Application of risk-based methods to inservice testing of check valves
N.B. Closky, K.R. Balkey, William J. McAllister
Abstract
N.B. Closky, K.R. Balkey, William J. McAllister
Abstract
Research efforts have been underway in the American Society of Mechanical Engineers (ASME) and industry to define appropriate methods for the application of risk-based technology in the development of inservice testing (IST) programs for pumps and valves in nuclear steam supply systems. This paper discusses a pilot application of these methods to the inservice testing of check valves in the emergency core cooling system of Georgia Power`s Vogtle nuclear power station. The results of the probabilistic safety assessment (PSA) are used to divide the check valves into risk-significant and less-risk-significant groups. This information is reviewed by a plant expert panel along with the consideration of appropriate deterministic insights to finally categorize the check valves into more safety-significant and less safety-significant component groups. All of the more safety-significant check valves are further evaluated in detail using a failure modes and causes analysis (FMCA) to assist in defining effective IST strategies. A template has been designed to evaluate how effective current and emerging tests for check valves are in detecting failures or in finding significant conditions that are precursors to failure for the likely failure causes. This information is then used to design and evaluate appropriate IST strategies that consider both the test method and frequency. A few of the less safety-significant check valves are also evaluated using this process since differences exist in check valve design, function, and operating conditions. Appropriate test strategies are selected for each check valve that has been evaluated based on safety and cost considerations. Test strategies are inferred from this information for the other check valves based on similar check valve conditions. Sensitivity studies are performed using the PSA model to arrive at an overall IST program that maintains or enhances safety at the lowest achievable cost.
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Research efforts have been underway in the American Society of Mechanical Engineers (ASME) and industry to define appropriate methods for the application of risk-based technology in the development of inservice testing (IST) programs for pumps and valves in nuclear steam supply systems. This paper discusses a pilot application of these methods to the inservice testing of check valves in the emergency core cooling system of Georgia Power`s Vogtle nuclear power station. The results of the probabilistic safety assessment (PSA) are used to divide the check valves into risk-significant and less-risk-significant groups. This information is reviewed by a plant expert panel along with the consideration of appropriate deterministic insights to finally categorize the check valves into more safety-significant and less safety-significant component groups. All of the more safety-significant check valves are further evaluated in detail using a failure modes and causes analysis (FMCA) to assist in defining effective IST strategies. A template has been designed to evaluate how effective current and emerging tests for check valves are in detecting failures or in finding significant conditions that are precursors to failure for the likely failure causes. This information is then used to design and evaluate appropriate IST strategies that consider both the test method and frequency. A few of the less safety-significant check valves are also evaluated using this process since differences exist in check valve design, function, and operating conditions. Appropriate test strategies are selected for each check valve that has been evaluated based on safety and cost considerations. Test strategies are inferred from this information for the other check valves based on similar check valve conditions. Sensitivity studies are performed using the PSA model to arrive at an overall IST program that maintains or enhances safety at the lowest achievable cost.
Key concepts: Computer science, Forensic engineering, Engineering