tornado missile risk analysis of spent fuel pool.' · 2019. 8. 9. · poisson arrival process...
TRANSCRIPT
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July 1979
Final Report 44T-1844
TORNADO MISSILE RISK ANALYSIS OF THE NORTH ANNANUCLEAR PCWER STATION UNITS 1 & 2 SPENT FUEL POOL
Prepared for
Virginia Electric and Power Company1 James River Plazai th and Cary Streets
Richmond, Virginia 23219
Under
Purchase Order No. 83331
Prepared By
L. A. TwisdaleW. L. CunnG. L. BilbroE. A. Cannady
798 258
c36-7903100
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July 1979
Final Report 44T-1844
TORNADO MISSILE RISK ANALYSIS OF THE NORTH ANNA
f!UCLEAR POWER STATION UNITS 1 & 2 SPENT FUEL PCOL
.
Prepared for
Virginia Electric and Power Comcany1 James River Plaza7th and Cary Streets
Richmond, Virginia 23219
Under
Purchase Order No. 38881
Prepared By
L. A. TwisdaleW. L. DunnG. L. BilbroE. A. Cannady
.
798 259
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TABLE OF CONTENTS
Page
I. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . I-1
II. METHODOLOGY .......................... II-1
A. Introduction ....................... II-1
B. Model s and Tornado Input Data . . . . . . . . . . . . . . . II-1
C. The Probabilistic Simulation Model II-4............
D. Probability Assignment II-6..................
E. Simulation Methodology II-8..................
III. PROBLEM OESCRIPTION AND SIMULATICN INPUTS III-l...........
A. Plant Definition III-l.....................
B. Postulated Missile Threat . . III-3...............
C. Tornado Hazard III-6......................
D. Simulaticn Input III-6.....................
!V. RESULTS ............................ IV-1
V. CONCLUSIONS V-1..........................
VI. REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . VI-l
APPENDIX A . . . . . . . . . . . . . . . . . . . . . . . . . . . A-1
798 i!60s,
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I. INTRODUCTION
This document is a report prepared by Research Triangle Institute (RTI)
unoer Virginia Ele,:tric and Power Company (VEPCO) Purchase Order No. 88881,
" Tornado Missile Analysis." The objective of this investigation was to
estimate the probability of tornado missile impact to the spent fuel pool of
Units 1 and 2 of the North Anna Nuclear Power Station. The scope of the study
consisted of four basic tasks: (1) acquisition of H c relevant data regarding
the plant design and missile characteristics, (2) s amalization of a plant
model with the important features of the spent fuel pool region and the
initial conditions of the postulated missiles, (3) computer simulation
analyses of the tornado missile threat to the spent fuel pool region, and (4)
compilation of the simulation results and the documentation of the findings of
the study. The information required to define the plant, structures, and
postulated missile input variables was obtained from VEPC0 and/or Stone and
Vebster Engineering Corporation. Tornado inputs were obtained from a recent
inslysis of the pertinent tornado data record with an upperbound intensity
given by the Nuclear Regulatory Commission (NRC) Region I design basis
tornado. A simulation computer code (TORMIS), developed explicitly for
tornado missile risk analysis, was used to estimate the missile impact
probabilities. The results of over 60,000 individual missile simulation
histories indicate that the probability that a single missile would impact the
pool region is 4.15 x 10-11 per year. The risk from the entire postulated
missile population is estimated as 7.65 x 10-7 per year. This report
documents the input data used in the investigation and summarizes the
methodology and results..
t-
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II. METHODOLOGY
A. Introduction
In general, the quantitative assessment of tornado missile risk requires
a mathematical model of the physical process, probability models of the
identified random variables, specification of the probability sample space,
ano a means to assign probacility measures to the points in the sample space
The models and met' odology developed by Twisdale et al. [1] for tornado
missile risk analysis cf nuclear power plants have been used in this
investigation to estimate missila impact probabilities to the spent fuel pool
for Units 1 and 2. Figure 1 illustrates the modeling and data components that
comprise the integrated risk analysis approach. Due to the complexity of the
mathematical models that describe the general tornado missile event secuence
and the relatively large numoer of random variables and requisite probability
density functions, "onte Carlo simulation is used to estimate individual event
probabilities. This secticn summarizes the components of the methodology;
detailed description of the models and previous results are given in several
reports and publications [1-6].
S. Models and Tornado Inout Data
A sequence of events must occur for a safety-related component at a
nuclear plant to be impacted and actually damaged by a tornadc-generated
missile. First of all, a tornado must occur and pass through the plant site
area. Five years of the national tornado data record (4,582 tornadoes) were
analyzed to provide input information to the risk analysis on tornado
occurrence rates and strike chara teristics [1, 4]. The investigation also
included analyses of the potential for tornado classification error based uoan
storm damage inter;:retatior.s and the lack of a damage medium (structures,
vehicles, trees, etc.) in some regions. The research also addressec the
}gg11-1
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TORNADO WINDFIELDMODELSTRIKE ANALYSIS - - - - + TORNAD0 +-----
MODELING
.
t'
I
MISSILE MISSILE+____SPECTRUM CHARACTERIZATION
'r
INJECTION _ _ _ _ # MISSILE + _ _ _ _ TRAJECTORYMETHODOLOGY TRANSPORT ANALYSIS
PLANT _ _ _ _ _ _ _ .MODELING
Y
IMPACT + _ _ __. DAMAGE CRITERIAANALYSIS AND MCDELI'!G
V
PROBABILITY _ _ _ _ + RISK + _ _ _ _ SIMULATIONMODELING ASSESSMENT METHODOLOGY
Figure 1. Components of the Tornado Missile Hazard Simulation Analysis
798 263II-2
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uncertainty in windspeed ranges and the variation of storm intensity along the
path length; a data set of 148 tornadoes was analyzed to provide quantitative
input on intensity variation. Combination of these analyses resulted in a
methodology to assess tornado strike probabilities and quantified input for
each of the Nuclear Regulatory Commission (NRC) tornado regions [7] in the
United' States.
A tornado windfield model was also developed to be compatible with the
entire range of observed windfield intensities and path widths. Tornado flow
characteristics were identified that were potentially significant in terms of
missile transport phenomena. In order to account for both modeling
uncertainty and the natural variability observed among tornadoes, several
random variables were specified in the model, including tornado intensity,
path width, translational speed, radius to maximum tangential velocity, ratio
of the radial to tangential wind speeds, vertical variation of core size, and
boundary layer thickness. In view of the difficulty in establishing a priori
conservative flow characteristics for missile transport, the windfield model
was synthesized from theoretical, observational, and probabilistic
considerations. A significant aspect of the model is that the parameters can
be adjusted to make the intensity, size, and velocity variables consistent
with the tornado path width boundary specifications.
Another component in the hazard must be the availability of objects in
the plant vicinity before any missiles can be generated. These objects must
be accelerated by the tornado winds to pose a potential threat to any of the
plant's safety systems. A missile transport model was needed that would be
efficient to permit simulation studies of thousands of trajectories and yet
describe ene e/nected variance of turbulent tornado transport. ^ random
orientation transport model was developed and statistically verified through a
II-3
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series of comparisons to both simplified three-degree-of-freedom and rigid
body six-degree-of-freedom trajectory model s. The missile injection
methodology sas developed to provide for missile release to the moving tornado
when the restraint forces are exceeded by the tornado-induced aerodynamic
forces. A simulation study was performed to determine the optimum
specification of missile restraint forces to ensure conservatisa in this
component of th: ::echanistic analysis.
Finally, if the potential missile is transported by the tornado, it must
hit a " target" or safety related system to pose an actual threat to the
operation of the plant. An impact methodology was developed for a spectrum of
missiles to provide a basis for predicting structual damage, given an impact.
Recent impact test data [8] were used in a probabilistic approach to
account for structural strength variations and random impact orientations. An
analytical study of oblique missile impact was also performed [6].
These components of the tornado missile hazard were linked together to
form an integrated model of the process as indicated in Figure 1. A total of
24 random variables were used to characterize the modeling uncertainty,
natural variability of tornado events, and the site-specific characteristics
at a particular plant. Specification of the probability models for these
variables, identification of the output sample space, and the use of
simulation techniques to assign probabilities to this sample space complete
the risk assessment methodology.
C. The Probabilistic Simulation Model
The probability model that is adopted to simulate ;ornado missile events
relies on the following hypotheses: (1) a finite and deterministic number (N)
of potential missiles exist in the plant vicinity and thus completely define -
the sampling population; (2) er.ch potential missile in the sampling population
793 265M4
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has an equally likely chance to be transported by each tornado that strikes
the plant; (3) a sequential event model for multiple missile generation is
adoptad: (4) the sample and/or event spaces for target impact are discrete;
and (5) individual missile events, including ground interaction and
termination, do not af#ect the governing sampling distributions of the
process. These hypotheses form a basis for constructing event spaces and
interpreting the resulting probability estimates from the simulations. The
detarministic restriction on ti in the first hypothesis results in considerable
simplification in the event space specification as well as in the probability
estimation and can be easily managed through conservative specification. The
second hypothesis ensures that a random sampling scheme that uses the common
missile input distributions is applicable. With respect to the first two
hypothesis, it is noted that it is not the total number of objects in the plant
vicinity but only those that have restraint forces that can be exceeded by the
tornado-induced forces. The number of potential missiles available for
transport during the actual time duration of a specific 1.ornado is
significantly less than the number of countable objects because of the
structural and storage mode restraints that limit missile ava.' lability
characteristics. The third hypothesis represents an approximat11n of the true
stochastic nature of the problem by adopting a sequential model of multiple
missile events rather that a " simultaneous" model with time history
superpositions. Hypothesis four is simply a statement of the discrete acure
of missile impact events. The final hypothesis specifies that a missile
history will not affect the sampling distributions for subsequent histories in
the same tornado event. Statistically, this suggests independence among the
missile histories in the sense that the sampling distributions remain
unchanged for a given tornado event.'
"-53g 266-
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D. Probability Assignment
The defined sampling experiment of tornado missile events specifies a
seqt.ence of individual missile trials to define the outcome of an individual
tarnado history. The developed methodology involves the' assignment of
multiple missile experimental outcomes from an analytical formulation that
uses the single missile probability estimations. In Ihe following paragraph ,
the basic analytic model for risk evaluation is given, the applicability of
the Bernoulli process and Poisun trials model is examined, and an analytical
model for multiple missiles is presented.
The basic tornado arrival process model for tornado missile risk
assessment is adopted from Wen and Chu's work [9] and can be expressed as
P(A) = 1 - exp[-v E(A)T] = v E(A)T, (1)
where P(A) = probability that event A occurs at least once during the time
period (T), v = tornado occurrence rate, and E(A) = an expectation over the
random variables defining event A for a single tornado. This expression is
the exact analytical expression for tornadoes that are characterized by a
Poisson arrival process and a union concept of success for event A. For rare
events, the approximation in Equation 1 is accurate to within 0.5 percent for
vE( A)T j 0.01. Consistent with the discrete nature of the tornado FPP (Fujita
intensity, Pearson path length, Pearean path width) classification system
[e.g.,10], E(A) is evoluated by its equivalent form
Ft
E(A) = [ E(AjI)P(I), (2)I=0
where I denotes the F-scale classification and F: the upperbound tornado
intensity.
II-6 .
798 267
*.
For the assumed sequence of N missiles generated during a tornado strike,
(Ij), the probability of target damage can be formulated analytically from the
single trial probability, P( AlIj). The probability of the event that target A
is damaged by at least one of the N missiles in the sampling population during
the jth tornado F-scale intensity I is denoted as P ( A|Ij). A conservativeN
union (U) concept of damagt. 'uccess being adopted, this probability is
NP (A|Ij) = P[(A |Ij) U ( A |Ij) U ... U (A IIj)], (3)1 2 N
where Aj denotes the event that A is damaged by missile i. If mutua!
independence is assumed among the Aj, then Equation 3 can be stated
equivalently as
N NNP (A|Ij) = 1 - H P(7j | Ij ) = 1 - 2 [1 - P(Aj lIj)], (4)
i=1 i=1
where lj denotes the complement of event A . This assumption of mutuali
independence means that the missile trials are repeated under identical
conditions for the assumed tornado; i .e. , the ith trial alone determines
whether or not Aj occurs. If the missiles are treated as being
indistinguishable (nonordered) in the sampling experiement in terms of event
A, then P( Aj |Ij) is replaced by P(A|Ij) and
P ( Aj Ij) = 1 - [1 - P( A|Ij)] N. (5)N
This familiar expression provides a basis for assigning multiple missile event
likelihoods during a specific tornado event (Ij) with an estimate of P( AjI )j
from the sequential sampling experiment.
Examination of Equation 5 suggests that this expression is identical to
the extensively studied Bernoulli process. It is noted that the expected
number of successes during tornado i on a single target " A" is N.P( Aj !j), and
II-7
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the variance is N P(A|Ij)[1 - P(A|Ij)]. Correspondingly, Equation 4 is the
analogous statement for Bernoulli trials with variable probabilities, i.e.,
Poisson trials [11]. The significance of the assumption of indistinguishable
missiles has been evaluated by comparing features of Poi'sson trials to
Bernoulli trials. It can be shown [cf.1] that the Bernoulli model provides a
conservative estimate of the variance and an estimate of the expected value
that is within a few percent of that obtained from the more general Poisson
trials model. Thus, the simplification provided by Equation 5 is used to.
assign multiple missile probabilities.
E. Simulation Methodolocy
Probabiliscic Monte Carlo simulation [e.g.,12,13] is used to estimate
the missile event probabilities--e.g., P( A|Ij)--because of the complex and
multidimensional form of the random process. The TORMIS simulation code has
been developed to produce numerical estimators of both single and multiple
missile event probabilities. The output consists of statistically independent
outcomes, each of which follows the same probability law. The expected value
and variance are the population descriptors evaluated explicitly in the TORMIS
code. For a mathematical statement of the tornado missile simulation, it is
convenient to introcuce the functions g(x|$) and h($) to represent the~
complete stochastic process. The random process for the tornado definition
andoccurrenceisdefinedbyh(I),where$isavectoroftornadorandom~
variables. The function g(x|$) denotes the tornado missile random process in'
which x is a vector of missile random variables. Thus, the complete
stochastic process is given by the product g(x|$)h($); the notation for an~
outcomeisg($j|kj)h(kj),whereX i denotes the i th vector of tornado variables~
sampled frcm f(x). For a single missile history, the outcome relative to some
defined event A is a random variable "a." This outcome being denoted as
"-8798 269
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gA(kj |5j)h ( j), the characteristics of the probability law of "a" can beA
inferred frcm n independent observations. The expected value of "a" is
estimated by
1 m _ 1 n _ _
E(a|I) = - )m j =,1 h(Zj)nj.). 9A(Xj|Zj), (6)A
1
where n = m n. For the Bernoulli trial model, the probability of success of A^
is given by this expectation, an,! hence P(A) = E(a) and P(A) = ^E(a). The
estimate of '( A|Ij) is given by the right summation in Equation 6. It is
noted that for single missile events the es*.imation of P(A|I) is not dependent
upon the division of m and n for large n, pro 'ided that a reasonable number
(m) of tornadoes is considered and n is sufficiently large. However, for
multiple missile events, n must be large enou!5 to provide an estimate of
P( A|Ij), which can be used in the analytical expressions derived previously.
Tr us, the estimation accuracy of P(A|Ij) is useful; the sampla variance,
2(a|Ij and the variance of P(A|Ij) follow the standard forms [1]. In the
TORMIS code, confidence bounds are calculated assuming normality, which has
been shown '.o give accurate results compared to a modified binomial sampling
procedure [1].
.
798 270u-9 -
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III. PROBLEM DESCRIPTION AND SIMULATION INPUTS
A. Plant Definition
The spent fuel pool for Units 1 and 2 is located within the fuel
building, which is directly between Containments 1 and 2 and south of the
auxiliary, service, and turbine buildings. To simulate the tornado missile
threat to the spent fuel storage area, the structures shown in Figure 2 were
modeled as a cluster of 13 targets. The interior of the pool itself was
modeled as two separa e targets (Numbers 7 and 8). Target 7 represents the
interior of the pool, from the top of the pool to a point 6 feet abcVe the
elevation of the top of the spent fuel assemblies. Target 8 covers the area
from 6 feet above the location of the fuel assemblies to the bottom of the
pool at elevation 249 feet 4 inches. This targeting arrangement was devised
to provide the most information about potential impacts within the pool.
Impacts to Target 7, which was modeled with no top or bottom surfaces,
represent actual hits to the interior walls of the pool. Impacts to Target S
represent hits to the fuel assemblies or to pool walls just above the fuel
assemblies. The probability of missiles entering the top portion of the pool
is thus the addition of the individua' probabilities for Targets 7 and 8. The
fluid within the pool was ignored in the trajectory analyses, and thus the
predicted missile impact veloctities are higher than those that would actually
occur because of the increased drag resistance provided by the water.
Targets 3, 4, 5, and 6 include the exterior pool walls and the remaining
per-ic' of the fuel building. The portion of the fuel building above the
elevation of the top of the pool (elevation 291 feet 10 inches) was not
considered to provide any significant missile protection to the pool and hence
was not modeled in the analysis. The remaining targets include the
containment structures, the auxiliary, service, and turbine buildings, and the
798 Nm-1 -
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11
Turbine Building
10
Service Building
Auxili ary
9
4 BuildingN
Containment 3 6 Conta nment
5
" "9 % Primary GradeWater Storage Tanks
(a) Target Plan View
Lecend
@ Spent Fuel Pool1,...,13 Target Numbers
Scale 1"=100'2
'150
::
100 :0
3 1 2
50 -
: 11 mun: 10 33 12
'
13 'ffg { p,q,w <<winwmwrw -w w e
NSpent Fuel Grade E1.270'Assemblies
(b) South Elevation View
798 272Figure 2. Plan and Elevation Views of Plant Targets
III-2
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primary grade water storage tanks. The auxiliary, service, and turbine
build ngs were modeled up to elevations that would continue to provide missile
protection during the design basis tornado. Other structures, components,
etc., in the region of the spent fuel pool were not explicitly modeled in this
study. Hence, only the major " shadows" were modeled, and the shadowing
effects of other structures, such as those of the waste disposal building, are
conservatively ignored in the missile simulations.
B. Postulated Missile Threat
The missile threat that was postulated for the spent fuel pool included
buildings, loose objects, construction materials, and other sources over the
entire plant and construction site area. As noted in Figure 3, a total of 17
areas were used to identify different missile origin zones. The zones include
storage and laydown areas, parking, Units 3 and 4 construction area, the
switchyard, and wooded regions. These areas include the contiguous land
region around the plant and thus all possible missile origins within 2,000
feet of the actual spint fuel pool target. A previous investigation indicatea
that missiles rareij travel more than 2,C00 feet and hence do not contributa
significantly to the impact risk for targets that are located more than 2,000
feet frcm the missile source. Simulation of missile trajectories and field
observations suggest that the greatest hazard is from missiles that originate
within several hundre.d feet of the target.
The number of each of the itandard missile types [14] postulated by zone
is summarized in Table I. A total of 19,995 potential missiles were specified
to simulate the availability of missile sources during the period of on-site
construction activities for Units 3 and 4. Upon completion of these units,
the number of potential on-site missiles will diminish, and thus this time
period is expected to reoresent the worst case in terms of the tornado missile
III-3
798 273
Y
2500
14
N2000 Pipe Laythwei Aira
21*
'? 13 15
I d Y '*" A' edd1500
Pasking11
WoodedArea
"$witthyard
16
500 Construt.tlon IUnits 3 & 4 L! nits 1 & 2 p,,gggg
10
*-*Woode<l Area
g . . * * ' ' ' : x. 500 1000 2000 oo 5000gy
2
500 Emi>ank nin t
9 7 5 4
Parking Storagekrh Wh PelStorage Area Area
10008
-
Storage 6Area
Discharge Canaland Wooded Area
-15005torage Arca
-~~.Y,.c
00 2000
N __
4# Figure 3. tiissile Origin Zone Definit. ion
TABLE I. MISSILE SPECIFIC UION BY ZOI:E
NumDer of Missiles by Tyce TotalP1 ant Number
Zone Wood 6" 1" Utility 12" Automobile OfNumber Beam Pice Rod Pole Pice Missiles
1 10 10 10 5 10 5 50
2 100 100 100 5 100 5 410
3 1,000 1,000 1,000 500 1,000 100 4,600
4 0 0 0 0 0 5 5
5 50 0 0 30 0 50 320
6 1,000 1,000 1,000 500 1,000 100 130
7 0 0 0 20 0 300 4,600
8 100 50 50 10 50 10 320
9 500 250 250 50 250 50 1,350
10 100 0 0 10 0 50 160
11 0 500 100 0 500 5 1,105
12 0 0 0 0 0 0 0
13 100 100 0 0 100 25 325
14 1,000 1,000 1,000 500 1,000 100 4,500
15 0 0 0 80 0 1,200 1,230
16 0 50 0 40 0 600 690
17 0 0 0 100 0 0 100
Total 3,960 4,060 3,510 1,850 4,010 2,605 19,995
* Zone 12 is a wooded area that is more than 2,000 feet frcm the spentfuel pool target.
III-5
]9b
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threat. These missiles were specified to originate at heights that follow the
land topography, building, and material laydown storage heights. The zone
elevation and maximum injection heights are given in Table II. The minimum
injection height was conservatively considered to be five feet above the zone
grade elevation. The missiles were uniformly injected over the interval
defined by these minimum and maximum heights, incorporating the differences in
zone elevations. The automobile was injected at a constant height of five
feet above grade for all zones.
C. Tornado Hazard
The input data for the tornado hazard definition was taken from an
analysis of 4,582 tornado data entries reported in the 1971-1975 FPP data base
[1]. Specifically, the data for NRC tornado Region I was used in the
specification of tornado intensity, path width, path length, and tornado
direction. The design basis tornado with a windspeed of 360 mph [7] was used
as the maximum intensity event. Thus, as noted in Table III, the F'6 tornado
intensities were specified to have a windspeed interval of from 277 to 366 mph
and an occurrence rate of 2.152 x 10-7 per square mile per year. A review of
the 1971-1975 data for the State of Virginia confirmed the conservatism of
using Region I tornado statistics in the tornado hazard simulation. The
angular difference of 21 degrees clockwise between plant north and true north
was also accounted for in the directional tornado data input relative to the
plant target model and missile zone geometry.
D. Simulation Incuts
Appendix A includes an actual computer printout of all of the input data
for the simulation of a given tornado intensity interval. Tne input data were
checked against the problem description defined in this chapter to insure the
validity of the results.
III-6 b
TABLE II. MISSILE INJECTION HEIGHT BY ZONE
Maximum Injection Height Above Grade (ft) by Missile TypePlant GradeZone Elevation Wood 6" l' Utility 12" AutomobileNumcer (ft) Beam Pice Rod Pole Pice
1 270 30 30 30 5 30 5
2 270 20 20 20 20 20 5
3 270 50 50 50 20 50 5
4 320 5- - - - -
5 320 2 20 - 5- -
6 320 3 30 30 30 30 5
7 320 - - - 5 - 5
8 320 2 20 20 20 20 5
9 320 2 20 20 20 20 5
10 300 2 - - 20 5-
11 270 40 40 - 40 5-
12 270 - - - - -
13 270 5 5 5 5- -
14 270 5 5 5 5 5 5
15 270 - - - 5 - 5
16 270 20 - 20 - 5-
17 270 - - - 20 - -
t "-7
79g 277
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TABLE III. TOR! LAD 0 ItiTENSITY INTERVALS A!iD OCCURREtiCE RATES
Tornado Intensity Windspeed Interval Occurrence Rate(F'-Scale) (moh) (/sc. mi. yr.)
F'O 40-73 2.206x10-4
F'1 73-103 1.207x10-4
F'2 103-135 6.413x10-5
F'3 135-168 1.941x10-5
F'4 168-209 4.390x10-6
F'S 209-277 9.469x10-7
F'6 277-360 2.152x10-7
AlI 40-360 4.304x10-4
jgg 278t "-8
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IV. RESULTS
Missile impact probabilities to the spent fuel pool targets were
estimated with the methodologv developed for the TORMIS computer code and the
specified input data. Ten thousand missile time histories were simulated for
tornado events within each tornado intensity interval. A total of 60,000
histories were recorded for F1 through F6 intensity tornadees. The tornado
charactistics or direction, path length, path width, translational windspeed
component, etc., were sampled from the defined frequency distributions for
each tornado event simulated. Missiles were selected from each of the types
specified and positioned within the zones for possible injection and transport
by the tornado. Missiles that impacted the structures were scored and the
target impact probabilities generated. The predicted impact probabilities for
the spent fuel targets (Numbers 7 and 8) are presented in Table IV for each
tornado intensity. The 95 percent confidence bounds are also given to
indicate the degree of statistical uncertainty in the simulation output, as
indicated in the example computer printout in Appendix A.
The results summarized in Table IV indicate that the probability of a
single tornade-generated missile, picked at andom frcm the entire missile
population, entering che spent fuel pool is estimated to be 4.15 x 10-11 per
year. The majority (95 percent) of this risk is due to impacts to the upper
portion of the interior wall the pool, as defined by Target 7. The model
predicts that the likelihood of a direct hit to Target 8 (the scent fuel
assemblies and the portion of the interior pool walls extending six feet abcve
the top of the assemblies) is 2.37 x 10-12 per year.
Multiple missile probabilities, as defined mathematically in Section
II.D, are also given in Table IV. Since there is : ore than one potent.al
missile at the plant, these probabilities are simply the total rid from all
pgIV-1
.
TABLE IV. PHEGICILO liiPACT PROBAh!LITIES Afl0 % PERClitT STATISTICAL C0flFIDEtlCL BOUllDS
Tornado Single flissile fiultiple liissile
(F'-Scole) flumber (1) Limit (2) Limit (2) Limit (2) Upper (2)Intensity Tar 9et Lower fican Upper Lower fleanLimit
1 7 0 1.12x10_13 2.46x10-13 0 1,73x10-9 4,12x10-98 2.07x10-16 S,79x10-15 1,14 x10-14 0 3.65x10-Il 1.06x10 .0
7 or 8 0 1.18x10-13 2.Six10-13 0 1,79xio-9 4,17x10-9
2 7 0 3.21x10-ll 9.llx10-Il 0 5.84x10-7 1.66xiU-68 0 2.59x10-13 7.13x10-13 0 3.74x10-9 1.09x10-'
7 or 8 0 3.24x10-Il 9.14x10-Il 0 5.89x10-7 1.66x10-6
3 7 0 5.52x10-12 1.28x10-Il 0 1.06x10-7 2.46x10-78 0 7.05x10-13 2.05x10-12 0 1.28x10-8 3.71x10-8
7 or 8 0 6.23x10-12 1.36x10-Il 0 1.19x10-7 2.6Sx10-7
4 7 1.02x10-13 9.76x10-13 1.85x10-12 1,44x10-9 1.85x10-8 3.SSx10-88 0 1.0lx10-12 2.93x10-12 0 1.93x10-8 S.61x10-8-
7 7 or 8 0 1.99x10-12 4,10x10-12 0 3.78x10-8 7.82x10-8'
5 7 2.48x10-14 4.12x10-13 7,99x10-13 4.27x10-10 7.9 x10-9 1.54x10-88 0 3.90x10-13 9.28x10-13 0 7.57x10-9 1.80x10-8
7 or 8 1.39x10-13 8.02x10-13 1,47xio-12 1,oixto-9 1.55x10-8 2.92x10-8
6 7 0 7.41x10-14 1.86x10-13 0 1.37x10-9 3.44x01-98 *(3) *
7 or 8 0 7.41x10-14 1.86x10-13 0 1.37x10-9 3.44x10-9
All 7 1.48x10-Il 3.91x10-Il 6. 34 x10-I l 2.77x10-7 7.20x10-7 1.16x10-68 1.37x10-12 2.37x10-12 3.37x10-12 2.47x10-8 4.34x10-8 6.21x10-8
7 or 8 1.72x10-Il 4.15x10-Il 6.58x10-Il 3.22x10-7 7.6Sx10-7 1.21x10-6
-.
flotes: (1) Target 7 = Spent fuel pool volume above fuel assemblies.-.,
Target 8 = Spent f uel pool volume containing fuel assemblies up to a point 6'~i above the top of spent fuel4 7 or 8 = Impact to either region defined by target 7 or target 8O (2) Upper and lower limits of the 95% statistical confidence bounds
(3) indicates that no hits were obtained to Llie to get far tiie specified tornado*
intensity
CDcD
.
the potential missiles specified in the missile threat definition. The event
is not based upon the assumption that only one missile is generated per
tcrnado, but that the entire population of potential missiles may be generatea
for any tornato event. The term multiole missile is also interpreted to mean
that all of the missiles have restraining forces that are specified within an
optimum interval for transport and thus are potentially transported by any
tornado that strikes the plant. Thus, the multiple missile risk provides a
conservative estimate of tornado-generated missile impact probabilities. For
multiple missile generation for each tornado event, the respective probability
estimates are 7.65 x 10-7 per year for missiles entering the pool and 4.34 x
10-8 per year for missiles hitting near the fuel assemblies (as specified by
Target 8). The 95 percent confidence bounds for these results are relatively
t. lose to the predicted mean values, indicating that a sufficient number of
simulations were made to minimize the statistical uncertainty of the
outcomes.
An examination of these results indicates that the simulation model
predicted event likelihoods that closely follow expected missile occurrences.
In the first place, the pool offers a very limited target as illustrated in
Figure 1; it is shadowed, or partially shadowed, from practically every
direction by adjacent structures. The missiles must avoid these targets and
at the same time be lifted to a height of at least 20 feet above the plant
grade elevation. If a missile, by chance, is transported into the region
above the pool, its trajectory must fall quickly, or else it will be carried
over the pool and into another target or a ground impact. Inspection of the
simulation results indicates that these types of outcomes occured more
frequently than the event of a missile trajectory intersecting the pool. Fo r
example, the single missile hit probability to the outside scuth wall of the
g
pool (Target 5) is more than 10 times likely than a hit to the pool it Li f
(4.61 x 10-10 vs 4.15 x 10-11). None of these predicted hits to the outside
wall produced damage to the massive 6-foot-thick, reir. forced concrete barrier.
Table IV also indicates the contribution by tornado intesity to the
overall risk. The maximum intensity tornado events (F'6) produced no hits to
Target 8, althouth it produced the most hits to the adjacent targets. For
these high intensity tornadoes, all of the hits to the pool occurred to the
interior walls within eight feet of the top of the pool. The speeds of the
missiles were higher, and thus they did not drop sufficiently during the time
interval they were over the pool to result in a direct hit to Target 8. The
hit probability for both Targets 7 and 8 peaked at the strong intensity
tornadoes (F'2 or F'3) as opposed to weak intensity tornadoes (F'O or F'1) or
violent storms (>F'4). F'O intensity tornadoes were not simulated because of
the noted reduction in risk contribution for the F'1 intensity.
In addition to the estimation of missile impact risk, the TOR.'i!S code is
alse capable of estimating damage to a target given missile impact. To
provide some indication of the like19aod of damage to the fuel assemblies
under hypothetical conditions, Target 8 was assumed to have a one-quarter-
inch steel plate element on its top surface. If oblique angles of entry and
the presence of the fuel rack structures are considered, this case may .orovide
a lower limit to the range of fuel usembly damage probability. The
predicted damage (plate pcrforation) probabilities for missiles entering the
pool and directly hitting Target 8 were 1.35 x 10-13 per year from a single
missile and 2.58 x 10-9 per year for all the raissiles combined. These
probabilities are each more than an order of magnitude less than the predicted
impact probabilities and, furtner, do not include the effect of the fluid drag
IV-4 -
798 282
.
provided by the 24 feet of water above the assemblies. Tornadoes with
intensities of F'3 or less did not contribute any to this actual damage risk.
An analysis of the impact risk cor.tribution by missile type to Target 8
provides further information regarding this difference i.n impact risk and
actual damage risk. The simulation outcomes for all the tornadoes indicate
that 82 percent of the impact risk to Target 8 was from the wood ber.m missile
(4 inches by 12 inches by 12 feet) with a total weight of only 115 lbs. The
6-inch steel pipe contributed 16 percent of the risk; the 1-inch steel rod
contributed 1 percent; and the utility pole,12-ir sa pipe, and vehicle
contributed less than 1 percent combined. Thus, the order of magnitude
reduction in the predicted impact risk versus the damage risk is partially due
to the fact that many of the predicted impacts involve one of the lighter
missiles that has a relatively weak damage potential.
n-s 798 283
V. CONCLUSIONS
On the basis of this investigation, the following conclusions are made
regarding the likelihoods of missile impact events in the spent fuel pool for
Units 1 and 2:
(1) J4issiles Entering tha Pool - Th.. mean probability of atornado-generated missile entering the spent fuel pool for Units 1and 2 is estimated as 4.15 x 10-11 per year. For the entirepopulation of postulated missiles, the combined probability of atleast one tornado-generestimated as 7.65 x 10 gted missile entering the spent fuel pool is' per year.
(2) Missiles Directly Hitting the Assemblies - The mean probability of atornado-generated mis;ile entering the :: pent fuel pool and directlyhitting the spent fuel assemblies (or the interior pool wall justabove the top of the assemblies) is estimated as 2.37 x 10-12 peryear. For the entire population of postulated missiles, theccabined probability of at least one tornado-generated misgiledirectly hitting the assemblies is estimated as 4.34 x 10-oper year.
(3) Missiles Damaging the Assemblies - A hypothetical lower-limitestimate of the prooability of a tornado-generated missile enteringthe pogl and damaging the spent fuel assemblies is estimated as 1.34x 10-14 per year. For the entire population of postulated missiles,the combined probability of at least one tornado-ggnerated missiledamaging the assemblies is estimated as 2.58 x 10-9 per year.
The results indicate that the probability of tornado-generated missile damage
is less than the 10-7 per year risk criterion specified in the Standard
Review Plan [14] for missiles generated by natural phenomena. In addition,
the conservatisms in the analysis, coupled with the tightness of the predicted
statistical confidence bounds, suggest that the actual risk is likely to be
less than the lower bound of the predicted risk.
~
hkV-1 g
-.
VI. REFERENCES
1. Twisdale, L. A. et al. , " Tornado Missile Risk Analysis," EPRI NP-768(Vol. I) and EPRI NP-769 (Vol. II), Electric Power Research Institute,Palo Alto, California, May 1978.
2. Twisdale, L. A., W.L. Dunn, and T.L. Davis, " Tornado Missile TransportAnalysis," Journal of Nuclear Engineering & Design, 51 (1979).
3. Dunn, W.L. and L. A. Twisdale,'" A Synthesized Windfield Model for Tornado~
Missile Transport," Journal of Nuclear Engineering & Design, 52 (1979).
4. Twisdale, L. A., " Tornado Data Characterization and Windspeed Risk,"Journal of the Structural Division, ASCE, Vol.104, No. ST10, October,s1978.
5. Twisdale, L. A. , " A Risk-Based Desiga Against Tornado Missiles,"Proceedings of the Third ASCE Specialty Conference on Structural Designof Nuclear Plant Facilities, Boston, Mass., April 1979.
6. Twisdale, L. A., "Probabilistic Considerations in Missile ImpactAssessment," Proceeding of the International Seminar on ProbabilisticDesign of Nuclear Power Plants, San Fransisco, Calif , August 1977.
7. Nuclear Regulatory Commission, " Design Basis Tornado for Nuclear PowerPlants," Regulatory Guide 1.76, April 1974.
8. Stephenson, A.E. , " Full-Scale Tornado -Missile Impact Tests," NP-440,Electric Power Research Institute, Palo Alto, California, July,1977.
9. Wen, Y.K. , and Chu, S.L. , " Tornado Risks and Design Wind Speed," Journalof the Structural Division, Proceedings ASCE, Volume 99, No. ST12,December 1973.
10. Fujita, T.T., " Proposed Characterization of Tornadoes and Hurricanes byArea and Intensity," The University of Chicago, SMRP Research Paper No.91, February 1971.
11. Feller, W. , An Introduction to Probability Theory and Its Acolications,Volume I, 3rd Edition, John Wiley & Sons, Inc., New Your,1968.
12. Fishman, G.S.. oncepts and Methods in Discrete Event Digital Simulation,John Wiley & Sons, New York,1973.
13. McGrath, E.J. , Basin, S.L. , Barton, R.W. , Erving, D.C. , Jaquette, S.C. ,and Ketler, W.R., et al., Technioues for Efficient Monte CarloSimulation, CRML-PSIC-38, Volumes 1, 2, 3, April 1975.
14. Nuclear Regulatory Commission. " Missiles Generated by Natural Phencmena,"3ection 3.5.1.4, Standard Review Plan, Revision 1, November,1975.
VI-1e
APPENDIX A
TORMIS Input and Output Sample
The input and a portion of the output of the computer simulation is given
in this appendix for the computer simuiation of F'S tornadoes. Table A-1
illustrates the data input requirements for the TORMIS code. In Table A-2 the
output summary by target number and impact event is presented. The four
impact events that the code analy2.es are as follows:
(1) Missile impact or a hit to the target.
(2) Missile impact with velocity greater than a specified value.
(3) Damage evaluation for specified target properties.
(4) Damage evaluation for a second set of target properties.
The output summary also includes estimates of missile impact and damage to
combinations of targets. The notation "7 S UN" in Table A-2 represents the
union of Targets 7 and 8 and hence the combined probaMiities for each target.
The notation "7 8 IN" represents the interesection of both targets and hence
the probability that both targets are impacted in the same tornado event.
A-1
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A-4
TABLE A-1. lilPUT DATA FOR F'5 sit 1ULAT10ft (Continued)
116, YT D , Zl (I) , W I, W Y , W 3 0. 2 0 6 Plo t C4 0.1240CJE 03 0.0 0.05C,00E 01 0.t.35000E 02 0. 2 4 0 '10 0 E 12
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118 , TT H ,2C (I) , W E , W r , W Z 0.3027001 04 -0. 9175 0 0 t 02 0.0 0.15J130E 02 0.0 0.390000E 02_
'1 All NUNSHF RT 84 T IC TC IC 1TPTAH LAP THETA,
1 3 70. 140. 2664 C. O. 1 3 3.0- 2 -3~~ 70.- 14 0. -~ ~ 31 17. ' --- - --- ' 0 . - ' O .- - ~~3 - 3- 0.0
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6 6 40. 22. 108: 1. - 1 1. O. 1 H 0.0.
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9 6 79. 22, 3000. 66. C. I B 0.010 6 331. 24. 2995. 15 8. O. 1 12 0.011 ' - 5 ' -- 2 7 9. 5 0.--- - 10 0 0 ; - ----'7 6 0 ; - --'C. 1 - ~ 1 C 0 . 0 - - - - - -~~- -- " - ~ - - - - - -
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12 3 25. 59 2980. -94. C. 4 2 0.0
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1 2 2 5 0 60. O. O. O. 72. 140. 4000. 72. 12.,
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2 1 4 4 0 60. O. O. O. O. 72. 4000. 72. 72. ',,'2 2 5 5 0 60. O. O. O. 72. 140. 4000. 72. 72.,
--- 2 T -- 6 --- ~ 0 - 11069 ;120 0~- 6 0.'- 68. O. ~0. 4000.-- '0 F ~0. ..,,
I 1 7 1 02932.2932. - 14. 7. O. 22. 4000. 12. 12. *
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1 4 10 2 02912.295). 7. 7. O. 22. 4000. 69 69.
1 5 11 1 02912.2951. - 1 84 . 7. 22. 22. 84000. 10. 10. [1 ' E-~~ 12 -~ ~ 0 -- ~; 12 912. 2 9 51.714.--- 7.--- 0 ; ~ ~ 0. 4 0 0 0 7-~ 0 7 D . ..
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4 1 Il 1 02953.2953. 2. 7. O. 22. ii 00 0. 12. 12. '.. ,,
4 2 14 0 - 12953.1014. 2. 2. O. 22. 4000. O. O. -.
4 1" 15 - ~ 1 -~ 01014.1014.- 2. ~ 7. O. 22. '4000. ~~12; 12 . ' -- ' ~ ~ - - ~'~'- ~~~ ~~
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4 is 16 2 02951.1014. 7. 7. O. 22. 4000. f. 9 . 69,,
4 5 17 1 02953.1014. 2. 7, 22. 22. 4000. 10. 10..
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5 1 19 1 02953.2953. -14. -28. O. 22. 4000. 12. 12...
5 2 20 2 02953.3014. -34 -14 O. 22. 4000. 72. 72. N,
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6 1 25 0 -1A14.1014 - 14 7. O. 22. 4000. O. O. a$ i
6 1 27 1 3136H.3060. - 14. 7. C. 22. 4003 12. 12. m )- ~~
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$6 2 ,26 2 01014.3068 -14. - 3 ft . O. 22. 4000. 72. 72. N,
g ;',6 4 2H 2 01014.3060. 7. 7. O. 22. 4000, t9. 69,
t. 5 29 1 01014.10 t> H . - 14. 7 2?. 22. 4000. 10. 10. g,
6 6 10 0 -11014.1068. -34. 7. U. O. 4000. O. O.- -
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7 1 11 1 02951.2951. -20. 2. 1. 22. 4000. 42. 42. "
7 1 11 1 C1314.1014 -2P. 2. 1. 22. 4011 72. 72.- - -
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