ASME Risk‐Based Inservice Inspection and Testing: An Outlook to the Future

Abstract

Significant research work has been completed in the development of risk-based inservice inspection (ISI) and testing (IST) technology for nuclear power plant applications through the ASME Center For Research and Technology Development. This paper provides technology that has been developed for these engineering applications. The technology includes risk-based ranking methods, beginning with the use of plant probabilistic risk assessment (PRA), for the determination of risk-significant and less risk-significant components for inspection and the determination of similar populations for pumps and valves for inservice testing. Decision analysis methods are outlined for developing IS1 and IST programs. This methodology integrates nondestructive examination data, structural reliabilityhsk assessment results, PRA results, failure data, and expert opinion to evaluate the effectiveness of IS1 programs. Similarly, decision analysis uses the output of failure mode and causes analysis in combination with data, expert opinion, and PRA results to evaluate the effectiveness of IST programs. Results of pilot applications of these ASME methods to actual nuclear plant systems and components are summarized. The results of this work are already being used to develop recommended changes in IS1 and IST requirements by the ASME Section XI and the ASME Operation and Maintenance Code organizations. A perspective on Code and regulatory adoption is also outlined. Finally, the potential benefits to the nuclear industry in terms of safety, person-rem exposure, and costs are summarized.

Development of Risk-Based Inspection and Maintenance procedures for an oil refinery

“…Many authors used probabilistic risk assessment (PRA) as a tool for maintenance prioritization (Vesely, Belhadj, & Rezos, 1993). Balkey and Art (1998) developed a methodology, which includes risk-based ranking methods, beginning with the use of plant PRA, for the determination of risk-significant and less risk-significant components for inspection and the determination of similar populations for pump and valve in-service testing. This methodology integrates non-destructive examination data, structural reliability/risk assessment results, PRA results, failure data and expert opinions.…”

A Fuzzy Cognitive Maps Tool for Developing a RBI&M Model

“…Many authors used probabilistic risk assessment as a tool for maintenance prioritisation . Balkey and Art developed a methodology, including risk‐based ranking methods, beginning with the use of plant probabilistic risk assessment, in order to determinate the risk‐significant and less risk‐significant components for inspection, and the determination of analogous populations for pump and valve in‐service testing phase.…”

“…It is likewise indispensable to highlight that Kosko 5 suggests the application of the step function (8) in order to simplify the vector normalisation. With this function, each value x ik (t) ∈ x i (t) is replaced by 0 and 1 values with the objective of reaching a simplified x i (t):…”

Recursive Operability Analysis as a decision support tool for Risk-Based Maintenance

“…On the basis of these results, they were able to prioritize the maintenance of those components that gave the basic events of the TEs. Balkey and Art (1998) developed a probabilistic risk assessment methodology that included risk-based ranking methods. They used their approach to determine risk-significant and less risk-significant components with respect to inspection.…”