ML12361A071

Kld TR-491, Final Report, Rev. 1, South Texas Project Electric Generating Station, Development of Evacuation Time Estimates, Appendix a - Glossary of Traffic Engineering Terms Through Appendix H, Evaluation Regions

ML12361A071
Person / Time
Site:	South Texas
Issue date:	12/17/2012
From:	KLD Engineering, PC
To:	Office of Nuclear Reactor Regulation, South Texas
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NOC-AE-12002941 KLD TR-491, Rev 1
Download: ML12361A071 (110)

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APPENDIX A Glossary of Traffic Engineering Terms A. GLOSSARY OF TRAFFIC ENGINEERING TERMS Table A-1. Glossary of Traffic Engineering Terms Def60 Analysis Network Link Measures of Effectiveness Node Origin Prevailing Roadway and Traffic Conditions A graphical representation of the geometric topology of a physical roadway system, which is comprised of directional links and nodes.A network link represents a specific, one-directional section of roadway. A link has both physical (length, number of lanes, topology, etc.) and operational (turn movement percentages, service rate, free-flow speed) characteristics.

Statistics describing traffic operations on a roadway network.A network node generally represents an intersection of network links. A node has control characteristics, i.e., the allocation of service time to each approach link.A location attached to a network link, within the EPZ or Shadow Region, where trips are generated at a specified rate in vehicles per hour (vph). These trips enter the roadway system to travel to their respective destinations.

Relates to the physical features of the roadway, the nature (e.g., composition) of traffic on the roadway and the ambient conditions (weather, visibility, pavement conditions, etc.).Maximum rate at which vehicles, executing a specific turn maneuver, can be discharged from a section of roadway at the prevailing conditions, expressed in vehicles per second (vps) or vehicles per hour (vph).Maximum number of vehicles which can pass over a section of roadway in one direction during a specified time period with operating conditions at a specified Level of Service (The Service Volume at the upper bound of Level of Service, E, equals Capacity).

Service Volume is usually expressed as vehicles per hour (vph).The total elapsed time to display all signal indications, in sequence.The cycle length is expressed in seconds.A single combination of signal indications.

The interval duration is expressed in seconds. A signal phase is comprised of a sequence of signal intervals, usually green, yellow, red.Service Rate Service Volume Signal Cycle Length Signal Interval South Texas Project Electric Generating Station Evacuation Time Estimate A-1 KLD Engineering, P.C.Rev. 1 Term Definiio Signal Phase Traffic (Trip) Assignment Traffic Density Traffic (Trip) Distribution Traffic Simulation Traffic Volume Travel Mode Trip Table or Origin-Destination Matrix Turning Capacity A set of signal indications (and intervals) which services a particular combination of traffic movements on selected approaches to the intersection.

The phase duration is expressed in seconds..A process of assigning traffic to paths of travel in such a way as to satisfy all trip objectives (i.e., the desire of each vehicle to travel from a specified origin in the network to a specified destination) and to optimize some stated objective or combination of objectives.

In general, the objective is stated in terms of minimizing a generalized "cost". For example, "cost" may be expressed in terms of travel time.The number of vehicles that occupy one lane of a roadway section of specified length at a point in time, expressed as vehicles per mile (vpm).A process for determining the destinations of all traffic generated at the origins. The result often takes the form of a Trip Table, which is a matrix of origin-destination traffic volumes.A computer model designed to replicate the real-world operation of vehicles on a roadway network, so as to provide statistics describing traffic performance.

These statistics are called Measures of Effectiveness.

The number of vehicles that pass over a section of roadway in one direction, expressed in vehicles per hour (vph). Where applicable, traffic volume may be stratified by turn movement.Distinguishes between private auto, bus, rail, pedestrian and air travel modes.A rectangular matrix or table, whose entries contain the number of trips generated at each specified origin, during a specified time period, that are attracted to (and travel toward) each of its specified destinations.

These values are expressed in vehicles per hour (vph) or in vehicles.The capacity associated with that component of the traffic stream which executes a specified turn maneuver from an approach at an intersection.

South Texas Project Electric Generating Station Evacuation Time Estimate A-2 KLD Engineering, P.C.Rev. 1 APPENDIX B DTRAD: Dynamic Traffic Assignment and Distribution Model B. DYNAMIC TRAFFIC ASSIGNMENT AND DISTRIBUTION MODEL This section describes the integrated dynamic trip assignment and distribution model named DTRAD (Dynamic Traffic Assignment and Distribution) that is expressly designed for use in analyzing evacuation scenarios.

DTRAD employs logit-based path-choice principles and is one of the models of the DYNEVII System.The DTRAD module implements path-based Dynamic Traffic Assignment (DTA) so that time dependent Origin-Destination (OD) trips are "assigned" to routes over the network based on prevailing traffic conditions.

To apply the DYNEV II System, the analyst must specify the highway network, link capacity information, the time-varying volume of traffic generated at all origin centroids and, optionally, a set of accessible candidate destination nodes on the periphery of the EPZ for selected origins.DTRAD calculates the optimal dynamic trip distribution (i.e., trip destinations) and the optimal dynamic trip assignment (i.e., trip routing) of the traffic generated at each origin node traveling to its set of candidate destination nodes, so as to minimize evacuee travel "cost".Overview of Integrated Distribution and Assignment Model The underlying premise is that the selection of destinations and routes is intrinsically coupled in an evacuation scenario.

That is, people in vehicles seek to travel out of an area of potential risk as rapidly as possible by selecting the "best" routes. The model is designed to identify these"best" routes in a manner that realistically distributes vehicles from origins to destinations and routes them over the highway network, in a consistent and optimal manner, reflecting evacuee behavior.For each origin, a set of "candidate destination nodes" is selected by the software logic and by the analyst to reflect the desire by evacuees to travel away from the power plant and to access major highways.

The specific destination nodes within this set that are selected by travelers and the selection of the connecting paths of travel, are both determined by DTRAD. This determination is made by a logit-based path choice model in DTRAD, so as to minimize the trip"cost", as discussed later.The traffic loading on the network and the consequent operational traffic environment of the network (density, speed, throughput on each link) vary over time as the evacuation takes place.The DTRAD model, which is interfaced with the DYNEV simulation model, executes a succession of "sessions" wherein it computes the optimal routing and selection of destination nodes for the conditions that exist at that time.Interfacing the DYNEV Simulation Model with DTRAD The DYNEV II system reflects NRC guidance that evacuees will seek to travel in a general direction away from the location of the hazardous event. An algorithm was developed to support the DTRAD model in dynamically varying the Trip Table (O-D matrix) over time from one DTRAD session to the next. Another algorithm executes a "mapping" from the specified"geometric" network (link-node analysis network) that represents the physical highway system, to a "path" network that represents the vehicle [turn] movements.

DTRAD computations are performed on the "path" network: DYNEV simulation model, on the "geometric" network.South Texas Project Electric Generating Station B-1 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 DTRAD Description DTRAD is the DTA module for the DYNEV II System.When the road network under study is large, multiple routing options are usually available between trip origins and destinations.

The problem of loading traffic demands and propagating them over the network links is called Network Loading and is addressed by DYNEVII using macroscopic traffic simulation modeling.

Traffic assignment deals with computing the distribution of the traffic over the road network for given O-D demands and is a model of the route choice of the drivers, Travel demand changes significantly over time, and the road network may have time dependent characteristics, e.g., time-varying signal timing or reduced road capacity because of lane closure, or traffic congestion.

To consider these time dependencies, DTA procedures are required.The DTRAD DTA module represents the dynamic route choice behavior of drivers, using the specification of dynamic origin-destination matrices as flow input.Drivers choose their routes through the network based on the travel cost they experience (as determined by the simulation model). This allows traffic to be distributed over the network according to the time-dependent conditions.

The modeling principles of D-TRAD include: " It is assumed that drivers not only selectthe best route (i.e., lowest cost path) but some also select less attractive routes. The algorithm implemented by DTRAD archives several"efficient" routes for each O-D pair from which the drivers choose." The choice of one route out of a set of possible routes is an outcome of "discrete choice modeling".

Given a set of routes and their generalized costs, the percentages of drivers that choose each route is computed.

The most prevalent model for discrete choice modeling is the logit model. DTRAD uses a variant of Path-Size-Logit model (PSL). PSL overcomes the drawback of the traditional multinomial logit model by incorporating an additional deterministic path size correction term to address path overlapping in the random utility expression." DTRAD executes the TA algorithm on an abstract network representation called "the path network" which is built from the actual physical link-node analysis network. This execution continues untila stable situation is reached: the volumes and travel times on the edges of the path network do not change significantly from one iteration to the next. The criteria for this convergence aredefined by the user." Travel "cost" plays a crucial role in route choice. In DTRAD, path cost is a linear summation of the generalized cost of each link that comprises the path. The generalized cost for a link, a, is expressed as c, = at,+6, +)ys, wherecis the generalized cost for link a, and a,,8, and yare cost coefficients for link travel time, distance, and supplemental cost, respectively.

Distance and supplemental costs are defined as invariant properties of the network model, while travel time is a dynamic property dictated by prevailing traffic conditions.

The DYNEV simulation model South Texas Project Electric Generating Station B-2 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 computes travel times on all edges in the network and DTRAD uses that information to constantly update the costs of paths.The route choice decision model in the next simulation iteration uses these updated values to adjust the route choice behavior.

This way, traffic demands are dynamically re-assigned based on time dependent conditions.

The interaction between the DTRAD traffic assignment and DYNEV II simulation models is depicted in Figure B-1. Each round of interaction is called a Traffic Assignment Session (TA session).

A TA session is composed of multiple iterations, marked as loop B in the figure.The supplemental cost is based on the "survival distribution" (a variation of the exponential distribution).The Inverse Survival Function is a "cost" term in DTRAD to represent the potential risk of travel toward the plant: Sa =- 13 In (p), 0< p <1; 13 >0 dn do dl= Distance of node, n, from the plant do =Distance from the plant where there is zero risk 13 = Scaling factor The value of d. = 15 miles, the outer distance of the shadow region. Note that the supplemental cost, Sa, of link, a, is (high, low), if its downstream node, n, is (near, far from) the power plant.South Texas Project Electric Generating Station Evacuation Time Estimate B-3 KLD Engineering, P.C.Rev. 1 Network Equilibrium In 1952, John Wardrop wrote: Under equilibrium conditions traffic arranges itself in congested networks in such a way that no individual trip-maker can reduce his path costs by switching routes.The above statement describes the "User Equilibrium" definition, also called the "Selfish Driver Equilibrium".

It is a hypothesis that represents a [hopeful]

condition that evolves over time as drivers search out alternative routes to identify those routes that minimize their respective"costs". It has been found that this "equilibrium" objective to minimize costs is largely realized by most drivers who routinely take the same trip over the same network at the same time (i.e., commuters).

Effectively, such drivers "learn" which routes are best for them over time. Thus, the traffic environment "settles down" to a near-equilibrium state.Clearly, since an emergency evacuation is a sudden, unique event, it does not constitute a long-term learning experience which can achieve an equilibrium state. Consequently, DTRAD was not designed as an equilibrium solution, but to represent drivers in a new and unfamiliar situation, who respond in a flexible manner to real-time information (either broadcast or observed) in such a way as to minimize their respective costs of travel.South Texas Project Electric Generating Station Evacuation Time Estimate B-4 KLD Engineering, P.C.Rev. 1 Start of next DTRAD Session Set To = Clock time.Archive System State at TO I Define latest Link Turn Percentages B Execute Simulation Model from time, To to T 1 (burn time)Provide DTRAD with link MOE at 1 time, T]I Execute DTRAD iteration; Get new Turn Percentages I Retrieve System State at To;Apply new Link Turn Percents I DTRAD iteration converges?

INo Yes Next iteration Simulate from T 0 to T 2 (DTA session duration)Figure B-1. Flow Diagram of Simulation-DTIRAD Interface South Texas Project Electric Generating Station Evacuation Time Estimate B-5 KLD Engineering, P.C.B-5 KLD Engineering, P.C.Rev. I APPENDIX C DYNEV Traffic Simulation Model C. DYNEV TRAFFIC SIMULATION MODEL The DYNEV traffic simulation model is a macroscopic model that, describes the operations of traffic flow, in terms of aggregate variables:

vehicles, flow rate, mean speed, volume, density, queue length, on each link, for each turn movement, during each Time Interval (simulation time step). The model generates trips from "sources" and from Entry Links and introduces them onto the analysis network at rates specified by the analyst based on the mobilization time distributions.

The model simulates the movements of all vehicles on all network links over time until the network is empty. At intervals, the model outputs Measures of Effectiveness (MOE)such as those listed in Table C-1.Model Features Include:* Explicit consideration is taken of the variation in density over the time step; an iterative procedure is employed to calculate an average density over the simulation time step for the purpose of computing a mean speed for moving vehicles.* Multiple turn movements can be serviced on one link; a separate algorithm is used to estimate the number of (fractional) lanes assigned to the vehicles performing each turn movement, based, in part, on the turn percents provided by the DTRAD model." At any point in time, traffic flow on a link is subdivided into two classifications:

queued and moving vehicles.

The number of vehicles in each classification is computed.

Vehicle spillback, stratified by turn movement for each network link, is explicitly considered and quantified.

The propagation of stopping waves from link to link is computed within each time step of the simulation.

There is no "vertical stacking" of queues on a link." Any link can accommodate "source flow" from zones via side streets and parking facilities that are not explicitly represented.

This flow represents the evacuating trips that are generated at the source.* The relation between the number of vehicles occupying the link and its storage capacity is monitored every time step for every link and for every turn movement.

If the available storage capacity on a link is exceeded by the demand for service, then the simulator applies a "metering" rate to the entering traffic from both the upstream feeders and source node to ensure that the available storage capacity is not exceeded.* A "path network" that represents the specified traffic movements from each network link is constructed by the model; this path network is utilized by the DTRAD model.* A two-way interface with DTRAD: (1) provides link travel times; (2) receives data that translates into link turn percentages." Provides MOE to animation software, EVAN* Calculates ETE statistics South Texas Project Electric Generating Station C-1 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 All traffic simulation models are data-intensive.

Table C-2 outlines the necessary input data elements.To provide an efficient framework for defining these specifications, the physical highway environment is represented as a network. The unidirectional links of the network represent roadway sections:

rural, multi-lane, urban streets or freeways.

The nodes of the network generally represent intersections or points along a section where a geometric property changes (e.g. a lane drop, change in grade or free flow speed).Figure C-1 is an example of a small network representation.

The freeway is defined by the sequence of links, (20,21), (21,22), and (22,23). Links (8001, 19) and (3, 8011) are Entry and Exit links, respectively.

An arterial extends from node 3 to node 19 and is partially subsumed within a grid network. Note that links (21,22) and (17,19) are grade-separated.

Table C-1. Selected Measures of Effectiveness Output by DYNEV II---- ------ ---- -Vehicles Discharged Vehicles Link, Network, Exit Link Speed Miles/Hours (mph) Link, Network Density Vehicles/Mile/Lane Link Level of Service LOS Link Content Vehicles Network Travel Time Vehicle-hours Network Evacuated Vehicles Vehicles Network, Exit Link Trip Travel Time Vehicle-minutes/trip Network Capacity Utilization Percent Exit Link Attraction Percent of total evacuating vehicles Exit Link Max Queue Vehicles Node, Approach Time of Max Queue Hours:minutes Node, Approach Route Statistics Length (mi); Mean Speed (mph); Travel Route Time (min)Mean Travel Time Minutes Evacuation Trips; Network C-2 KLD Engineering, P.C.South Texas Project Electric Generating Station Evacuation Time Estimate C-2 KLD Engineering, P.C.Rev. 1 Table C-2. Input Requirements for the DYNEV II Model HIGHWAY NETWORK* Links defined by upstream and downstream node numbers* Link lengths* Number of lanes (up to 6) and channelization" Turn bays (1 to 3 lanes)" Destination (exit) nodes* Network topology defined in terms of downstream nodes for each receiving link* Node Coordinates (X,Y)" Nuclear Power Plant Coordinates (X,Y)GENERATED TRAFFIC VOLUMES* On all entry links and source nodes (origins), by Time Period TRAFFIC CONTROL SPECIFICATIONS

• Traffic signals: link-specific, turn movement specific* Signal control treated as fixed time or actuated* Location of traffic control points (these are represented as actuated signals)* Stop and Yield signs" Right-turn-on-red (RTOR)" Route diversion specifications" Turn restrictions" Lane control (e.g. lane closure, movement-specific)

DRIVER'S AND OPERATIONAL CHARACTERISTICS

• Driver's (vehicle-specific) response mechanisms:

free-flow speed, discharge headway" Bus route designation.

DYNAMIC TRAFFIC ASSIGNMENT" Candidate destination nodes for each origin (optional)

• Duration of DTA sessions* Duration of simulation "burn time"* Desired number of destination nodes per origin INCIDENTS* Identify and Schedule of closed lanes" Identify and Schedule of closed links South Texas Project Electric Generating Station C-3 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 Entry, Exit Nodes are numbered 8xxx Figure C-1. Representative Analysis Network South Texas Project Electric Generating Station Evacuation Time Estimate C-4 KLD Engineering, P.C.Rev. 1 C.A Methodology C.1.1 The Fundamental Diagram It is necessary to define the fundamental diagram describing flow-density and speed-density relationships.

Rather than "settling for" a triangular representation, a more realistic representation that includes a "capacity drop", (I-R)Qm.x, at the critical density when flow conditions enter the forced flow regime, is developed and calibrated for each link. This representation, shown in Figure C-2, asserts a constant free speed up to a density, kf, and then a linear reduction in speed in the range, kf < k < kc = 45 vpm, the density at capacity.

In the flow-density plane, a quadratic relationship is prescribed in the range, kc < k < k, = 95 vpm which roughly represents the "stop-and-go" condition of severe congestion.

The value of flow rate, Qs, corresponding to ks, is approximated at 0.7 RQmax. A linear relationship between ks and kj completes the diagram shown in Figure C-2. Table C-3 is a glossary of terms.The fundamental diagram is applied to moving traffic on every link. The specified calibration values for each link are: (1) Free speed, vf ; (2) Capacity, Qmax ; (3) Critical density, kc =45 vpm ; (4) Capacity Drop Factor, R = 0.9 ; (5) Jam density, kj. Then, vc = Qmax kf = kc -, , ~kc'(VfVc)kc Setting k = k -kc, then Q = RQmax RQmax k 2 for 0 k < k, = 50 .it can be Qmax " 8333-- -shown that Q = (0.98 -0.0056 k) RQmax for k, -< k - kj, where k, = 50 and E, = 175.C.1.2 The Simulation Model The simulation model solves a sequence of "unit problems".

Each unit problem computes the movement of traffic on a link, for each specified turn movement, over a specified time interval (TI) which serves as the simulation time step for all links. Figure C-3 is a representation of the unit problem in the time-distance plane. Table C-3 is a glossary of terms that are referenced in the following description of the unit problem procedure.

South Texas Project Electric Generating Station C-5 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 Volume, vph Capacity Drop Qmax -R Qmax -Speed, Vf R vc-- Qs mph~Free: Forced: I Iy--- Density, vpm-* Density, vpm kf k Figure C-2. Fundamental Diagrams C-6 KLD Engineering, P.C.South Texas Project Electric Generating Station Evacuation Time Estimate C-6 KLD Engineering, P.C.Rev. 1 Distance Qb OQ OM OE L Mb Qe me O Down Up--o Time Ei E2 TI Figure C-3. A UNIT Problem Configuration with t, > 0 South Texas Project Electric Generating Station Evacuation Time Estimate C-7 KLD Engineering, P.C.Rev. 1 Table C-3. Glossary The maximum number of vehicles, of a particular movement, that can discharge Cap from a link within a time interval.E The number of vehicles, of a particular movement, that enter the link over the time interval.

The portion, ETI, can reach the stop-bar within the TI.The green time: cycle time ratio that services the vehicles of a particular turn movement on a link.h The mean queue discharge headway, seconds.k Density in vehicles per lane per mile.-The average density of moving vehicles of a particular movement over a TI, on a link.L The length of the link in feet.The queue length in feet of a particular movement, at the [beginning, end] of a Lb Le time interval.The number of lanes, expressed as a floating point number, allocated to service a particular movement on a link.Lv The mean effective length of a queued vehicle including the vehicle spacing, feet.M Metering factor (Multiplier):

1.The number of moving vehicles on the link, of a particular movement, that are Mb , Me moving at the [beginning, end] of the time interval.

These vehicles are assumed to be of equal spacing, over the length of link upstream of the queue.The total number of vehicles of a particular movement that are discharged from a link over a time interval.The components of the vehicles of a particular movement that are discharged from a link within a time interval:

vehicles that were Queued at the beginning of the TI; vehicles that were Moving within the link at the beginning of the TI;vehicles that Entered the link during the TI.The percentage, expressed as a fraction, of the total flow on the link that executes a particular turn movement, x.South Texas Project Electric Generating Station C-8 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 Qb, Qe The number of queued vehicles on the link, of a particular turn movement, at the[beginning, end] of the time interval.The maximum flow rate that can be serviced by a link for a particular movement Qmax in the absence of a control device. It is specified by the analyst as an estimate of link capacity, based upon a field survey, with reference to the HCM.R The factor that is applied to the capacity of a link to represent the "capacity drop" when the flow condition moves into the forced flow regime. The lower capacity at that point is equal to RQmax.RCap The remaining capacity available to service vehicles of a particular movement after that queue has been completely serviced, within a time interval, expressed as vehicles.Sx Service rate for movement x, vehicles per hour (vph).t, Vehicles of a particular turn movement that enter a link over the first t, seconds of a time interval, can reach the stop-bar (in the absence of a queue down-stream) within the same time interval.TI The time interval, in seconds, which is used as the simulation time step.v The mean speed of travel, in feet per second (fps) or miles per hour (mph), of moving vehicles on the link.VQ The mean speed of the last vehicle in a queue that discharges from the link within the TI. This speed differs from the mean speed of moving vehicles, v.W The width of the intersection in feet. This is the difference between the link length which extends from stop-bar to stop-bar and the block length.South Texas Project Electric Generating Station Evacuation Time Estimate C-9 KLD Engineering, P.C.Rev. 1 The formulation and the associated logic presented below are designed to solve the unit problem for each sweep over the network (discussed below), for each turn movement serviced on each link that comprises the evacuation network, and for each TI over the duration of the evacuation.

Given = Qb, Mb, L,TI,Eo, LN, G/C ;, LVR o L, Compute = 0, Qe, Me Define O=OQ+OM+OE

E=E 1+E 2 1. For the first sweep, s = 1, of this TI, get initial estimates of mean density, k 0 , the R -factor, Ro and entering traffic, E 0 , using the values computed for the final sweep of the prior TI.For each subsequent sweep, s > 1, calculate E = ,i Pi Oi + S where Pi , Oi are the relevant turn percentages from feeder link, i, and its total outflow (possibly metered) over this TI; S is the total source flow (possibly metered) during the current TI.Set iteration counter, n = 0, k = k0 , and E = E 0 .2. Calculate v (k) such that k < 130 using the analytical representations of the fundamental diagram.Qmnax(TI)G Calculate Cap = 60 (G/c) LN,in vehicles, this value may be reduced 3600 due to metering SetR= 1.0ifG/c<l orifk<k,;

Set R=0.9onlyifG/C=

land k>k, Calculate queue length, Lb = Qb LN 3. Calculate tj =TI -L. If t 1 <0, sett, =E 1=OE =0; Else, El =E E v TI 4. Then E 2=E-El ; t 2=TI-tj 5. If Qb Cap, then OQ= Cap,OM = OE = 0 If tj > 0,then Qe = Qb + Mb + E 1 -Cap Else Qe = Qb -Cap End if Calculate Qe and Me using Algorithm A (below)6. Else (Qb < Cap)OQ = Qb, RCap = Cap- OQ 7. If Mb __ RCap,then South Texas Project Electric Generating Station C-10 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1

8. If t, > 0 OM = Mb, OE = min RCap- Mb, t ) 0 Qe = El -OE If Q'e > 0,then Calculate Qe, Me with Algorithm A Else Qe = 0, Me = E2 End if Else (t, = 0)OM (v(T)-Lb Mb and OE = 0\ L-Lb )Me Mb -0 M + E; Qe = 0 End if 9. Else (Mb > RCap)OE = 0 If t 1 > 0, then m= RCap, Qe = Mb -OM + E 1 Calculate Qe and Me using Algorithm A 10. Else (t 1 = 0)Md = [v(TL-Lb Mb]If Md > RCap, then m= RCap Qe =Md -OM Apply Algorithm A to calculate Qe and Me Else OM = Md Me = Mb -0 M + E and Qe = 0 End if End if End if End if 11. Calculate a new estimate of average density, kn [kb + 2 km + ke], 4 where kb = density at the beginning of the TI ke = density at the end of the TI km = density at the mid-point of the TI All values of density apply only to the moving vehicles.If kn-kn--I >Eandn<N where N = max number of iterations, and E is a convergence criterion, then South Texas Project Electric Generating Station C-11 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1

12. set n = n + 1 , and return to step 2 to perform iteration, n, using k = kn*End if Computation of unit problem is now complete.

Check for excessive inflow causing spillback.

13. If Qe + Me > (L-W) LN, then L, (L-W) -LN The number of excess vehicles that cause spillback is: SB = Qe + Me L-W)-,N where W is the width of the upstream intersection.

To prevent spillback, meter the outflow from the feeder approaches and from the source flow, S, during this TI by the amount, SB. That is, set SB M = 1 -> 0 where M is the metering factor (over all movements).(E + S) -This metering factor is assigned appropriately to all feeder links and to the source flow, to be applied during the next network sweep, discussed later.Algorithm A This analysis addresses the flow environment over a TI during which moving vehicles can join a standing or discharging queue. For the case QbQ'e shown, Qb -< Cap, witht 1 > 0 and a queue of Qe length, Qe, formed by that portion of Mb and E that reaches the stop-bar within the TI, but could v + not discharge due to inadequate capacity.

That is, Mb Qb + Mb + E 1 > Cap. This queue length,/ L3 Qe = Qb + Mb + El -Cap can be extended to Qe IV by traffic entering the approach during the current-TI, traveling at speed, v, and reaching the rear of the tqueue within the TI. A portion of the entering TI vehicles, E 3 = E 131, will likely join the queue. This TI analysis calculates t 3 , Qe and Me for the input values of L, TI, v, E, t, LV, LN, Qe *When t, > 0 and Qb -Cap: Lv Define: L'e = Q'e v .From the sketch, L 3 = v(TI -t, -t 3) = L- (Qe + E 3) L e N LN Substituting E 3 = t3 E yields: -vt 3 + t E '- = L -v(TI -tj) -Le .Recognizing that TI TI LN the first two terms on the right hand side cancel, solve for t 3 to obtain: South Texas Project Electric Generating Station C-12 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 t3 Iv e- -N Lv]suchthat 0 _t 3 _TI-t 1 E ELV]If the denominator, v T- -< 0, set t 3 = TI -t.I TI LNJ , t3 Me =E (t+t 3 ,)Then, Qe = Qe + E L3 M e = E 1 1t The complete Algorithm A considers all flow scenarios; space limitation precludes its inclusion, here.C.1.3 Lane Assignment The "unit problem" is solved for each turn movement on each link. Therefore it is necessary to calculate a value, LNx, of allocated lanes for each movement, x. If in fact all lanes are specified by, say, arrows painted on the pavement, either as full lanes or as lanes within a turn bay, then the problem is fully defined. If however there remain unchannelized lanes on a link, then an analysis is undertaken to subdivide the number of these physical lanes into turn movement specific virtual lanes, LNx.C.2 Implementation C.2.1 Computational Procedure The computational procedure for this model is shown in the form of a flow diagram as Figure C-4. As discussed earlier, the simulation model processes traffic flow for each link independently over TI that the analyst specifies; it is usually 60 seconds or longer. The first step is to execute an algorithm to define the sequence in which the network links are processed so that as many links as possible are processed after their feeder links are processed, within the same network sweep. Since a general network will have many closed loops, it is not possible to guarantee that every link processed will have all of its feeder links processed earlier.The processing then continues as a succession of time steps of duration, TI, until the simulation is completed.

Within each time step, the processing performs a series of "sweeps" over all network links; this is necessary to ensure that the traffic flow is synchronous over the entire network. Specifically, the sweep ensures continuity of flow among all the network links; in the context of this model, this means that the values of E, M, and S are all defined for each link such that they represent the synchronous movement of traffic from each link to all of its outbound links. These sweeps also serve to compute the metering rates that control spillback.

Within each sweep, processing solves the "unit problem" for each turn movement on each link.With the turn movement percentages for each link provided by the DTRAD model, an algorithm South Texas Project Electric Generating Station C-13 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1

• allocates the number of lanes to each movement serviced on each link. The timing at a signal, if any, applied at the downstream end of the link, is expressed as a G/C ratio, the signal timing needed to define this ratio is an input requirement for the model. The model also has the capability of representing, with macroscopic fidelity, the actions of actuated signals responding to the time-varying competing demands on the approaches to the intersection.

The solution of the unit problem yields the values of the number of vehicles, 0, that discharge from the link over the time interval and the number of vehicles that remain on the link at the end of the time interval as stratified by queued and moving vehicles:

Qe and Me. The procedure considers each movement separately (multi-piping).

After all network links are processed for a given network sweep, the updated consistent values of entering flows, E;metering rates, M; and source flows, S are defined so as to satisfy the "no spillback" condition.

The procedure then performs the unit problem solutions for all network links during the following sweep.Experience has shown that the system converges (i.e. the values of E, M and S "settle down" for all network links) in just two sweeps if the network is entirely undersaturated or in four sweeps in the presence of extensive congestion with link spillback. (The initial sweep over each link uses the final values of E and M, of the prior TI). At the completion of the final sweep for a TI, the procedure computes and stores all measures of effectiveness for each link and turn movement for output purposes.

It then prepares for the following time interval by defining the values of Qb and Mb for the start of the next TI as being those values of Qe and Me at the end Oof the prior TI. In this manner, the simulation model processes the traffic flow over time until the end of the run. Note that there is no space-discretization other than the specification of network links.South Texas Project Electric Generating Station Evacuation Time Estimate C-14 KLD Engineering, P.C.Rev. 1 Figure C-4. Flow of Simulation Processing (See Glossary:

Table C-3)South Texas Project Electric Generating Station Evacuation Time Estimate C-15 KLD Engineering, P.C.Rev. 1 C.2.2 Interfacing with Dynamic Traffic Assignment (DTRAD)The DYNEV II system reflects NRC guidance that evacuees will seek to travel in a general direction away from the location of the hazardous event. Thus, an algorithm was developed to identify an appropriate set of destination nodes for each origin based on its location and on the expected direction of travel. This algorithm also supports the DTRAD model in dynamically varying the Trip Table (O-D matrix) over time from one DTRAD session to the next.Figure B-i depicts the interaction of the simulation model with the DTRAD model in the DYNEV II system. As indicated, DYNEV II performs a succession of DTRAD "sessions";

each such session computes the turn link percentages for each link, that remain constant for the session duration,[To , T2], specified by the analyst. The end product is the assignment of traffic volumes from each origin to paths connecting it with its destinations in such a way as to minimize the network-wide cost function.

The output of the DTRAD model is a set of updated link turn percentages which represent this assignment of traffic.As indicated in Figure B-i, the simulation model supports the DTRAD session by providing it with operational link MOE that are needed by the path choice model and included in the DTRAD cost function.

These MOE represent the operational state of the network at a time, T 1 5 T 2 , which lies within the session duration, [T 0 ,T 2] .This "burn time", T 1 -T 0 , is selected by the analyst. For each DTRAD iteration, the simulation model computes the change in network operations over this burn time using the latest set of link turn percentages computed by the DTRAD model. Upon convergence of the DTRAD iterative procedure, the simulation model accepts the latest turn percentages provided by the DTA model, returns to the origin time, T 0 , and executes until it arrives at the end of the DTRAD session duration at time, T 2 .At this time the next DTA session is launched and the whole process repeats until the end of the DYNEV II run.Additional details are presented in Appendix B.South Texas Project Electric Generating Station C-16 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 APPENDIX D Detailed Description of Study Procedure D. DETAILED DESCRIPTION OF STUDY PROCEDURE This appendix describes the activities that were performed to compute ETE. The individual steps of this effort are represented as a flow diagram in Figure D-1. Each numbered step in the description that follows corresponds to the numbered element in the flow diagram.Step 1 The first activity was to obtain EPZ boundary information and create a GIS base map. The base map extends beyond the Shadow Region which extends approximately 15 miles (radially) from the power plant location.

The base map incorporates the local roadway topology, a suitable topographic background and the EPZ and PRZ boundaries.

Step 2 2010 Census block information was obtained in GIS format. This information was used to estimate the resident population within the EPZ and Shadow Region and to define the spatial distribution and demographic characteristics of the population within the study area. Employee data were estimated from phone calls to major employers.

Transient data were obtained from local/state emergency management agencies and from phone calls to transient attractions.

Information concerning schools, within the EPZ was obtained from county and municipal sources, augmented by telephone contacts with the identified facilities.

Step 3 A kickoff meeting was conducted with major stakeholders (state and local emergency managers, on-site and off-site utility emergency managers, local and state law enforcement agencies).

The purpose of the kickoff meeting was to present an overview of the work effort, identify key agency personnel, and indicate the data requirements for the study. Specific requests for information were presented to local emergency managers.

Unique features of the study area were discussed to identify the local concerns that should be addressed by the ETE study.Step 4 Next, a physical survey of the roadway system in the study area was conducted to determine the geometric properties of the highway sections, the channelization of lanes on each section of roadway, whether there are any turn restrictions or special treatment of traffic at intersections, the type and functioning of traffic control devices, gathering signal timings for pre-timed traffic signals, and to make the necessary observations needed to estimate realistic values of roadway capacity.South Texas Project Electric Generating Station D-1 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 Step 5 A telephone survey of households within the EPZ was conducted to identify household dynamics, trip generation characteristics, and evacuation-related demographic information of the EPZ population.

This information was used to determine important study factors including the average number of evacuating vehicles used by each household, and the time required to perform pre-evacuation mobilization activities.

Step 6 A computerized representation of the physical roadway system, called a link-node analysis network, was developed using the UNITES software developed by KLD. Once the geometry of the network was completed, the network was calibrated using the information gathered during the road survey (Step 4). Estimates of highway capacity for each link and other link-specific characteristics were introduced to the network description.

Traffic signal timings were input accordingly.

The link-node analysis network was imported into a GIS map. 2010 Census data were overlaid in the map, and origin centroids where trips would be generated during the evacuation process were assigned to appropriate links.Step 7 The EPZ is subdivided into 11 PRZs. Based on wind direction and speed, Regions (groupings of PRZ) that may be advised to evacuate, were developed.

The need for evacuation can occur over a range of time-of-day, day-of-week, seasonal and weather-related conditions.

Scenarios were developed to capture the variation in evacuation demand, highway capacity and mobilization time, for different time of day, day of the week, time of year, and weather conditions.

Step 8 The input stream for the DYNEV II model, which integrates the dynamic traffic assignment and distribution model, DTRAD, with the evacuation simulation model, was created for a prototype evacuation case -the evacuation of the entire EPZ for a representative scenario.Step 9 After creating this input stream, the DYNEV II System was executed on the prototype evacuation case to compute evacuating traffic routing patterns consistent with the appropriate NRC guidelines.

DYNEV II contains an extensive suite of data diagnostics which check the completeness and consistency of the input data specified.

The analyst reviews all warning and error messages produced by the model and then corrects the database to create an input stream that properly executes to completion.

The model assigns destinations to all origin centroids consistent with a (general) radial evacuation of the EPZ and Shadow Region. The analyst may optionally supplement and/or replace these model-assigned destinations, based on professional judgment, after studying the topology of the analysis highway network. The model produces link and network-wide measures of effectiveness as well as estimates of evacuation time.South Texas Project Electric Generating Station D-2 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 Step 10 The results generated by the prototype evacuation case are critically examined.

The examination includes observing the animated graphics (using the EVAN software which operates on data produced by DYNEV II) and reviewing the statistics output by the model. This is a labor-intensive activity, requiring the direct participation of skilled engineers who possess the necessary practical experience to interpret the results and to determine the causes of any problems reflected in the results.Essentially, the approach is to identify those bottlenecks in the network that represent locations where congested conditions are pronounced and to identify the cause of this congestion.

This cause can take many forms, either as excess demand due to high rates of trip generation, improper routing, a shortfall of capacity, or as a quantitative flaw in the way the physical system was represented in the input stream. This examination leads to one of two conclusions:

• The results are satisfactory; or* The input stream must be modified accordingly.

This decision requires, of course, the application of the user's judgment and experience based upon the results obtained in previous applications of the model and a comparison of the results of the latest prototype evacuation case iteration with the previous ones. If the results are satisfactory in the opinion of the user, then the process continues with Step 13. Otherwise, proceed to Step 11.Step 11 There are many "treatments" available to the user in resolving apparent problems.

These treatments range from decisions to reroute the traffic by assigning additional evacuation destinations for one or more sources, imposing turn restrictions where they can produce significant improvements in capacity, changing the control treatment at critical intersections so as to provide improved service for one or more movements, or in prescribing specific treatments for channelizing the flow so as to expedite the movement of traffic along major roadway systems. Such "treatments" take the form of modifications to the original prototype evacuation case input stream. All treatments are designed to improve the representation of evacuation behavior.Step 12 As noted above, the changes to the input stream must be implemented to reflect the modifications undertaken in Step 11. At the completion of this activity, the process returns to Step 9 where the DYNEV II System is again executed.Step 13 Evacuation of transit-dependent evacuees and special facilities are included in the evacuation analysis.

Fixed routing for transit buses and for school buses, ambulances, and other transit vehicles are introduced into the final prototype evacuation case data set. DYNEV II generates route-specific speeds over time for use in the estimation of evacuation times for the transit South Texas Project Electric Generating Station D-3 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 dependent and special facility population groups.Step 14 The prototype evacuation case was used as the basis for generating all region and scenario-specific evacuation cases to be simulated.

This process was automated through the UNITES user interface.

For each specific case, the population to be evacuated, the trip generation distributions, the highway capacity and speeds, and other factors are adjusted to produce a customized case-specific data set.Step 15 All evacuation cases are executed using the DYNEV II System to compute ETE. Once results were available, quality control procedures were used to assure the results were consistent, dynamic routing was reasonable, and traffic congestion/bottlenecks were addressed properly.Step 16 Once vehicular evacuation results are accepted, average travel speeds for transit and special facility routes were used to compute evacuation time estimates for transit-dependent permanent residents, schools, hospitals, and other special facilities.

Step 17 The simulation results are analyzed, tabulated and graphed.documented, as required by NUREG/CR-7002.

Step 18 The results were then Following the completion of documentation activities, the ETE criteria checklist (see Appendix N) was completed.

An appropriate report reference is provided for each criterion provided in the checklist.

D-4 KLD Engineering, P.C.South Texas Project Electric Generating Station Evacuation Time Estimate D-4 KLD Engineering, P.C.Rev. 1 Step 1 Step 10 Examine Results of Prototype Evacuation Case using EVAN and DYNEV II Output i Results Satisfactory 0 T Step 11 Modify Evacuation Destinations and/or Develop Traffic Control Treatments I Step 12 Modify Database to Reflect Changes to Prototype Evacuation Case Step 13 Establish Transit and Special Facility Evacuation Routes and Update DYNEV II Database F-Step 14 Generate DYNEV II Input Streams for All Evacuation Cases I Step 15 Execute DYNEV II to Compute ETE for All Evacuation Cases Step 16 Use DYNEV II Average Speed Output to Compute ETE for Transit and Special Facility Routes Step 17 Documentation Step 18 J -Complete ETE Criteria Checklist Figure D-1. Flow Diagram of Activities D-5 KLD Engineering, P.C.South Texas Project Electric Generating Station Evacuation Time Estimate D-5 KLD Engineering, P.C.Rev. 1 APPENDIX E Special Facility Data E. SPECIAL FACILITY DATA The following tables list population information, as of November 2011, for schools, transient attractions, and major employers that are located within the STP EPZ. Transient population data is included in the tables for recreational areas and lodging facilities.

Employment data is included in the tables for major employers.

The location of the facility is defined by its straight-line distance (miles) and direction (magnetic bearing) from the center point of the plant. Maps of each school, recreational area, lodging facility, and major employer are also provided.South Texas Project Electric Generating Station Evacuation Time Estimate E-1 KLD Engineering, P.C.Rev. 1 Table E-1. Schools within the EPZ 7 I 8.5 I SE I Matagorda Elementary School I 717 Wightman St I Matagorda I (979) 863-7693 135 24 10 8.2 NW Tidehaven Middle School 2469 FM 459 I El Maton (361) 588-6600 210 24 10 J 9.1 NW Tidlehaven High School 144 FM 1095 El Maton (361) 588-6810 216 40-3/43/4 ' Ma&4~rda County.Subtotals:-, '.561 8=G~L 561 8 Table E-2. Major Employers within the EPZ 2 0.0 STP FM 521 Bay City (361) 972-3611 1,420 9.0% 1,39 2 4.3 NE White Stallion*

FM 2668 Bay City (979) 323-9367 200 9.% 195 2 4.9 NN OXEA Corporation 2001 FM 3057 Bay City (979) 241-4300 304 9.% 298 3 6.7 U.S. 60, 13 miles south of Bay I %innrldii rhamirni rith/*White Stallion represents future on site employment after construction is completed in 2015. These employees are not currently on site.South Texas Project Electric Generating Station Evacuation Time Estimate E-2 KLD Engineering, P.C.Rev. 1 0 Table E-3. Recreational Areas within the EPZ 2 4.5 NNE Bay-Cel Golf Course FM 3057 Bay City (979) 863-7861 6 3 3 3.2 E Boat Launch FM 521 Bay City (979) 863-7861 71 60 3 6.9 ESE Lighthouse RV Park 18411 Hwy 60 Bay City (979) 863-7773 90 75 6 9.2 NNE Rio Colorado Golf Course FM-2668 Riverside Pk Bay City (979) 244-2955 24 18 6 8.9 NNE Riverside Campgrounds 7330 FM 2668 Bay City (979) 245-0340 50 23 7 8.9 SE Matagorda Harbor Hwy 60, Matagorda Matagorda (979) 863-2103 157 66 7 8.5 SE Seabird RV Park Cypress Matagorda (979) 863-7229 30 20 9 6.2 W Carl Park Boat Ramp FM 521 Palacios (979) 863-7861 5 2 Matagorda Bay Nature Park &S.R. 14.3 SSE Campgrounds End of FM 2031 Matagorda (979) 557-6261 350 132 S.R. 14.3 SSE Matagorda Beach and Jetty Park End of FM 2031 Matagorda (979) 863-7861.... 1 <""Matoagord CountyS o ta/ 783 399 qToTAL: 78 399*These facilities are in the Shadow Region but would evacuate according to the county emergency plans.Table E-4. Lodging Facilities within the EPZ t7 8.7 SE Fisherman's Motel 40 Fisher St Matagorda (979) 863-0000 18 7 8.8 SE Shell Motel 1 778 Market St Matagorda (979) 863-2520 52 26 South Texas Project Electric Generating Station Evacuation Time Estimate E-3 KLD Engineering, P.C.Rev. 1 Figure E-1. Schools within the EPZ South Texas Project Electric Generating Station Evacuation Time Estimate E-4 KLD Engineering, P.C.Rev. 1 0 I Figure E-2. Major Employers within the EPZ 1(1 fl FnQinpprin~

P.C.Rev. 1 South Texas Project Electric Generating Station Evacuation Time Estimate E-5 n~ ig.PC KLD Enryineering P.C.Rev. 1 0 Figure E-3. Recreational Areas within the EPZ E-6 KLD Engineering, P.C.South Texas Project Electric Generating Station Evacuation Time Estimate E-6 KLD Engineering, P.C.Rev. 1 Figure E-4. Lodging Facilities within the EPZ Inc ; pr South Texas Project Electric Generating Station Evacuation Time Estimate E-7 Rev. 1 APPENDIX F Telephone Survey F. TELEPHONE SURVEY F.1 Introduction The development of evacuation time estimates for the Emergency Planning Zone (EPZ) of the STP requires the identification of travel patterns, car ownership and household size of the population within the EPZ. Demographic information can be obtained from Census data. The use of this data has several limitations when applied to emergency planning.

First, the Census data do not encompass the range of information needed to identify the time required for preliminary activities (mobilization) that must be undertaken prior to evacuating the area.Secondly, Census data do not contain attitudinal responses needed from the population of the EPZ and consequently may not accurately represent the anticipated behavioral characteristics of the evacuating populace.These concerns are addressed by conducting a telephone survey of a representative sample of the EPZ population.

The survey is designed to elicit information from the public concerning family demographics and estimates of response times to well defined events. The design of the survey includes a limited number of questions of the form "What would you do if ...?" and other questions regarding activities with which the respondent is familiar ("How long does it take you to ...?")South Texas Project Electric Generating Station Evacuation Time Estimate F-1 KLD Engineering, P.C.Rev. 1 F.2 Survey Instrument and Sampling Plan Attachment A presents the final survey instrument used in this study. A draft of the instrument was submitted to stakeholders for comment. Comments were received and the survey instrument was modified accordingly, prior to conducting the survey.Following the completion of the instrument, a sampling plan was developed.

A sample size of approximately 500 completed survey forms yields results with a sampling error of +4% at the 95% confidence level. The sample must be drawn from the EPZ population.

Consequently, a list of zip codes in the EPZ was developed using GIS software.

This list is shown in Table F-1. Along with each zip code, an estimate of the population and number of households in each area was determined by overlaying Census data and the EPZ boundary, again using GIS software.

The proportional number of desired completed survey interviews for each area was identified, as shown in Table F-1.Table F-1. STP EPZ Telephone Survey Sampling Plan 77414 23,596 844 9,042 282 106 338 77419 1,440 844 552 282 106 21 77440 498 463 191 190 72 8 77456 1,999 285 766 108 41 29 77457 913 695 350 335 126 14 77465 6,181 361 2,369 141 53 90 34,627 3,492 13,270 1,338 500 500 Average Household Size 2.61 Total Sample Required 500 Due to the sparse population of the zip codes within the EPZ, the area which was sampled was expanded (within the zip codes identified) so that an appropriate sample could be gathered.The over-sampling was computed in proportion to the entire zip code population.

The approach is justified on the basis that the area outside of the EPZ has similar land-use and housing characteristics as does the EPZ. We were careful to avoid sampling multi-family dwellings in the over-sample area since the EPZ does not contain these dwellings.

The completed survey adhered to the over-sampling plan.The survey discussed herein was performed in 2007 for the preparation of a COLA licensing effort. The EPZ population has increased by about 8 percent (257 people) between the 2000 and 2010 Census (see Section 3.1). In the intervening period, the nature of the EPZ has not changed. It consists primarily of ranchland and scattered housing. Consequently, the use of 2007 telephone survey results can be justified on this basis.South Texas Project Electric Generating Station F-2 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1 F.3 Survey Results The results of the survey fall into two categories.

First, the household demographics of the area can be identified.

Demographic information includes such factors as household size, automobile ownership, and automobile availability.

The distributions of the time to perform certain pre-evacuation activities are the second category of survey results. These data are processed to develop the trip generation distributions used in the evacuation modeling effort, as discussed in Section 5.A review of the survey instrument reveals that several questions have a "don't know" (DK) or"refused" entry for a response.

It is accepted practice in conducting surveys of this type to accept the answers of a respondent who offers a DK response for a few questions or who refuses to answer a few questions.

To address the issue of occasional DK/refused responses from a large sample, the practice is to assume that the distribution of these responses is the same as the underlying distribution of the positive responses.

In effect, the DK/refused responses are ignored and the distributions are based upon the positive data that is acquired.F.3.1 Household Demographic Results Household Size Figure F-1 presents the distribution of household size within the EPZ. The average household contains 2.38 people. The estimated household size (2.61 persons) used to determine the survey sample (Table F-i) was drawn from Census data. The average household size obtained from survey results is within 10% of the census value and is an indication of the reliability of the survey.South Texas Project Household Size 50%40%0 30%0 4-o 20%C10%0%1 2 3 4 5 6 Household Size 7 8 9 10+Figure F-i. Household Size in the EPZ South Texas Project Electric Generating Station Evacuation Time Estimate F-3 KLD Engineering, P.C.Rev. 1 Automobile Ownership The average number of automobiles available per household in the EPZ is 1.86. It should be noted that approximately

5.3 percent

of households do not have access to an automobile; 74 percent of households have access to one or two automobiles.

The distribution of automobile ownership is presented in Figure F-2. Figure F-3 and Figure F-4 present the automobile availability by household size. As expected, nearly all households of 2 or more people have access to at least one vehicle.South Texas Project Vehicle Availability 50%-40%0'-= 30%0 4 20%C C, 0%0 1 2 3 4 5 6 7 8 9+Number of Vehicles Figure F-2. Household Vehicle Availability South Texas Project Electric Generating Station Evacuation Time Estimate F-4 KLD Engineering, P.C.Rev. 1 Distribution of Vehicles by HH Size 1-5 Person Households 1Person M2 People 3 People *4 People a5 People 100%80%60%X 40%0 20%0%0 1 2 3 4 5 6 7 8 9+Vehicles Figure F-3. Vehicle Availability

-1 to 5 Person Households Distribution of Vehicles by HH Size 6-9+ Person Households S6 People *7 People 8 People *9+ People 100%80%60%U'0 x 40%0 20%0%1 2 3 4 5 Vehicles Figure F-4. Vehicle Availability

-6 to 9+ Person Households South Texas Project Electric Generating Station Evacuation Time Estimate F-5 KLD Engineering, P.C.Rev. 1 Commuters Figure F-5 presents the distribution of the number of commuters in each household.

Commuters are defined as household members who travel to work or college on a daily basis.The data shows an average of 0.82 commuters in each household in the EPZ. 49% of households have at least 1 commuter.

Note, however, that only those households with no access to a vehicle -26 total out of the sample size of 500 -answered this question.

Thus, the results are not statistically significant.

As such, the NRC recommendation of 50% ridesharing is used throughout this study. Figure F-5 presents this response.STP Commuters 60%50%40%4-.8 30%20%10%0%0 1 2 3 4+Number of Commuters Figure F-5. Commuters in Households in the EPZ South Texas Project Electric Generating Station Evacuation Time Estimate F-6 KLD Engineering, P.C.F-6 KLD Engineering, P.C.Rev. 1 Commuter Travel Modes Figure F-6 presents the mode of travel that commuters use on a daily basis. The vast majority of commuters use their private automobiles to travel to work. The data shows an average of 1.12 employees per vehicle, assuming 2 people per vehicle -on average -for carpools.F -STP Travel Mode to Work 95.0%100%80%.1 0)CL 60%40%20%0%2.5% 1.1%1.4%Carpool (2+)Bus Walk/Bike Drive Alone Number of Commuters Figure F-6. Modes of Travel in the EPZ F.3.2 Evacuation Response Several questions were asked to gauge the population's response to an emergency.

These are now discussed: "How many of the vehicles would your household use during an evacuation?" The response is shown in Figure F-7. On average, evacuating households would use 1.43 vehicles."Would your family await the return of other family members prior to evacuating the area?" Of the survey participants who responded, 70 percent said they would await the return of other family members before evacuating and 30 percent indicated that they would not await the return of other family members.South Texas Project Electric Generating Station Evacuation Time Estimate F-7 KLD Engineering, P.C.Rev. 1 Vehicles Used for Evacuation 100%80%60%40%L.IX 20%0%0 1 2 3 4 5 6 7 8 9+Number of Vehicles Figure F-7. Number of Vehicles Used for Evacuation F.3.3 Time Distribution Results The survey asked several questions about the amount of time it takes to perform certain pre-evacuation activities.

These activities involve actions taken by residents during the course of their day-to-day lives. Thus, the answers fall within the realm of the responder's experience.

The mobilization distributions provided below are the result of having applied the analysis described in Section 5.4.1 on the component activities of the mobilization."How long does it take the commuter to complete preparation for leaving work?" Figure F-8 presents the cumulative distribution; in all cases, the activity is completed by about 90 minutes.Eighty percent can leave within 35 minutes.South Texas Project Electric Generating Station Evacuation Time Estimate F-8 KLD Engineering, P.C.Rev. 1 Time to Prepare to Leave Work 4-.E E 0.4-0 100%80%60%40%20%0%0 20 40 60 80 Travel Time (min)100 Figure F-8. Time Required to Prepare to Leave Work/School"How long would it take the commuter to travel home?" Figure F-9 presents the work to home travel time for the EPZ. About 84 percent of commuters can arrive home within about 30 minutes of leaving work; nearly all within 90 minutes.Work to Home Travel E E 0 0 100%80%60%40%20%0%0 20 40 60 80 Travel Time (min)100 Figure F-9. Work to Home Travel Time South Texas Project Electric Generating Station Evacuation Time Estimate F-9 KLD Engineering, P.C.Rev. 1 "How long would it take the family to pack clothing, secure the house, and load the car?" Figure F-10 presents the time required to prepare for leaving on an evacuation trip. In many ways this activity mimics a family's preparation for a short holiday or weekend away from home. Hence, the responses represent the experience of the responder in performing similar activities.

The distribution shown in Figure F-10 has a long "tail." About 85 percent of households can be ready to leave home within 150 minutes; the remaining households require up to an additional 3 and a half hours.Time to Prepare to Leave Home 100%80%0-. 60%0 M 40%0 20%0% --I 0 60 120 180 240 300 360 420 Travel Time (min)Figure F-10. Time to Prepare Home for Evacuation When compared with telephone survey results obtained from surveys of EPZ residents at other nuclear sites, the STP results presented in Figure F-10 seem excessive.

Both the mean value and standard deviation of this distribution are more than double the value for any other site studied to date. A reason for this is the fact that when the STP survey was conducted (2007), the area was dealing with the after effects of Hurricane Rita which impacted the Texas Gulf Coast in 2005. Consequently, responses to this question are indicative of a level of hurricane preparation that is not relevant to a nuclear power plant evacuation scenario.

A complete discussion of these data is presented in Section 5.4.1 which discusses the topic of statistical outliers and presents a methodology for handling this issue.F.4 Conclusions The telephone survey provides valuable, relevant data associated with the EPZ population, which have been used to quantify demographics specific to the EPZ, and "mobilization time" which can influence evacuation time estimates.

South Texas Project Electric Generating Station Evacuation Time Estimate F-10 KLD Engineering, P.C.Rev. 1 ATTACHMENT A Telephone Survey Instrument South Texas Project Electric Generating Station Evacuation Time Estimate F-11 KLD Engineering, P.C.Rev. 1 Survey Instrument Hello, my name is and I'm working on a survey being made for [insert marketing firm name] designed to identify local travel patterns in your area. The information obtained will be used in a traffic engineering study and in connection with an update of the county's emergency response plans. The survey will be used for emergency plans in response to hazards that are not weather-related.

Your participation in this survey will greatly enhance the county's emergency preparedness program.COL. 1 COL. 2 COL .3 COL. 4 COL .5 Unused Unused Unused Unused Unused Sex COL. 8 1 Male 2 Female INTERVIEWER:

ASK TO SPEAK TO THE HEAD OF HOUSEHOLD OR THE SPOUSE OF THE HEAD OF HOUSEHOLD.(Terminate call if not a single-family residence)

DO NOT ASK: 1A. Record area code. To Be Determined COL. 9-11 lB. Record exchange number. To Be Determined COL. 12-14 2. What is your home Zip Code Col. 15-19 3. In total, how many cars, or other vehicles COL.20 are usually available to the household?

1 ONE (DO NOT READ ANSWERS.)

2 TWO 3 THREE 4 FOUR 5 FIVE 6 SIX 7 SEVEN 8 EIGHT 9 NINE OR MORE 0 ZERO (NONE)X REFUSED 4. How many people usually live in this household? (DO NOT READ ANSWERS.)COL. 21 1 ONE 2 TWO 3 THREE 4 FOUR 5 FIVE 6 SIX 7 SEVEN 8 EIGHT 9 NINE COL. 22 0 TEN 1 ELEVEN 2 TWELVE 3 THIRTEEN 4 FOURTEEN 5 FIFTEEN 6 SIXTEEN 7 SEVENTEEN 8 EIGHTEEN 9 NINETEEN OR MORE X REFUSED South Texas Project Electric Generating Station Evacuation Time Estimate F-12 KLD Engineering, P.C.Rev. 1

5. How many children living in this household go to local public, private, or parochial schools?(DO NOT READ ANSWERS.)COL.23 0 ZERO 1 ONE 2 TWO 3 THREE 4 FOUR 5 FIVE 6 SIX 7 SEVEN 8 EIGHT 9 NINE OR MORE X REFUSED 6. How many people in the household COL.24 SKIP TO commute to a job, or to college, 0 ZERO Q. 12 at least 4 times a week? 1 ONE Q. 7 2 TWO Q. 7 3 THREE Q. 7 4 FOUR OR MORE Q. 7 5 DON'T KNOW/REFUSED Q. 12 INTERVIEWER:

For each person identified in Question 6, ask Questions 7, 8, 9, and 10.7. Thinking about commuter #1, how does that person usually travel to work or college?(REPEAT QUESTION FOR EACH COMMUTER.)

Commuter #1 Commuter #2 Commuter #3 Commuter #4 COL.25 COL.26 COL.27 COL.28 Rail 1 1 1 1 Bus 2 2 2 2 Walk/Bicycle 3 3 3 3 Driver Car/Van 4 4 4 4 Park & Ride (Car/Rail, Xpressbus) 5 5 5 5 Driver Carpool-2 or more people 6 6 6 6 Passenger Carpool-2 or more people 7 7 7 7 Taxi 8 8 8 8 Refused 9 9 9 9 8. What is the name of the city, town or community in which Commuter #1 works or attends school? (REPEAT QUESTION FOR EACH COMMUTER.) (FILL IN ANSWER.)COMMUTER #1 COMMUTER #2 COMMUTER #3 COMMUTER #4 City/Town State City/Town State City/Town State City/Town State COL.29 COL.30 COL.31 COL.32 COL.33 COL.34 COL.35 COL.36 COL.37 COL.38 COL.39 COL.40 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 9 9 South Texas Project Electric Generating Station F-13 KLD Engineering, P.C.Evacuation Time Estimate Rev. 1

9. How long would it take Commuter #1 to travel home from work or college?(REPEAT QUESTION FOR EACH COMMUTER.) (DO NOT READ ANSWERS.)COMMUTER #1 COL.41 COL.42 1 5 MINUTES OR LESS 1 46-50 MINUTES 2 6-10 MINUTES 2 51-55 MINUTES 3 11-15 MINUTES 3 56 -1 HOUR 4 16-20 MINUTES 4 OVER 1 HOUR, BUT 5 21-25 MINUTES LESS THAN 1 HOUR 6 26-30 MINUTES 15 MINUTES 7 31-35 MINUTES 5 BETWEEN 1 HOUR 8 36-40 MINUTES 16 MINUTES AND 1 9 41-45 MINUTES HOUR 30 MINUTES 6 BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES 7 BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS 8 OVER 2 HOURS (SPECIFY )9 0 X DON'T KNOW/REFUSED COMMUTER #3 COL.45 COL.46 1 5 MINUTES OR LESS 1 46-50 MINUTES 2 6-10 MINUTES 2 51-55 MINUTES 3 11-15 MINUTES 3 56 -1 HOUR 4 16-20 MINUTES 4 OVER 1 HOUR, BUT 5 21-25 MINUTES LESS THAN 1 HOUR 6 26-30 MINUTES 15 MINUTES -7 31-35 MINUTES 5 BETWEEN 1 HOUR 8 36-40 MINUTES 16 MINUTES AND 1 9 41-45 MINUTES HOUR 30 MINUTES 6 BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES 7 BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS 8 OVER 2 HOURS (SPECIFY )COMMUTER #2 COL.43 COL.44 1 5 MINUTES OR LESS 1 46-50 MINUTES 2 6-10 MINUTES 2 51-55 MINUTES 3 11-15 MINUTES 3 56 -1 HOUR 4 16-20 MINUTES 4 OVER 1 HOUR, BUT 5 21-25 MINUTES LESS THAN 1 HOUR 6 26-30 MINUTES 15 MINUTES 7 31-35 MINUTES 5 BETWEEN 1 HOUR 8 36-40 MINUTES 16 MINUTES AND 1 9 41-45 MINUTES HOUR 30 MINUTES 6 BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES 7 BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS 8 OVER 2 HOURS (SPECIFY )9 0 X DON'T KNOW/REFUSED COMMUTER #4 COL.47 COL.48 1 5 MINUTES OR LESS 1 46-50 MINUTES 2 6-10 MINUTES 2 51-55 MINUTES 3 11-15 MINUTES 3 56 -1 HOUR 4 16-20 MINUTES 4 OVER 1 HOUR, BUT 5 21-25 MINUTES LESS THAN 1 HOUR 6 26-30 MINUTES 15 MINUTES 7 31-35 MINUTES 5 BETWEEN 1 HOUR 8 36-40 MINUTES 16 MINUTES AND 1 9 41-45 MINUTES HOUR 30 MINUTES 6 BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES 7 BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS 8 OVER 2 HOURS (SPECIFY )9 0 X 9 0 X DON'T KNOW/REFUSED DON'T KNOW/REFUSED South Texas Project Electric Generating Station Evacuation Time Estimate F-14 KLD Engineering, P.C.Rev. 1

10. Approximately how long does it take Commuter #1 to complete preparation for leaving work or college prior to starting the trip home? (REPEAT QUESTION FOR EACH COMMUTER.)(DO NOT READ ANSWERS.)COMMUTER #1 COL. 49 COL.50 1 5 MINUTES OR LESS 1 46-50 MINUTES 2 6-10 MINUTES 2 51-55 MINUTES 3 11-15 MINUTES 3 56 -1 HOUR 4 16-20 MINUTES 4 OVER 1 HOUR, BUT 5 21-25 MINUTES LESS THAN 1 HOUR 6 26-30 MINUTES 15 MINUTES 7 31-35 MINUTES 5 BETWEEN 1 HOUR 8 36-40 MINUTES 16 MINUTES AND 1 9 41-45 MINUTES HOUR 30 MINUTES 6 BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES 7 BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS B OVER 2 HOURS (SPECIFY )9 0 X DON'T KNOW/REFUSED COMMUTER #3 COL. 53 COL. 54 1 5 MINUTES OR LESS 1 46-50 MINUTES 2 6-10 MINUTES 2 51-55 MINUTES 3 11-15 MINUTES 3 56 -1 HOUR 4 16-20 MINUTES 4 OVER 1 HOUR, BUT 5 21-25 MINUTES LESS THAN 1 HOUR 6 26-30 MINUTES 15 MINUTES -7 31-35 MINUTES 5 BETWEEN 1 HOUR 8 36-40 MINUTES 16 MINUTES AND 1 9 41-45 MINUTES HOUR 30 MINUTES 6 BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES 7 BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS 8 OVER 2 HOURS (SPECIFY )9 0 X DON'T KNOW/REFUSED COMMUTER #2 COL.51 COL. 52 1 5 MINUTES OR LESS 1 46-50 MINUTES 2 6-10 MINUTES 2 51-55 MINUTES 3 11-15 MINUTES 3 56 -1 HOUR 4 16-20 MINUTES 4 OVER 1 HOUR, BUT 5 21-25 MINUTES LESS THAN 1 HOUR 6 26-30 MINUTES 15 MINUTES 7 31-35 MINUTES 5 BETWEEN 1 HOUR 8 36-40 MINUTES 16 MINUTES AND 1 9 41-45 MINUTES HOUR 30 MINUTES 6 BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES 7 BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS 8 OVER 2 HOURS (SPECIFY )9 0 X DON'T KNOW/REFUSED COMMUTER #4 COL. 55 COL. 56 1 5 MINUTES OR LESS 1 46-50 MINUTES 2 6-10 MINUTES 2 51-55 MINUTES 3 11-15 MINUTES 3 56 -1 HOUR 4 16-20 MINUTES 4 OVER 1 HOUR, BUT 5 21-25 MINUTES LESS THAN 1 HOUR 6 26-30 MINUTES 15 MINUTES 7 31-35 MINUTES 5 BETWEEN 1 HOUR 8 36-40 MINUTES 16 MINUTES AND 1 9 41-45 MINUTES HOUR 30 MINUTES 6 BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES 7 BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS 8 OVER 2 HOURS (SPECIFY )9 0 X DON'T KNOW/REFUSED

11. When the commuters are away from home, is there a vehicle at home that is available for evacuation during any emergency?

Col. 57 1 Yes 2 No 3 Don't Know/Refused South Texas Project Electric Generating Station Evacuation Time Estimate F-15 KLD Engineering, P.C.Rev. 1

12. Would you await the return of family members prior to evacuating the area?Col. 58 1 Yes 2 No 3 Don't Know/Refused

13. How many of the vehicles that are usually available to the household would your family use during an evacuation?(DO NOT READ ANSWERS.)COL. 59 1 ONE 2 TWO 3 THREE 4 FOUR 5 FIVE 6 SIX 7 SEVEN 8 EIGHT 9 NINE OR MORE 0 ZERO (NONE)X REFUSED 14. How long would it take the family to pack clothing, secure the house, load the car, and complete preparations prior to evacuating the area? (DO NOT READ ANSWERS.)COL. 60 1 LESS THAN 15 MINUTES 2 15-30 MINUTES 3 31-45 MINUTES 4 46 MINUTES -1 HOUR 5 1 HOUR TO 1 HOUR 15 MINUTES 6 1 HOUR 16 MINUTES TO 1 HOUR 30 MINUTES 7 1 HOUR 31 MINUTES TO 1 HOUR 45 MINUTES 8 1 HOUR 46 MINUTES TO 2 HOURS 9 2 HOURS TO 2 HOURS 15 MINUTES 0 2 HOURS 16 MINUTES TO 2 HOURS 30 MINUTES X 2 HOURS 31 MINUTES TO 2 HOURS 45 MINUTES Y 2 HOURS 46 MINUTES TO 3 HOURS COL. 61 1 3 HOURS 2 3 HOURS 3 3 HOURS 4 3 HOURS 5 4 HOURS 6 4 HOURS 7 4 HOURS 8 4 HOURS 9 5 HOURS 0 5 HOURS X 5 HOURS Y 5 HOURS TO 16 31 46 TO 16 31 46 TO 16 31 46 3 HOURS MINUTES MINUTES MINUTES 4 HOURS MINUTES MINUTES MINUTES 5 HOURS MINUTES MINUTES MINUTES 15 TO TO TO 15 TO TO TO 15 TO TO TO MINUTES 3 HOURS 30 MINUTES 3 HOURS 45 MINUTES 4 HOURS MINUTES 4 HOURS 30 MINUTES 4 HOURS 45 MINUTES 5 HOURS MINUTES 5 HOURS 30 MINUTES 5 HOURS 45 MINUTES 6 HOURS COL. 62 1 DON'T KNOW 15. Would you take household pets with you if you were asked to evacuate the area?Col. 58 1 Yes 2 No 3 Don't Know/Refused Thank you very much.(TELEPHONE NUMBER CALLED)If requested:

For Additional information Contact your County Emergency Management Office South Texas Project Electric Generating Station Evacuation Time Estimate F-16 KLD Engineering, P.C.Rev. 1 APPENDIX G Traffic Management Plan G. TRAFFIC MANAGEMENT PLAN NUREG/CR-7002 indicates that the existing TCPs and ACPs identified by the offsite agencies should be used in the evacuation simulation modeling.

The traffic and access control plans for the EPZ were provided by the county.These plans were reviewed and the TCPs were modeled accordingly.

G.1 Traffic Control Points As discussed in Section 9, traffic control points at intersections (which are controlled) are modeled as actuated signals. If an intersection has a pre-timed signal, stop, or yield control, and the intersection is identified as a traffic control point, the control type was changed to an actuated signal in the DYNEV II system. Table K-2 provides the control type and node number for those nodes which are controlled.

If the existing control was changed due to the point being a Traffic Control Point, the control type is indicated as "TCP" in Table K-2.Figure G-1 maps the TCPs identified in the county emergency plan. Theses TCPs would be manned during evacuation by traffic guides who would direct evacuees inr the proper direction and facilitate the flow of traffic through the intersections.

As discussed in Section 7.3, the animation of evacuation traffic conditions indicates several critical intersections which could be bottlenecks during evacuation.

These critical intersections were cross-checked with the EPZ county emergency plan. All of the intersections, except the intersection of FM 2668 and SH 60 -were not identified as TCPs in the county plan. All of the identified critical intersections are within Bay City, in the Shadow Region. However, none of the non-TCP intersections cause a backup of congestion to penetrate the EPZ. We do, however, recommend the addition of a TCP in Bay City at the intersection of SH 35 (7 th Street) and SH 60 (Avenue F). The purpose of this TCP is to manage the flow of evacuation traffic through this critical location.

As shown in Figure G-2, SH 35 and SH 60 each have two lanes heading outbound from the EPZ. It is recommended that a police officer man this intersection and prevent traffic from entering SH 60 southbound and SH 35 westbound.

G.2 Access Control Points It is assumed that ACPs will be established within 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> of the advisory to evacuate to discourage through travelers from using major through routes which traverse the EPZ. As discussed in Section 3.7, external traffic was only considered on one main route which traverses the EPZ -State Highway 35 with access from FM 616 and FM 1862 -in this analysis.

The generation of these external trips ceased at 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> after the advisory to evacuate in the simulation.

According to the county emergency plan, the access control points will be established based on natural boundaries and roads. The Emergency Management Director will receive advice and guidance from the Department of State Health Services and/or STP, regarding the areas for which access control points should be established at the time of the evacuation.

It is South Texas Project Electric Generating Station G-1 KLD Engineering, P.C.Evacuation Time Estimate Rev. I recommended that ACPs on the eastern and western boundaries of the EPZ along SH 35, FM 616, and FM 1862 be the top priority in assigning manpower and equipment as they are the major routes traversing the EPZ, which will typically carry the highest volume of through traffic.South Texas Project Electric Generating Station Evacuation Time Estimate G-2 KLD Engineering, P.C.Rev. 1 0 Figure G-1. Traffic Control Points for South Texas Project Electric Generating Station South Texas Project Electric Generating Station Evacuation Time Estimate G-3 KLD Engineering, P.C.Rev. 1 ntersection of SH 35 and SH 60 in Bay City, Texas Figure G-2. Intersection of SH 35 and SH 60 South Texas Project Electric Generating Station Evacuation Time Estimate G-4 KLD Engineering, P.C.Rev. 1 APPENDIX H Evacuation Regions H EVACUATION REGIONS This appendix presents the evacuation percentages for each Evacuation Region (Table H-i) and maps of all Evacuation Regions. The percentages presented in Table H-1 are based on the methodology discussed in assumption 5 of Section 2.2 and shown in Figure 2-1.Note the baseline ETE study assumes 20 percent of households will not comply with the shelter advisory, as per Section 2.5.2 of NUREG/CR-7002.

South Texas Project Electric Generating Station Evacuation Time Estimate H-1 KLD Engineering, P.C.Rev. 1 Table H-1. Percent of PRZ Population Evacuating for Each Region I Evacuate 2-Mile Radius and Downwind to 5 Miles I Region R04 ROS R06 R07 ROB R09 RIO RO1*Wind Direction From in Degrees: 29-50 51-106 107-140 141-174 175-230 231-286 287-331 332-28 Protective Response Zone 20% 20 20~)20% 20% 20% 209 7 8 9 10 11 6 20% 20%1 20% 20% 20%6 20% 20% 20% 20% 20%4 20% 20% 20% 20% 20%6 20% 20% 20% 20% 20%6 20% 20% 20% 20% 20%20% 20% 20% 20% 20% 20% 20% 20%20% 20% 20% 20% 20% 20% [ 20% 20%20% 20%20% 20% 120% 1 20% 20%______ J L S .5. 5 .5 Evacuate 5-Mile Radius and Downwind to the EPZ Boundary SWind Direction I Protective Response Zone Region From: 1 2 36 7ý8 91 RlII 355-5020 2%2%R12 I 51-6120 2%2%R13 I 62-9520 2%R14 96-129 R15 130-163 20% 20% 20%R16 164-174 20% 20% 20%R17 175-219 20% 20% 20% 20%R18 220-230 20% 20% 20%R19 231-286 20% 20%R20 287-298 R21 1 299-343 R22 344-354 PRZ(s) Shelter-in-Place 1 20% of population in these subareas will not comply with the shelter advisory, as per Section 2.5.2 of NUREG/CR-7002. Once 90% of the 2-mile Region has evacuated, the remaining population in these subareas will evacuate.South Texas Project Electric Generating Station Evacuation Time Estimate H-2 KLD Engineering, P.C.Rev. 1 Table H-1. Continued from above.Staged Evacuation Mile Radius Evacuates, then Evacuate Downwind to 5 Miles I Region R23 R24 R25 R26 R27 R28 R29 R30 Wind Direction Protective Respi From: 1 2 3 4 5 6 5-mile ring 20%29-50 20% 20% 20% 20%51-106 20% 20% 20%107-140 20% 20% 20% 20%141-17420 2%20 175-230 20 0 0 231-28620 20 20 287-3312020 2%20 onse Zone 7 8 1 9 10 11 20% 20% 20% 20% 20%20% 20% 20% 20% 20%20% 20% 20% 20% 20%20% 20% 20% 20% 20%20% 20% 20% 20% 20%20%20% 120% 1 20% 120%20%20% 20% 20% 20%10% 20% 20% 20%ZU7b Evacuate 2-Mile Radius and Downwind to the EPZ Boundary Region R31 R32 R33 R34 R35 R36 R37 R38 R39 R40 R41 R42 R43 R44 SWind Direction I From:1 2 l 344-5020 251-61 I 62-9520 I 96-10620 107-129 20%130-140 20%I 141-163 I 164-174 I 175-219 I 220-230 I 231-286 I 287-29820 I 299-33120 7 8 9 1 lo 1 11 2()% 2 20%20%7 8 9 '0 11 20% 20%20% 20% 20%20% 20%E20% 20%20% 20% 20%Protective Response Zone 20% 20%2% 20%20%20%120% 120%20%Notes: 1. Evacuating the 2-mile region and downwind to 5 miles with wind from 3320 to 28" both result in the evacuation of Regioni. Thus, R01 is shown twice in the table above.2. The STP site is not part of PRZ 1 but will evacuate with PRZ 1.3. Residents and Transients in the Matagorda Beach area are always evacuated.

South Texas Project Electric Generating Station Evacuation Time Estimate H-3 KLD Engineering, P.C.Rev. 1 0 I Figure H-1. Region R01 South Texas Project Electric Generating Station Evacuation Time Estimate H-4 KLD Engineering, P.C.Rev. 1 Figure H-2. Region R02 South Texas Project Electric Generating Station Evacuation Time Estimate H-5 KLD Engineering, P.C.Rev. 1 Figure H-3. Region R03 South Texas Project Electric Generating Station Evacuation Time Estimate H-6 KLD Engineering, P.C.Rev. 1 0 Figure H-4. Region R04 South Texas Project Electric Generating Station Evacuation Time Estimate H-7 KLD Engineering, P.C.Rev. 1 Figure H-5. Region R05 South Texas Project Electric Generating Station Evacuation Time Estimate H-8 KLD Engineering, P.C.Rev. 1 Figure H-6. Region R06 South Texas Project Electric Generating Station Evacuation Time Estimate H-9 KLD Engineering, P.C.Rev. 1 0 0 Figure H-7. Region R07 South Texas Project Electric Generating Station Evacuation Time Estimate H-10 KLD Engineering, P.C.Rev. I 0 Figure H-8. Region ROB South Texas Project Electric Generating Station Evacuation Time Estimate H-11 KLD Engineering, P.C.Rev. 1 Figure H-9. Region R09 South Texas Project Electric Generating Station Evacuation Time Estimate H-12 KLD Engineering, P.C.Rev. 1 0 Figure H-10. Region RIO H-13 KLD Engineering, P.C.Soutn i exas Project Electric Generating station Evacuation Time Estimate H-13 KLD Engineering, P.C Rev. I 0 0 I Figure H-11. Region Rl1 South Texas Project Electric Generating Station Evacuation Time Estimate H-14 KLD Engineering, P.C.Rev. 1 0 Figure H-12. Region R12 South Texas Project Electric Generating Station Evacuation Time Estimate H-15 KLD Engineering, P.C.Rev. 1 0 Figure H-13. Region R13 South Texas Project Electric Generating Station Evacuation Time Estimate H-16 KLD Engineering, P.C.Rev. 1 0 0 Figure H-14. Region R14 South Texas Project Electric Generating Station Evacuation Time Estimate H-17 KLD Engineering, P.C.Rev. 1 Figure H-15. Region R15 1(1 fl Fncrinpprin0 Pf~M-1~Rev. 1 South Texas Project Electric Generating Station Evacuation Time Estimate H-18 k" D Enaineerinp PC.Rev. 1 Figure H-16. Region R16 South Texas Project Electric Generating Station Evacuation Time Estimate H-19 KLD Engineering, P.C.Rev. I Figure H-17. Region R17 South Texas Project Electric Generating Station Evacuation Time Estimate H-20 KLD Engineering, P.C.Rev. 1 0 Figure H-18. Region R18 I~LU engIneerIng, r.L.South Texas Project Electric Generating Station Evacuation Time Estimate H-21 LU Engineering, PR.C.Rev. 1 0 Figure H-19. Region R19 South Texas Project Electric Generating Station Evacuation Time Estimate H-22 KLD Engineering, P.C.Rev. 1 0 Figure H-20. Region R20 South Texas Project Electric Generating Station Evacuation Time Estimate H-23 KLD Engineering, P.C.Rev. 1 0 0 Figure H-21. Region R21 South Texas Project Electric Generating Station Evacuation Time Estimate H-24 KLD Engineering, P.C.Rev. 1 0 Figure H-22. Region R22 South Texas Project Electric Generating Station Evacuation Time Estimate H-25 KLD Engineering, P.C.Rev. 1 Figure H-23. Region R23 South Texas Project Electric Generating Station Evacuation Time Estimate H-26 KLD Engineering, P.C.Rev. 1 Figure H-24. Region R24 H-27 KLD Engineering, P.C.South Texas Project Electric Generating Station Evacuation Time Estimate H-27 KLD Engineering, P.C.Rev. 1 Figure H-25. Region R25 South Texas Project Electric Generating Station Evacuation Time Estimate H-28 KLD Engineering, P.C.Rev. 1 Figure H-26. Region R26 South Texas Project Electric Generating Station Evacuation Time Estimate H-29 KLD Engineering, P.C.Rev. 1 0 0 Figure H-27. Region R27 H-30 KLD Engineering, P.C.5outn I exas Project Electric Generating Station Evacuation Time Estimate H-30 KLD Engineering, P.C.Rev. I Figure H-28. Region R28 South Texas Project Electric Generating Station Evacuation Time Estimate H-31 KLD Engineering, P.C.Rev. 1 0 0 Figure H-29. Region R29 South Texas Project Electric Generating Station Evacuation Time Estimate H-32 KLD Engineering, P.C.Rev. 1 0 0 Figure H-30. Region R30 South Texas Project Elec-tric r-V,-r=:,n C. -;Evacuation Time Estimate H-33 KLD Engineering, P.C.Rev. 1 0 Figure H-31. Region R31 D r South Texas Project Electric Generating Station Evacuation Time Estimate H-34 Rev. 1 Figure H-32. Region R32 South Texas Project Electric Generating Station Evacuation Time Estimate H-35 KLD Engineering, P.C.H-35 KLD Engineering, P.C.Rev. 1 Figure H-33. Region R33 W1 % C ; pr South Texas Project Electric Generating Station Evacuation Time Estimate H-36 Rev. 1 0 0 Figure H-34. Region R34 VI fl% C .., D p South Texas Project Electric Generating Station Evacuation Time Estimate H-37 Rev. 1 0 Figure H-35. Region R35 South Texas Project Electric Generating Station Evacuation Time Estimate H-38KLEniernPC KLD Engineering, P.C.Rev. 1 Figure H-36. Region R36 South Texas Project Electric Generating Station Evacuation Time Estimate H-39 KLD Engineering, P.C.Rev. 1 Figure H-37. Region R37 South Texas Project Electric Generating Station Evacuation Time Estimate H-40 KLD Engineering, P.C.Rev. 1 Figure H-38. Region R38 South Texas Project Electric Generating Station Evacuation Time Estimate H-41 KLD Engineering, P.C.Rev. 1 Figure H-39. Region R39 South Texas Project Electric Generating Station Evacuation Time Estimate H-42 KLD Engineering, P.C.Rev. 1 0 0 Figure H-40. Region R40 VI ft 9:n innarina P C South Texas Project Electric Generating Station Evacuation Time Estimate H-43 Rev. 1 0 Figure H-41. Region R41 VI r C: ; pr South Texas Project Electric Generating Station Evacuation Time Estimate H-44 Rev. 1 Figure H-42. Region R42 H-45 KLD Engineering, P.C.South Texas Project Electric Generating Station Evacuation Time Estimate H-45 KLD Engineering, P.C.Rev. I 0 S I Figure H-43. Region R43 r, *k T D El Evacuation Time Estimate H-46 KLD Engineering, P.C.Rev. 1 Figure H-44. Region R44 South Texas Project Electric Generating Station Evacuation Time Estimate H-47 KLD Engineering, P.C.Rev. 1