
the Order to Evacuate) point is moved forward (namely 1.e.,
by 25 minutes).
See Volume 6, pages 10-16 and 10-17 for a detailed discussion of the results.of sensitivity tests for an "immediate" General Emergency compared to the results of the Planning Basis.
6.
Item 5.
The arguments presented here are speculative and unsupported.
It is hardly likely that the residents will leave their homes to evacuate just because they see traffic moving from the beach area.
During the summer, there is always traffic moving from the beach area.
There is no regulatory requirement that evacuation outside of the plume EPZ should be taken into account in calculating the ETE.
7.
Item 6.
The sample of 1300 responses is extremely robust for this survey size.
For example, a somewhat similar survey was conducted throughout New York State in 1983.
This random sample telephone survey interviewed 1503 State residents out of a total population of approximately 17.8 million, compared with our 1300 responses for a resident population of under 150,000.
(Reft
- Byunso, J.
and
- Hartgen, D., "An Update on Household-Reported Trip-Generation Rates" in Transportation Research Record 987, 1984). -
o
-i The 1382 calls that led to completed interviews represents a 63 percent completion rate.
This rate is typical of telephone surveys, according to the market research firm of First Market Research of Boston.
See Item 17 on page E-13 of Volume 6.
There is no merit to the contention that there exists "a large non-response bias" in the data sample.
8.
Item 7.
This contention argues that the travel time home reflects travel during " normal circumstances", while during an evacuation, commuters would be returning home against the direction'of evacuating traffic in part.
It must be pointed out that " normal circumstances" represent peak hour conditions when other commuters are occupying the roadways over the same time frame as those who are returning to their homes within the EPZ..
If an order to evacuate occurs prior to the normal peak period then those returning home to the EPZ will be occupying the roadways while workers wh:2 live elsewhere remain on their jobs.
Consequently, under those circumstances, the trip home should take somewhat less time than during the " normal" peak traffic period.
Furthermore, it is highly unlikely that other travelers, who might be going to or through the EPZ, would actually make their trips under emergency conditions.
This reduction in other trip-making also tends to shorten work-to-home travel time. -
Travel against the direction of evacuating traffic will not have an effect on major highways such as I-95 and I-495 since the two directions of traffic are physically separated and traffic in one direction has no impact on the other.
On surface roads there could be some frictional effects but these would be counter-balanced by the factors discussed in the preceding paragraph.
Again, it must be emphasized that the cones do not block desired turning movements in any direction.
As noted on page 7-1:
"There are always legitimate reasons for a driver to prefer a direction other than that indicated.
For example:
He/she may be traveling home from work or from another location, to join other family members preliminary to evacuating."
Later, the plan states, "The implementation of a plan must provide room for the application of sound judgment.
The traffic cones and barriers are deployed as indicated in the sketches of Appendix I, so that there remains room for vehicles to maneuver through these guides.
That is, cones and barriers will not physically obstruct passage."
It is thus seen that the plan is designed to accommodate commuters who will be returning home and that they will not encounter any blockage which will obstruct their movements to their home from work.
The contention argues that 95% of the commuting traffic will attempt to return home within 30 minutes of each other leading to a " massive rush home".
There is a reference to I
i i I
page 4-9 which has a table which clearly states that the indicated distribution is the amount of timo needed to prepare to leave work -- that is not the distribution of work-to-home trip generation.
The distribution of primary relevance is shown as Figure 11-1 on page 11-17 which indicates that some 70-75% of commuters would arrive home within 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> of the Order to Evacuate, under normal rush-hour conditions.
The argument that the travel time distributions from work to home are unrealistic is completely unsupported.
The very existence of a peak in the late afternoon reflects the l
l fact that the majority of workers leave their places of business within a narrow time frame and enter the highway system over that same time frame.
The data that we have obtained reflects the travel times under those very circumstances.
9.
Item 8.
The ETE is not responsible for identifying the source of personnel staffing; that is instead a function of the NHCDA in conjunction with the appropriate State response organization.
The issue therefore regarding the availability of manpower is not an appropriate concern of j
l f
the ETE.
Again, the computed analysis of non-compliance cases reveal that the ETEs are not adversely impacted by any absences of guides at TCPs.
The lone exceptions to this l
l l
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i rule are TCP F-EX-04 and D-HA-02, which are assigned the highest priority.
10.
Item 9.
One argument that is presented under Basis 9 asserts that cars could break down on bridges and "other choke points" within the EPZ which could lead to one vehicle totally obstructing the road.
No plan, however, is designed to take into account the worst possible conditions.
Dr.
Urbanik, who is one of the lead writers of Appendix 4 of NUREG-0654, has testified it is not the intent of the FEMA guidelines to require that the plan be responsive to the worst case conditions, since the domain of possible calamities that could occur during an emergency is virtually unbounded.
Instead, the planning basis of any emergency plan must be based on what can reasonably be expected to occur.
In specific response to this contention, however, it is noted that all bridges of significant length are designed so that there is some shoulder space available to store i
disabled vehicles.
Narrow, short bridges do exist on some two-lane roads.
If a car should stall on such a bridge (which is a low probability event), it can be pushed off the bridge onto the shoulder immediately downstream.
Furthermore, even if a vehicle is stored at a point on a highway where there is little or no shoulder room, there is still sufficient room for the traffic to move around the disabled vehicle even if it means encroaching, somewhat, t
into the incoming lane of travel on a two-lane road.
In
~
j situations like this, the dominant flow of evacuating traffic which would be in the outbound direction would effectively "take over" that "chokepoint" and traffic would move past the obstruction.
The " minor" traffic flow in the inbound direction would take advantage of any gaps in the evacuation traffic.
This contention's claim that the Highway Capacity Manual (HCM) estimates that capacity is reduced by 1/3 "because the roadway's perceived width is reduced" is simply l
incorrect.
The referenced passage page 6-10 in the HCM cites one study (by Goolsby, M.)
which describes an
" incident removed to the shoulders" which reduced capacity I
by one-third, on a three-lane (in one direction) freeway.
The Goolsby paper specifies that this incident was actually
)
an accident and that capacity reduction was caused by the i
" gapers-block" phenomenon.
That is, the drivers along the freeway slowed their cars to observe the activities associated with the processing of the vehicle involved in the accident.
There is no mention of a perceived reduction in width.
Goolsby then indicates that capacity returns to normal when the [ accident) investigation is complete.
3 Thus, a car parked on a shoulder, with no associated activity, would have a negligible effect on traffic flow.
For example, the narrowing of a lane, due to maintenance or construction purposes, to 10 or 11 feet widths, provides a J
i 4
e capacity of about 1800 vph as described on page 6-13 of the HCM.
This figure compares with the value of 1728 selected for the ETE study (see page 3-10).
i In the HCM chapter on Intersection capacity, the impact of a lane of parked, motionless cars can reduce capacity by q
up to 10 percent (Table 9-8 in HCM); a single parked car should produce a lesser effect.
The estimates of highway capacity by KLD (see discussion in Section 3), takes into l
account uncertainty in driver responses.
The ETE has reasonable expectations that under i
l emergency conditions, there could be produced somewhat uncertain responses on the part of the evacuating public.
For example, it must be anticipated that some vehicles will exhaust their fuel supply and will have to be pushed to a shoulder or driveway.
Such short-term disruptions also serve to reduce capacity for short periods of time, and justify the conservative posture we have adopted.
We believe that this posture is prudent and responsive to the intent of NUREG-0654.
As noted on page 3-4, the calculation of ETE asserts i
that capacity of a link is reduced by 15 percent when congestion (i.e., Level of Service, F) prevails there.
The following appears in Chapter 6 of the Highway capacity Manual (HCM):
f i
4 l
In many cases, vehicles are unable to depart a standing queue at the normal capacity rate of 2,000 pcphpl.
In their studies of uninterrupted flow characteristics, Edie and l
others (30) have noted that the relationships 1
among speed, density, and flow may be discontinuous at the point of capacity, and that the maximum rate of flow of vehicles departing a queue may be less than capacity under stable flow.
Various observations of a freeway queue departure rates range from as low as 1,500 pcphpl to as high as 2,000 pcphpl.
Local driving characteristics have a major influence on this effect, which ranges from a significant reduction in capacity (compared to 2,000 pcphpl) of up to 25 percent to cases in which there is virtually no reduction.
Since capacity reduction during congestion can range l
l from zero to 25 percent, our adoption of a 15 percent reduction is sound.
In summary response to this basis, the expressed concerns regarding this issue have been incorporated into the KLD procedures to calculate the ETE.
The NHCDA has elected to utilize routine procedures l
for dispatch of towing vehicles by the state Police as their r
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l l
l l
preferred option.
The time for a tow truck to respond to a need depends on the location of the disabled vehicle, but the distance traveled will be minimized by contact with the most proximate towing service.
Note that if a tow truck receives a call for assistance while returning to its original position, it will respond immediately; in these cases the tow vehicles will move from one incident directly to the next.
The contention argues that buses will travel at high speeds (even though they challenge these estimates elsewhere) implying that an accident at these speeds could disable a car.
The higher speed vehicles, however, are traveling counterflow and are assumed to take place on Interstate roads, or the highways traveling toward the EPZ.
The majority of vehicles on the road within the EPZ are evacuating at low speed.
(Note the contention misquoted the last sentence on page 12-3.)
The contention argues that the reduction in capacity e
to account for snow is inadequate.
This contention is incorrect in its interpretation of the term
" water-equivalent snowfall".
The ratio of
" water-equivalent" to " depth of snow" is commonly termed
" snow-density".
Average densities generally range from 0.05 to 0.3 with the higher figures applicable for late-winter snow (with a high moisture content).
The average figure for 16 -
freshly fallen snow is 0.1, which we will use.
(See Appendix H of NCHRP Report No. 127).
Applying this figure, a fall of 6 inches over 8 hours9.259259e-5 days <br />0.00222 hours <br />1.322751e-5 weeks <br />3.044e-6 months <br />, as cited in the contention, is equivalent to 0.075 in./hr.
l water equivalent snowfall.
On this basis, the associated percent capacity reduction using the 2.8 percent model cited in the contention ist 8 + 0.075 x 2.8/0.01 = 29 percent This figure for the indicated severe snowfall, which only applies to conditions at the end of 8 hours9.259259e-5 days <br />0.00222 hours <br />1.322751e-5 weeks <br />3.044e-6 months <br />, compares with the representative figure of 25 percent in the ETE study, which is applicable throughout the 8-hour evacuation period.
Other studies offer evidence that capacity reduction due to snow is less pronounced.
Using data from Appendix E of p
NCHRP Report 127, capacity is reduced by 25 percent whenever i
l
" snowstorm speed factor" is about 0.55.
This value corresponds to a condition of 1 inch per hour of snowfall over 5 or more hours.
Note that the EPZ is subject to an average of 12-16 inches of snowfall per winter month, as shown in Table 1-1 i
l of the plan.
Thus, the examples given above represent i
i near-extreme conditions, rather than reasonable expectations.
Even so, the 25 percent capacity reduction figure is applicable.
The use of a higher value of capacity 17 -
i l
l l
. ~..
reduction due to snow would bias the ETE results on the high side.
Fog is discussed on page 2-11 of Volume 6 and is 1
considered under inclement weather.
Consultation with Messrs. Sonnichsen and Goetz of FEMA Region 1 in Boston forms the basia of the following
]
discussion on flooding.
There are two types of flooding:
r Tidal flooding Riverine flooding j
j Tidal flooding is generally associated with high winds which raise the level of the tide along the coastal areas.
l Of course, the level of the tide still responds to the lunar 4
t cycle.
It was estimated by FEMA that for the 50-year storm, l
it was possible for parts of Salisbury beach to remain under
)
water for as long as 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> at high tide, at a depth which I
would make vehicle passage impossible and with no alternative roads available.
4 such an event, if synchronous with the Order to s
Evacuate, could delay some permanent residents up to 2 I
hours.
(Note that such storms do not, in general, occur l
during the tourist season).
Since the ETE substantially l
exceeds 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br />, this extension in trip generation time does not necessarily imply an extension in ETE -- certainly not i
j an extension of as much as two hours, in any care.
(of course, such a severe storm may well lead to the beach area 1
l being evacuated prior to the accident.)
l 1
Riverine flooding is associated with rainwater and/or i
melting cnow run-off, and generally occurs in the Spring.
Riverine flooding could also occur during heavy rains i
produced by hurricanes in Autumn.
The Town of Exeter is i
most vulnerable to such flooding which could sever one, and j
possibly two evacuation routes.
Specifically, Route 108 i
south of the village is a potential flood area, as well as i
Route 150 in northern Kensington.
Fortunately, there are five other evacuation routes from 4
i i
Exeter to the north and west.
Calculations of ETE indicate
)
that the ETE for residents of the Town of Exeter are less i
than for residents in the towns in the coastal region; l
therefore, any incremental delays experienced in Exeter due
)
i to the loss of a flooded road should not extend the overall i
travel time for the residents in the EPZ, beyond the ETE.
The effect of ice storms on the ETE can vary widely depending on the conditions of ice on the pavement and on l
the temperature.
The friction factor offered by an icy surface varies with temperature, increasing as temperature decreases below freezing.
In the temperature range between 4
28 and 32 degrees F, the heated tire surface can ride on a film of water and traction is at a minimum.
Under these I
circumstances, travel would be slowest.
An exhaustive literature search revealed no estimate of the effect of ice on highway capacity.
In the absence of i
t 1
such data, a 25 percent reduction in capacity as used for snow appears acceptable for the following reasons:
Highway capacity during an ice storm may be less than that during a snowfall, thus tending to increase travel time relative to snow.
(Of course, sanding operation would restore capacity to a sginificant extent.)
There is no need to shovel a driveway in an ice storm, in general, thus tending to reduce trip generation time, relative to snow.
While we have no data to quantify these trade-offs, it is reasonable to expect that the net effect is limited.
11.
Item 10.
Rejected by the ASLB, 2/18/87.
12.
Item 11.
This contention argues that the time estimate study does not account for topographical features.
This is not correct.
As indicated by the discussion on page 3-8 the estimates of capacity for all two-lane roads within the EPZ are classified as " rolling terrain".
Note that the vast majority of congested highways are east of I-95.
The terrain in this area is relatively flat with elevations rarely exceeding 100 feet above sea level.
The contention also argues that "chokepoints and bridges" have been ignored.
An ETE survey of the highway network indicates that the bridges should not constitute chokepoints.
Any vehicles stalled on a narrow bridge (a low-probability event) can be pushed forward to a shoulder just beyond the bridge.
,20 -
x
,C 7
6, 4.
b t
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13.
Iter-12., A telephone r,urvey"was conducted in early'
~
2 i-1987 by the NHCDA in' order to verify the mobilization times t
for bus company. vehicles under let,ts of agraement., This survey indicated that approximateli 30% of:needed vehicles
.could report to State staging'trens'within one hour, m.,d
- t j
that the remaining needed busep cou12 report within 2 1.rtra of notification.
While this information varios somewhat
4
~
from the results of the mobilization survey conducted in
+
s preparation of the'ETE, zero imp'act te,the PlfE will be experienced using data frcm thin supplempntal survey for those scentirios where evacuatioit t' ravel time exceeds clansid-J
__. as the subject vehicles will merge with the
- times,
. ~
l evacuating traffic.
'SSme effect gLay be experienced on1.y'for
,1 i
the off-season scenerios where evacuation, time estimates are'[_
i 1
minimized.
i i
It is noted that historie d records indicate thn*. most evacuees use private vehicles.
The publicstion entitled
" Evacuation Risks -- An Evalua cion", by Joseph M. Hans et 4
al., June 1974, is an analysiu of over 50 true Tife
)
emergencies req. tiring evacuation of 1,142,336 persons.
Page s
51 of this document notes that "(i)n most evacuations,
~
people use their private vehicles",'also, " cars With mechanical breakdowns worr. pushed off the road dnd theit s.
occupants were absorked in other evreuating vehicles".
Thus, the estimated need for transportation via bus may be i
i i
significantly less than prepared for within the NMREh?.
I
. )
ll 3
1 s
'This contention argues that the " response rate" could not reas'onably be expected to be as nearly as favorable as v
the mobilization rates cited in the KLD report during off
)
business hours.
It is reasonable to argue, however, that the reverse is true.
Bus drivers will have a greater probability of being in their homes during off business hours than during mid-day.
Consequently, there is a higher probability that the mobilization time would be thereby reduced.
14.
Item 13.
This contention argues that the estimate of people within the EPZ who require transit assistance in crde'r to evacuate is understated.
There is no support given
'for this contention.
Furthermore, the contention misstates the contents of the ETE.
Specifically, the contention states that the " revised KLD report now computes the number of persons within the EPZ having no vehicles available and requiring transit services at 2249..."
This statement is not' correct.
The ETE calculates that the number of people requiring transit within New Hampshire is 4495, not 2249 peop 3 as acaerted in the contention.
This figure of 4495
]
people constitutes approximately 5% of the total resident population within the New Hampshire portion of the EPZ.
In response to concerns expressed by FEMA that the plan should take into account the high probability that ride J
sharing would provide transportation for most of these i
p people, an estimate of 50% has been applied to indicate
' r
's
n those transit dependent people who will be able to ride share.
Thus, the estimate of 2249 people requiring transit i
are those who do not have access to a vehicle and who do not have access to ride sharing.
In addition, the transit needs as estimated by KLD agree favorably with those obtained by the NHCDA survey.
The July 11, 1986 survey report date indicates a total of 2106 persons requiring transit assistance, while the August 15, 8
1986 report date indicates a total of 2378 persons.
The contention offers no evidence to dispute either or both findings.
The estimate of 2.65% of households with no car available was empirically determined by way of the KLD survey.
The validity of the KLD survey is discussed under Item 6 above.
The use of the NHCDA survey to identify special needs persons has been previously accepted by the Board; therefore, this basis complaint that the NHCDA survey has " reliability problems" is without merit.
15.
Item 14.
This contention argues that KLD has underestimatekthetimeforloadingabuswithmembersof the population from special facilities.
It takes issue with the use of a 15 second mean headway.
In Table-12-33 in the Highway Capacity Manual, empirical data has lead to the estimate of boarding times per passenger equal to 2.6 secondstwhich includes the payment of a fare with a single coin.
Other figures are 3.0 seconds for exact fare and 3.5 seconds for passengers who are standees on a bus.
It is
_ 23 -
seen that our estimate for people from special facilities is approximately 5 times that in'the Highway Capacity Manual.
Also, the figure of 15 seconds is an average boarding time, balancing a generous boarding time for ambulatory persons with a potentially longer boarding time required by non-ambulatory persons.
We feel this is a reasonable estimate and the argument to the contrary is unsupported.
It is true that the total time to load passengers, which consists of travel from the local transportation center to the special facility plus the time for passengers to board the bus, was estimated at 40 minutes (0.67 hour7.75463e-4 days <br />0.0186 hours <br />1.107804e-4 weeks <br />2.54935e-5 months <br />) in Progress Report No.
7.
The current estimate is 45 minutes (0.75 hour8.680556e-4 days <br />0.0208 hours <br />1.240079e-4 weeks <br />2.85375e-5 months <br />), as documented on page 11-21.
The number of non-ambulatory persons outside of special facilities who are in need of.special transportation assistance has been determined by way of the NHCDA special needs survey, and has been included in the local RERPs.
16.
Item 15.
This contention argues that the rural roads were classified into "only 4 crude groups" and argues that the detailed data collected should confirm that the minimum width of each roadway section should be greater or equal to those values which are defined in these groups.
The measurements that are taken in the field were taken at the representative section:
It is not practical or feasible to take width measurements at closely spaced intervals along the highway nor is it necessary.
The discussion on page 8-8,
t U
v' of the Highway Capacity Manual does not stipulate that such detailed measurements need to be taken and furthermore indicates that "the impact of narrow lanes restricted I
shoulder widths is less deleterious if vehicles are~already traveling at reduced speeds which prevail under capacity operation".
Note that the qualifications used are no less
" crude" than that used in table 8-5 of the Highway Capacity
.i Manual.
17.
Item 16.
Rejected by the ASLB, 2/18/87.
18.
Item 17.
The NHRERP, Volume 6, Section 11 at i
p.
11-8 utilizes a deliberately selected conservative figure of 6 percent with which to estimate persons needing transit because of out of service vehicles.
This figure assumes that on the average, every vehicle is out of service 3 weeks 4
per year.
This figure is higher than available sources indicate which is 4 days per year, or 1.1 percent of the time.
i Whether the. 1.1 percent figure is applied to the percentage of EPZ population who own one vehicle or the 6 percent figure is applied to the estimated transit-dependent population, the result is the same (approximately 0.3 percent of the population would require transportation assistance becauselof out of service vehicles).
The calculational method has no impact on-ETE.
19.
Item 18.
In~sub-item A it is argued-that the' data in Appendix N "seems to imply that 1500 cars can enter node 4
i _
number 1 from each of 3 directions".
This is not correct.
The actual discharge rate through node 1 is about 800-900 vph.
The discussion of the calculation of capacity extends from page 3-1 through page 3-11 of Volume 6.
Under item B the contention argues that loading procedures are not described in much detail.
In actual fact, the trip generation rates are given in great detail in Appendix M.
For representative scenarios and off-season scenarios considered and for all centroids, these data indicate the variation of loading rates over time.
Note that these are nominal loading rates which could be reduced by congestion on the evacuation network.
The actual loading rates are computed internally by the simulation model and are not provided as output.
In item C the contention argues that a " substantial amount of passing has been assumed since...fd=0.675."
This t
is not correct on several counts.
First, the value of fd as indicated on page 3-9 of Volume 6 is 0.75 not 0.675.
Volume 6, p. 3-9 assumes a directional split of traffic (averaged over the evacuation time frame) on all two-way road sections i
of 0.9.
That is, 90% of all traffic is outbound and 10% is inbound; the outbound traffic is evacuating while the inbound traffic is the " light" counterflow traffic.
Columns A and B, Table 4-2 of Volume 6, demonstrate that over the majority of the evacuation, very little counterflow traffic
)
exists.
Thus, the estimate of 90% directional split, and l l'
O' use of 0.75 as the value of fd, is supported by.these statistics.
The statement under item D questions how the light-traffic patterns which are indicated in Appendix I had been treated in the simulation model.
These light traffic patterns represen1 traffic which is moving in directions which are generally counterflow to those of evacuating traffic.
Therefore, while the simulation model does not explicitly consider this inbound traffic, the effects of the inbound flow is included in the ETE calculations through the capacity calculation of the roadway system.
20.
Item 19.
This contention argues that the estimate of 2.6 people per vehicle is unrealistic particularly for the'first hour when people will be returning home or picking up family members.
This argument is without basis.
As specified on page 2-5 the estimate pertains to " Persons per Vehicle for the Evacuation of Permanent Residents"; thus, this estimate of 2.6 persons is for evacuating residents, not for those people returning home to pick up family members.
The contention also argues that the data of actual counts of vehicle occupancy collected in August 1985 and July 4th weekend in 1986 do not support this estimate.
The contention fails to state that these counts are taken of vacationers in the beach area and do not represent household populations.
By direct observation many of the vehicles
- visiting the beach. transport couples (that is, small groups 4
in a social environment); by direct observation the number of vehicles transporting family units are in the minority.
Thus, the data taken in the beach areas, which produce an average vehicle occupancy of about 2.4 persons, are not representative of household units:
the estimate of 2.6 persons pertains only to residents which by definition form household units.
Thus, the argument here is without merit.
21.
Item 20.
This contention argues that.KLD should have taken extensive area photographs during the height of the beach season rather than relying on " indirect inferences from beach blanket space and parking spaces...".
In fact, KLD has reviewed area photographs taken during the height of J
^
the beach season during 1985 as well as over the July 4th weekend in 1986.
Furthermore, there have been extensive data collection activities taken on the ground measuring traffic volume on all the beach access roads.
During 1983, which was the peak season in recent years for the New Hampshire coastal area, traffic counts were taken 24 hours2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br /> a day 7 days a week throughout the entire summer season.
Table 2-3 on page 2-13 documents traffic counts entering and exiting the Seabrook and Hampton Beach areas on the most crowded day of this peak season in 1983.
As indicated there the aggregate influx of vehicles for this peak day took place at 2:00 p.m.
and amounted to about 5600 cars.
This.
actual count is consistent with the data for Hampton and y-,.-
,u-,
~.
4 Seabrook Beaches which were obtained using the aerial film.
Refer'to the discussion on pages 2-8 through 2-13.
22.
For the above reasons, it is my opinion that Volume 6 of the NHRERP, Evacuation Time Study, properly accounts for the number of vehicles evacuating the EPZ and potential travel impediments under various scenarios; relies on empirical, unbiased, factual bases, and on solid, unbiased assumptions; accounts realistically for driver uncertainty, topographical features, transport of transit dependent persons, and roadway capacities, and thus is an accurate evacuation time study of the 10-mile plume EPZ surrounding Seabrook Station.
mn Edward B. Lieberman 1.
STATE OF NEW YORK March h 1987 Duf70M ss The above subscribed Edward B. Lieberman appeared before me and made oath that he had read the foregoing affidavit and that the statements set forth therein are true to the best of his knowledge.
4 Before me, Luw Ndtary Public
,My Commission Expires:
. ROCHELLE lANDr.-
Notary Public, State of *:-;,,.
No. 52-4742519 -
Qualified in Suttork County Commission Expires March 30.19 l
, 4 y
~
~
PROFESSIONAL QUALIFICATIONS EDWARD B.
LIEBERMAN Vice President 1
KLD ASSOCIATES, INC.
My name is Edward B.
Lieberman and my business address is KLD Associates, Inc., 300 Broadway, Huntington Station, 1
New York 11746.
I am presently Vice President of KLD Associates, Inc.
l I received the Bachelor of Science degree in Civil Engineering in 1951 from Polytechnic Institute of Brooklyn.
I was awarded the Master of Science degree in Civil Engineering in 1954 from Columbia University and in Aeronautical Engineering in 1967 from Polytechnic Institute l
j of Brooklyn.
I am currently working on a Doctorate degree j
in Transportation Planning at the Polytechnic University.
I i
j am a member of the Chi Epsilon Honorary Fraternity.
With almost 30 years of professional experience, I have i
managed a number of major projects.
I pioneered the
)
development and application of traffic simulation models, I
making major state-of-the-art innovations in the traffic i
engineering profession.
I have also been responsible for f
many engineering studies involving data collection and
]
analysis and. design of traffic control systems to expedite l
traffic flow and relieve congestion.
i I have developed simulation models to study traffic j
performance on urban networks, freeways, freeway corridors i
i
, ~. - -...
= -.
and two-lane, two-way rural roads.
These programs include t
consideration of pedestrians, interaction with vehicular traffic, truck and bus operations, special turning lanes, j
and vehicle fuel consumption and emissions; both pretimed and actuated traffic signal controls are represented.
I was the Principal Investigator for the development of traffic signal control strategies for. congested conditions in mid-Manhattan.
These strategies were implemented and J
evaluated in the field.
Field tests indicated substantial l
reductions in delay combined with increased vehicle throughput.
I was the Principal Investigator in.the development of i
an interactive computer graphics (ICG) software system for displaying traffic simulation results generated by the NETSIM model.
I designed the overall structure of the software for implementation on PC AT computers and, subsequently, on larger ICG work stations.
This work was sponsored by EHWA.
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 I
dynamic traffic simulation model designed for all types of i
roadway facilities (urban streets, freeways, rural roads).
i DYNEV is designed to be used as a tool to develop and i
organized evacuation plans needed as part of general 2-4 n,.
c,g.-n,,,va-
,-e w
-,.,--r
' 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 extensive evacuation plan for the LILCO Shoreham Nuclear Power Station on Long Island, New York.
In developing this evacuation plan for the Seabrook Nuclear Power Station, my activities include definition of evacuation scenarios, definition of the evacuation network, development of traffic control treatments and of traffic routing patterns, analysis of trip tables, analysis of simulation results, optimization of evacuation strategies and the preparation of formal documentation.
I was responsible for the development of the I-DYNEV model, an interactive version and enhancement of the DYNEV i
model, under contract with the Federal Emergency Management Agency (FEMA).
I-DYNEV, in turn, was integrated into the Integrated Emergency Management Information System (IEMIS),
developed by FEMA.
I-DYNEV was applied to estimate the evacuation times for the Emergency Planning Zones (EPZ) for eight nuclear power stations.
I developed course material and conducted training for emergency planning personnel at the National Emergency Training Center (NECTC) in Emmittsburgh, Maryland.
I was also responsible for the designs of the NESIM microscopic urban traffic simulation model (formerly UTCS-1) and of the SCOT freeway traffic simulation model.
The l t
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 assignment algorithm which routes traffic over a network in response to changing traffic flow characteristics to satisfy a specified origin-destination table.
In addition, I have developed advanced traffic control policies for urban traffic for the FHWA-sponsored UTSC 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 generation" area-wide, cycle-free control policies for moderate and congested traffic flow for computer-monitored real-time systems.
I also developed a cycle-based, off-line computational procedure named SIGOP-II, to optimize traffic signal timing patterns to minimize system "disutility."
i 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 programming techniques, TRAF integrates:
NETSIM, TRAFLO, and ROADSIM, a microscopic rural-road simulation model.
I served as Principal Investigator on NCHRP Project 3 entitled, " Traffic Signal Warrants."
This project involved both field data collection and the application of the NETSIM 1
model to study intersection delay as a function of traffic volume, a type of control and geometrics.
In turn, I developed and documented new signal warrants, some of which will be incorporated in the next version of the Manual on 4
Uniform Traffic Control Devices (MUTCD).
i Under NHTSA sponsorship, I directed a research study to evaluate a Driver Vehicle Evaluation Model named DTRVEM.
I This model simulates the response of motorists to hazardous 1
events.
This effort included analysis of the model j
formulation and software and sensitivity testing.
A workship was designed, organized,-scheduled and conducted by myself and other KLD professionals; experts from all over l
the U.S. were invited to recommend specific NHTSA research i
activities for the further development of the model.
A l
j recommended research program constituted the major output of I
the contract.
1 i
i
- )
j t
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 analysis of differential equations.
These analyses were programmed for the IBM 7090 and System 360, CDC 6600 and 7600, G.E.
625 and UNIVAC IIOB digital computers in assembly languate, FORTRAN and PLI.
I also designed the logic and real-time programming for a sonar simulator built for the Department of Navy and monitored by a PDP-8 progess-control digital computer.
I am a member of the American Society of Civil Engineers, the Institute of Transportation Engineers, the Association of Computing Machinery and the Transportation Research Board (TRB).
I am also a member 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 Annual Simulation Symposium, 1970.
l l
(
t
" Simulation of Traffic Flow at Signalized Intersections:
the SURF System," Proceedings, 1970 Summer-Computer Simulation Conference, 1970.
" Dynamic Analysis of Freeway Corridor Traffic," SME 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 l
with R. D. Worrall and J. M.
Bruggerman).
" Variable Cycle Signal Timing Program:
Volumes 1-4," Final Report of Contract DOT-FH-11-7924, June, 1974.
" Traffic Signal Warrants," KLD TR-51, i
Final Report on NCHRP Project 3-20/1, December 1976 (with G.
F. King and R.
Goldblatt).
" Rapid Signal Transition Algorithm," Transportation Research i
Record No. 509 1974 (with D. Wicks).
I "Subnetwork Structuring and Interfacing for UTCS Project-Program of Simulation Studies," KLD TR-5, January, 1972.
" Development of a Bus Signal Preemption Policy and a System Analysis of Bus j
Operations," KLD TR-11, April, 1973.
t "SIGOP-II - Program to Calculate Optimal, Cycle-Based Traffic Signal Timing Patters, Volumes 1 and 2,"
Final l
Report, Contract DOT-FH-11-7924, KLD i
TR-29 and TR-30, December, 1974.
Summary report inTransportation Research Record 596, 1976 (with J. Woo).
" Developing a Predictor for Highly t
I Responsive System-Based Contro,"
Transportation Research Record 596, 1976 l
(with W. McShane and R. Goldblatt).
i i I 4
- ~..,, _
___,,,m.
_,m.
"A New. Approach for Specifying Delay-Based Traffic Signal Warrants,"
l Transportation Research Special Report i
153 - Better Use ofExisting i
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 l
J. Woo).
I
" Extension of the UTCS-1 Traffic Simulation Program to Incorporate.
Computation of Vehicular Fuel Consumption and Emissions," KLD TR-63, s
1976 (with N. Rosenfield),
t
" Analysis and Comparison of the.UTCS Second-and Third-Generation Predictor l
Models," KLD TR-35, 1975.
i
" Urban Traffic Control System (UTCS) i Third Generation Control (3-GC) Policy,"
Vol.
1, 1976 (with A. Liff).
" Design of TRAFIC Operating System (TOS), KLD TR-57, 1977.
4
" Revisions to the UTCS-1 Traffic l
Simulation Model to Enhance Operational Efficiency," KLD TR-59, 1977 (with A.
i Wu).
"The Role of Capacity in Computer i
Traffic Control," in Research Directions in Computer Control of Urban Traffic j
Systems, ASCE, 1979.
l
" Traffic Simulation:
Past, Present and Potential," in Hamburger, W.S.
and
- Steinman, L.,
eds., Proceedings of the International Symposium of Traffic i
Control Systems, University of California, Berkeley, 1979.
"TRAFLO:
A New Tool to Evaluate Transportation System Management Strategies," presented at the 59th i
l
{ l
Annual Meeting of the Transportation Research Board, 1980 (with B. Andrews),
f
" 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 Simulation Model," presented at the 59th Annual Meeting of the Transportation Research Board, 1980 (with M. Yedlin).
" Hybrid Macroscopic-Microscopic Traffic Simulation Model," presented at the 59th Annual Meeting of the Transportation Research Board, 1980 (with M. C.
i Davila).
"A Model for Calculating Safe Passing s
Distance on Two Lane Rural Road,"
presented at the 60th Annual Meeting of the Transportation Research Board, 1981.
"The TRAF System - Anayltic Formulation and Logical Design of the Roadsim Model," KLD TR-129, June, 1983.
"PREDYN User's Guide," KLD TR-131, June, q
1983.
1 "The TRAF System - Technical Report,"
KLD TR-136, August, 1983 (with M.
i Yedlin, B. Andrew and K. Sheridan).
" Application of the I-DYNEV System to Compute Estimates of Evacuation Travel Time at Nuclear Power Stations -- Four Demonstration Case Studies," KLD TR-142, December, 1983.
" Users Manual for the Interactive Dynamic Network Evacuation Model:
I-DYNEV,"KLD TR-144, February, 1984.
+
e--.-m v..a
.,.m
. =.
O
" Formulations of the DYNEV and I-DYNEV Traffic Simulation Models Used in EESF,"
l KLD TR-154, March, 1984.
"PREDYN/IDYNEV Training Guide," KLD TR-155, April, 1984 (with R. Goldblatt).
" Specifications of Recommended Interactive Graphics Hardware Configuration and Graphics Support Software for the Netsim Graphics Display Package," KLD TM-93, July, 1985.
" Metering of High-Density Sectors Comparison of Traffic Operations Along Fifth Avenue in Mid-Manhattan:
Metering Control vs. Existing Control," KLD TM-94, July, 1985.
4
" Description of an Integrated Traffic Assignment and Distribution Model (TRAD) for the IDYNEV System," KLD TR-187, April, 1986.
" Evacuation Plan Update (Robert G. Ginna Nuclear Power Station)," KLD TR-189, May, 1986 (with R. Goldblatt).
" Evacuation Plan Update (Davis Besse),"
KLD TR-190, July, 1986 (with R.
Goldblatt).
"Seabrook Station Evacuation Time Estimates and Traffic Management Plan Update," KLD TR-174, August, 1986.
" Reducing Traffic Congestion at Herald Square," ITE Journal, September, 1986, pp. 27-31 (with A. K. Rathi).
" Congestion Based Traffic Control Scheme for High Traffic Density Sectors,"
4 Transportation Research Record No. 1057, TRB, National Research Council, Washington, D.C.,
1986, pp. 49-57 (with A. K. Rathi and G.
F. King).
" Overview of the Evacuation Plan and of t
the Evacuation Time Estimtaes for the Seabrook Nuclear Power Station," KLD TM-98, October, 1986.,
" Overview of the Evacuation Plan and of the Evacuation Time Estimates of the Ginna Nuclear Power Station," KLD TM-99, November, 1986 (with R. Goldblatt).
" Overview of the Coastal Region within the Pilgrim Station Emergency Planning Zone," KLD TM-100, November, 1986.
" Enhanced Freflo Program:
Simulation of Congested Environments," paper submitted for presentation at Transportation Research Board's 66th Annual Meeting, January, 1987 (with A. K. Rathi and M.
Yedlin).
"The Netsim Graphics System," paper submitted for presentation at Transportation Research Board's 66th Annual Meeting, January, 1987 (with B.
Andrews and A.
Santiago).
,