Risk-Informed Prioritization of Seismic Upgrades Based on Approximate PSA

Transcription

1 Risk-Informed Prioritization of Seismic Upgrades Based on Approximate PSA Jan L6tman 2), Kelvin Merz 1), Thomas Rochel), Johan Sandstedt z), Donald Wakefield 1) 1) EQE International, Inc., Irvine, CA 2) Forsmarks Kraftgrupp, AB, 0sthammar, Sweden ABSTRACT Forsmarks Kraftgrupp AB utilized the results of the Forsmark 1 (F1) and Forsmark 2 (F2) Seismic Margin Assessment (SMA) along with an approximate Seismic Probabilistic Safety Assessment (SPSA) to prioritize and optimize plant enhancements of the sister 1006 MW ABB Atom nuclear power plants. The F1 and F2 SMA equipment lists were expanded to include approximately 7,500 components for the two units, in lieu of the more common assessment method for developing the minimum set of equipment necessary to achieve two diverse safe shutdown paths. SMA results were reported as estimated High Confidence of Low Probability of Failure (HCLPF) capacities for each of the 7500 components. Approximate seismic fragilities were generated based on HCLPF capacities, generic component fragility information, and plant specific information. The approximate seismic fragility curves were incorporated into the existing PSA model in order to understand the relative importance of components and associated seismic capacities. The information provided a tool to efficiently allocate resources for seismic upgrades. Unique aspects of the program included software development, treatment of high frequency spectra content, generation of approximate seismic fragilities, interface with the plant PSA model, and presentation of relative results. A multi-media application was developed in Microsoft Visual Basic using the Microsoft Access data structure to facilitate the efficient walkdown, HCLPF analysis, generation of approximate seismic fragilities, and integration into the RiskSpectrum PSA model for the 7500 items. The scaling of SMA results combined with an approximate PSA model is a valuable tool for assessing the cost verses benefit of plant enhancements, however, this procedure is intended to be used for ranking of plant enhancements only. In general, the results would be overly conservative for estimating core damage frequency (CDF) compared to a comprehensive SPSA. INTRODUCTION The Forsmark Seismic Margin Assessment (SMA) was performed for Forsmark 1 (F1) and Forsmark 2 (F2) following the Electric Power Research Institute methodology [1]. The program was performed in order to obtain a better understanding of the expected performance of plant systems and equipment during an earthquake, rather than to meet regulatory requirements. The Safe Shutdown Evaluation List (SSEL) included most of the components in the initial classification list, in lieu of developing the minimum set of equipment necessary to achieve two diverse safe shutdown paths. This resulted in a very conservative SSEL of approximately 7,500 components rather than a minimum set of about 1,000 items for both units. The expanded SSEL results in a program that can be used to address future seismic equipment qualification and seismic risk issues beyond the SMA Program. The SMA results were then merged into the plant PSA model in order better understand the relative importance of components and associated seismic capacities. The information is intended for developing a tool to efficiently allocate resources for future seismic upgrades on a risk-informed basis. During the SMA, each item on the SSEL was evaluated by one of several Seismic Review Teams (SRT's). Each SRT was responsible for evaluating credible failure modes of equipment, many of which originate from the studies conducted during investigations performed in areas that have experienced significant earthquakes throughout the world. The SRT evaluated the threat of system interactions, anchorage capacity, and judged the structural integrity of SSEL components as well as the functionality of equipment that was determined to require operational capability. Results were documented on Seismic Evaluation Work Sheets (SEWS), one for each of the 7,500 components or component groups. Based on the analysis of a selected subset of equipment, each component was assigned a High Confidence of Low Probability of Failure (HCLPF) capacity in terms of Peak Ground Acceleration (PGA). The HCLPF is the acceleration level below which seismic failure of the component is considered very unlikely. The SEWS were tailored to document the SMA program in order to efficiently review, document, and report on the 7,500 components. SMA walkdowns were performed using the SMA SEWS with enhancements to capture a level of detail consistent with the more prescriptive USI A-46 criteria contained in the Generic Implementation Procedure [2]. The Seismic Review Teams (SRT) had liberal access to plant design drawings and analyses to use in conjunction with the screening criteria. Much of this information was reviewed and summarized into an EQESEWS database prior to the field walkdowns providing information to walkdown teams for investigation of specific concerns that may have been identified during prescreening.

2 Ranking and screening of equipment was a continuous process that began by assessing the relative capacity of equipment during the walkdowns. At the conclusion of the walkdowns, equipment and subsystems were reviewed and grouped within each equipment class for subsequent analyses. The ranking and screening process was documented in EQESEWS by identifying similar and bounding components within each equipment class. Outliers were also identified. Bounding components were assigned to calculation packages according to equipment class and similar attributes. Calculations were performed to establish HCLPF capacities for equipment and subsystems. Seismic fragilities were then estimated based on the HCLPF capacities and equipment class through database queries and manipulations. The question is how best to incorporate the seismic evaluations into the existing PSA for Forsmark so as to provide a risk ranking of the components most likely to be impacted by earthquakes. The incorporation should allow the seismic related failures to be combined with the non-seismic failures for a complete representation of important sequences. The incorporation of seismic events into the risk models was preformed in three steps of the analysis; hazard analysis, fragility analysis, correlation of SMA results to the PSA, and plant system and sequence analysis. HAZARD ANALYSIS Uniform Hazard Spectra (UHS) for annual probability values (frequencies of exceedance) corresponding to 10 5, 10.6 and 10-7 were generated by SKI [3]. Most SPRAs, rather than deal with a set of spectra, each associated with an annual exceedance rate, utilize a constant mean hazard spectral shape anchored to a single ground motion parameter. Peak Ground Motion (PGA) is the most common characteristic hazard parameter used in past SPRAs and thus a Mean Hazard Curve is often presented as a plot of Annual Exceedance Probability versus PGA. However, more recent SPRAs conducted for various sites have also utilized Average Spectral Acceleration (SA) over a given range as the anchor parameter. Most studies have indicated that it is more rational to consider the variability of that portion (i.e., SA) of the input motion (in the frequency domain) that actually causes the maximum response of structures and equipment rather than using PGA, which has only a weak correlation with peak response. In fact, the OBE exceedance criteria recently adopted by the USNRC uses spectral acceleration within a given frequency range as the basis for determining if plant shutdown is required following an earthquake. It should also be noted that site spectra developed for hard rock sites (such as the SKI Swedish rock spectra) have a higher ratio of spectra acceleration to PGA. Thus, the reporting of low PGA values does not necessarily imply that the equipment response, which is governed by spectral acceleration over the Hz range, is also low. In the following, hazard spectra are presented in terms of both reference parameters. While there is a slight preference for use of Average Spectral Acceleration over PGA in SPRAs, either value may be used as the reference parameter as long as the reference basis is clearly stated. Mean hazard curves for F1 and F2 were estimated in terms of both PGA and S A. Hazard Based on Peak Ground Motion SKI Developed Uniform Hazard Spectra to be used for seismic probabilistic risk assessments (SPRA) of Swedish nuclear power plants [3]. The spectra were developed to represent the ground motion characteristics for the "typical Swedish hard rock" site. The basis for modifying the hazard spectra for the site-specific characteristics of the Forsmark site (increased rock hardness variation with depth) was provided in Reference 4. The response spectra represent an approximate 80% non-exceedance probability for the spectral response ordinates. For the distribution used in [3], the mean spectral values can be obtained by dividing the spectra by 1.2; e.g., SAav e = SA/1.2, where SA is the spectral acceleration associated with a given damping value. Further, in accordance with Reference 4, the mean spectra for the Forsmark site may be estimated by 0.85 SAav e. Most SPRAs utilize a constant mean hazard spectral shape anchored to the Peak Ground Motion (PGA) as the hazard parameter, rather than deal with a set of spectra associated with each annual exceedance rate. The Mean Hazard Curve is commonly presented as a plot of Annual Exceedance Probability versus PGA. The range of probability considered for such plots is usually 10.9 to In order to expand the range of exceedance rate presented in Reference 3, the mean hazard curve is extrapolated as power function as shown in Figure 1. The Annual Exceedance Probability, or Mean Hazard, H, is estimated as: H = 10-6 X (PGAmean/0.1664) -K n where KH is given by : H =10 3 to 10-6 ; KH = and: H =10-6 to 10.8 ;KH = 3.897

3 Mean Hazard Curve (Forsmark Site) 1E-02 1E-03 ' SKI x Power Function t= 1E-04 x m o 1E-05 1E-06 u. -i < 1E-07 1E-08 1E , ,..., , O i Mean PQA, g Fig. 1. Uniform Hazard Curve in Terms of PGA Mean Hazard Curve (Forsmark Site) 1 0 E E -03 SKI x E Power Function m 1E-05 -j o" 1 E-06 o =,. u,, l- 10E-07 1 E-08 1 E Mean SA (10 to 20 Hz), g Fig. 2. Uniform Hazard Curve for Forsmark Site in Terms of SA

4 Hazard Based on Average Spectral Acceleration Recent SPRAs use an average Spectral Acceleration, SA, (usually associated with 5% damping) defined over a range of frequencies. The corresponding hazard CUrve used in such studies is a plot of Annual Exceedance Probability versus SA. For the URS provided by SKI [3], the spectra are near maximum over the range of Hz, thus the average SA over this range is suggested as an alternate hazard parameter. The range of probability considered for Mean Hazard plots is usually 10.9 to In order to expand the range of exceedance rate presented in Reference [3], the mean hazard curve as power function hazard curve was extrapolated as a power function as shown in Figure 2. This is an alternate representation of the Uniform Hazard of the Forsmark site. The Annual Exceedance Probability, or Mean Hazard, H, is estimated as: FRAGILITY ANALYSIS H = 10-6 (SAmean/0.667) -KH where KH is given by : H = 10-3 to 10-6 ; KH = and:h=10.6 to 10.8 ;KH = The SMA results are currently reported as High Confidence Low Probability of Failure (HCLPF) capacity values in terms of the PGA of RLE as a reference spectral shape [2]. These HCLPF capacities may also be reported in terms of the SAave of the RLE. The HCLPFpGA would be multiplied by SAave/PGA = 0.312/ in order to convert the HCLPF values to the alternate basis HCLPFsA. In general, a HCLPF value is defined by assuming a double lognormal fragility model: k.) HCLPF = A e{-l'65(13r +13u ) } k.) where A is the median capacity (either PSA or SAAvE ) and the logarithmic standard deviations for randomness and uncertainty are denoted by ~r and 13u, respectively. If 13r and 13u are approximately equal, then k.) HCLPF = A e -2'33~c where 13c is the composite variability of the mean fragility curve given by ~c = (~r 2 "k- ~u2) 1/2 SMA HCLPF values, however, are associated with the nonexceedance probability level of the RLE (80% in the case of the SKI E5) and thus need to be converted to a median value by a factor which accounts for the ratio of the RLE capacity to the "true" median capacity. Since the SKI E5 spectra have been defined by taking the ratio of the 80% nonexceedance spectra to the mean spectra to be a value of 1.2, the ratio of the 80% nonexceedance spectra to the median spectra is approximately 1.25, thus HCLPFs0 = HCLPF80 / 1.25 where HCLPF80 denotes the SMA HCLPF capacity value and HCLPFs0 denotes the HCLPF capacity value referenced to the median capacity value to be used in an SPRA. Past SPRAs have indicated that 13c values are generally within the range of Therefore, as a first approximation, the mean fragility curves for each component was obtained by simply assuming that the HCLPF is a fixed value and the 13c values are always These were called the approximate seismic fragility curves. CORRELATION OF SSEL COMPONENTS TO PSA BASIC EVENTS The seismic evaluation of approximately 7,500 components was accomplished through extensive relational database manipulations. EQESEWS was developed in Microsoft Visual Basic using the Microsoft Office suite of programs for data management and reporting. Correlation of seismic analysis results to the plant PSA was feasible since both RiskSpectrum PSA software and EQESEWS utilize the Microsoft Access data structure. The estimated equipment seismic fragilities were correlated to PSA model basic events through database queries. The subsets of SSEL items that do not have corresponding basic events, and basic events that do not have corresponding seismic fragilities, were identified as part of the review process. Because the fragility levels are rough estimates, not all safety

5 related items are contributors to core damage, and non-safety related systems are included in core damage sequences; the systems analysis should be used to assess equipment and systems on a relative basis and core damage frequencies should not be determined. PLANT SYSTEM AND SEQUENCE ANALYSIS One option for integrating seismic data into the PSA is incorporation of all items on the SSEL into the existing Forsmark PSA model. This would require a component-by-component review of all several thousand components, a discussion of the failure mode for each, and a decision as to how such a failure mode can be incorporated explicitly in the PRA models. It also would require that the PSA model be expanded to include all components for which HCLPFs were developed. This process would be very time consuming and of limited value for many components that have a high seismic capacity. We, therefore, chose to screen the list of several thousand components to only those items that may significantly contribute to the risk results. The components remaining after screening are incorporated into the PSA models. Frequency Screening of Components Based on a cursory look at potentially dominant sequences, the seismic core damage frequency using the conservative SMA HCLPFs was judged to be in the per year range. The hazard exceedance frequency at 0.3g is only lxl0 7 per year. Therefore, at most the core damage frequency can increase by only lxl0 7 per year due to components that only fail above 0.3g. Therefore, components with HCLPFs above 0.3g PGA can be screened from further consideration. This is even more apparent when one considers that components with HCLPFs below 0.3g are more likely fail above 0.3g; i.e., core damage may also occur from such failures. If so, adding stronger components is unlikely to have a significant impact. Seismic Initiating Events Six earthquake ranges were selected to match up with the lowest HCLPF of any Forsmark component (i.e., 04g) and to coincide with the ground accelerations for which hazard exceedance frequencies have been developed by SKI; i.e., at 076g, g, g,.400g, and.500g. An additional break point at 0.11 g has been added because this is the HCLPF for block walls; i.e., below this acceleration no block wall failures are anticipated. Above g, no detailed modeling is believed necessary. The hazard exceedance frequency at g is already low (i.e., per year). The frequency of each of the six earthquake initiating events is given in the following Table 1. Table 1. Seismic Initiating Events Initiator Name Lower Boundary (g). Upper Boundary (g) EQ EQ EQ EQ EQ EQ Frequency per year 6.6x x x x x x10 8 Seismic Component Failures For components with HCLPFs less than.300g, the conditional component failure probabilities were developed for each earthquake initiator. As mentioned earlier, the fragility curves for each component were assumed to have a [3c value of.35 and a HCLPF as determined in the SMA. The mean fragility curves were integrated over the range of accelerations that make up each earthquake initiator to obtain the average component failure probability over each range. The results for selected HCLPFs are presented in Table 2. For earthquake ranges below the HCLPF, a failure probability of zero is assumed. As expected, the failure probabilities for weaker components get very large, even for earthquakes less than.30g. Events representing the seismic failure modes were added to the PRA model for all components with HCLPFs less than or equal to.30g. Only a single event needed to be added for each failure mode. The failure probabilities assigned to these events were changed for each of the six earthquake levels. The loss of mainfeedwater PRA models were used to quantify the earthquake initiators. This accident sequence model was judged appropriate for earthquakes since offsite power is likely to be lost (e.g., causing mainfeedwater to be lost) and no credit for electric power recovery should be taken. Also, all systems dependent on offsite power were assumed to be unavailable.

6 Table 2. Conditional Component Failure Probabilities by Peak Ground Acceleration Lower and Upper Acceleration Bin Boundaries (g) HCLPF x x Seismic Risk Model Results The earthquake event tree models were then quantified for each of the six ranges of earthquakes defined. A sensitivity case in which the minimum acceleration at which failures could be expected was increased to 0.1 g was also quantified. The core damage frequencies for these two sets of results are unimportant for our purposes. What is important is the list of components ranked by importance to the seismic core damage frequency. INSIGHTS GAINED The quantification of SMA results in the PSA model identified the top components in terms of approximate core damage frequency as well as the more critical ranking by importance to the seismic core damage frequency. In both cases the top ten components were foundto include electrical and control cabinets that were assigned a low HCLPF capacity due to attributes that can be mitigated through relatively minor enhancements. In fact, most components found to have a significant impact on core damage frequency can be upgraded through relatively easy enhancements to bring the seismic capacity to a level that will result in an insignificant contribution to the core damage frequency. The approximate seismic PSA quantification also identified many components found to have relatively low seismic capacities that do not significantly contribute to the overall plant risk. The approximate seismic PSA model provides Forsmarks Kraftgrupp with a living risk-informed tool to perform cost vs. benefit evaluation of seismic enhancements, and compare the value of seismic enhancements to unrelated plant upgrades. This facilitates the efficient allocation of plant resources to seismic, fire, line break, and other risk and reliability issues. REFERENCES 1. A Methodology for Assessment of Nuclear Power Plant Seismic Margin, Electric Power Research Institute, EPRI NP SL, Revision 1, August Generic Implementation Procedure for Seismic Verification of Nuclear Plant Equipment, Seismic Qualification Utility Group, Revision 2, Characterization of Seismic Ground Motion for Probabilistic Analyses of Nuclear Facilities in Sweden, Swedish Nuclear Power Inspectorate, SKI Technical Report 92:3, Stockholm, Sweden, 1992 (consists of summary report and five separate study documentation reports). 4. "FT 97/322, Omr~desspecifik seismisk markrorelsekarakteristik (jordbavning) for Forsmark, FT-Rapport 97/322,