The MAAP4 computer code (Reference 1) is often used to perform thermal hydraulic simulations of severe accident sequences for nuclear power plant Probabilistic Risk Assessments (PRAs). MAAP4 can be used to simulate accidents for both Boiling Water Reactors (BWRs) as well as Pressurized Water Reactors (PWRs). This assessment employs MAAP 4.0.6a for PWRs (References 1 and 5), which incorporates explicit thermal hydraulic modeling of the Reactor Coolant System (RCS) and Steam Generators (SGs), along with a nodalized integrated containment model. In the PRA environment, MAAP4 has been used for applications such as the development of PRA Level 1 and Level 2 success criteria and human action timings. The CENTS computer code (Reference 2) is a simulation tool that is typically used to analyze non-Loss of Coolant Accident (non-LOCA) events postulated to occur in nuclear power plants incorporating Combustion Engineering (CE) and Westinghouse Nuclear Steam Supply System (NSSS) designs. It is licensed by the NRC perform design basis non-LOCA safety analyses. It is a best estimate code which uses detailed thermal hydraulic modeling of the RCS and SGs; however, it does not model the containment performance. It is used to perform a wide spectrum of licensing and best estimate non-LOCA event analysis and has the capability to simulate operator actions. The CENTS models are the basis for several full scope simulators in the industry. The purpose of the analyses described in this paper is to compare MAAP4 and CENTS predictions for the Station Blackout (SBO) and Total Loss of Feedwater (TLOFW) scenarios for a representative PWR in the Westinghouse fleet that employs a CE NSSS design. The results of this comparison are used to highlight postulated MAAP4 user challenges and assist in developing guidance on selecting MAAP4 parameters for use in these scenarios. The results of the analyses presented in this paper indicate several useful insights. Overall, this paper shows that when care is taken to normalize the MAAP4 and CENTS primary side natural circulation flowrate and SG modeling, the trends of the MAAP4 and CENTS predictions of core uncovery agree reasonably well.

Paragraph (a)(4) of the Maintenance Rule (re 10CFR§50.65) states that before performing maintenance activities, the licensees shall assess and manage the increase in risk that may result from the maintenance activities. The rule is explicitly applicable to all operating modes. Currently, most plants use a qualitative tool for assessing and controlling the risk of the various plant conditions during an outage. Fewer plants have any means of performing a quantitative or qualitative assessment of the associated risks of transitioning the plant in each configuration from power to “cold shutdown.” Typically, only the end-state of shutdown is considered. The transition-period includes short-duration configurations when the available set of equipment is not what it was during power operations, e.g., having only one main feedwater train in-service. Given the concern that the NRC may require quantitative risk assessments of plant transitions and plant configurations during shutdown operations, Omaha Public Power District (OPPD) pro-actively authorized Westinghouse Engineering Services to develop a method for assessing risk associated with a transition from all power to shutdown and back to full power. An outage schedule is highly plant specific, with plant-to-plant and outage-to-outage variations in system configurations, and maintenance practices. Accordingly, the duration of the transition largely depends on equipment maintenance activities driving the decision to shutdown and repair. The time spent in various parts of the transition is a strong determinant in the associated risk of the transition. A transition takes the plant through a series of Plant Operational States (POSs). The features important to the characterization of each of the POSs include decay-heat level, plant activities involved, available equipment, as well as RCS temperature and pressure. The risk of the entire transition comes from calculating a figure-of-merit of each POS which can be loosely thought of as a per-hour core-damage frequency (CDF). This number gets multiplied by the associated duration of the POS. The sum is the transition risk. The effective CDF associated with the transition comes from dividing the POS-specific CDF sum by the total transition time, and converting that result to an annual frequency. Our paper describes decomposing OPPD operating procedures into periods for which we quantified sequences. In particular, the method considers the dominant shutdown failure modes: loss of shutdown cooling, loss of inventory, and loss of offsite power (including both plant centered and grid-related events). The transition example presented herein covers a simple shutdown and restart stemming from an indeterminate-quality problem. That is, all equipment is functional and available to the plant operators.

An Internal Flooding Probabilistic Risk Assessment (IF-PRA) study is required to meet the requirements of the Internal Flooding portions of the ASME Internal Events PRA standard [1, 2, 3] and RG 1.200 R1 [4] for risk-informed applications at Nuclear Power Plants (NPPs). An internal flooding study was performed recently for a Nuclear Power Plant (NPP), Fort Calhoun Station (FCS), with a nuclear steam supply system designed by Combustion Engineering. The study was performed using guidance that is currently being developed for industry use by EPRI [5]. The intent of the EPRI draft guidance is to describe how to perform the various tasks to meet the requirements and expectations of the ASME PRA Standard in order to comply with RG 1.200. Performing this analysis provided an opportunity to gain numerous insights on how to best perform the analysis from a technical standpoint. This paper provides lessons learned and insights gained in the implementation of the EPRI draft guidance on internal flooding for PRA. Insights and lessons learned on the assignment of initiating event frequencies, treatment of dynamic flood volumes and time-based operator response timings, and developing associated peer review materials are provided. Discussions dealing with various sources of pipe failure frequencies highlight key differences between commonly used data. Characterizations of spray scenarios were evaluated to determine their impact on plant risk caused by internal flooding events. Maintenance-induced flooding scenarios that are often neglected were evaluated to gain insights on their impact on plant risk. Insights on performing a timely completion of the analysis are provided. Optimization techniques for plant walkdowns to capture relevant information and identify high priority flood areas are discussed. The impact of the flooding scenarios on PRA-related equipment was integrated into the internal events PRA model to quantify the associated risk. The rules used to perform the integration process and the lessons learned from the integration are also discussed.

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