Evelyn H. Hirt

Progress towards prognostic health management of passive components in advanced small modular reactors

Sustainable nuclear power to promote energy security and to reduce greenhouse gas emissions are two key national energy priorities. The development of deployable small modular reactors (SMRs) is expected to support these objectives by developing technologies that improve the reliability, sustain safety, and improve affordability of new reactors. Advanced SMRs (AdvSMRs) refer to a specific class of SMRs and are based on modularization of advanced reactor concepts. Prognostic health management (PHM) systems can benefit both the safety and economics of deploying AdvSMRs and can play an essential role in managing the inspection and maintenance of passive components in AdvSMR systems. This paper describes progress on development of an experimental setup for testing and validation of PHM systems for AdvSMR passive components. The experimental set-up for validation of prognostic algorithms is focused on thermal creep degradation as the prototypic degradation mechanism. The test bed enables accelerated thermal creep aging of materials relevant to AdvSMRs along with multiple nondestructive evaluation (NDE) measurements for assessment of thermal creep damage. NDE techniques include eddy current, magnetic Barkhausen noise (MBN), and linear and non-linear ultrasonic measurements. Details of the test-bed design as well as initial measurements results for specimens at different levels of thermal creep damage are presented.

Summary Describing Integration of ERM Methodology into Supervisory Control Framework with Software Package Documentation; Advanced Reactor Technology Milestone: M4AT-16PN2301052

....................................................................................................................................................... iii Acknowledgments ......................................................................................................................................... v Acronyms and Abbreviations ..................................................................................................................... vii 1.0 Introduction ....................................................................................................................................... 1.1 1.1 Research Objectives .................................................................................................................. 1.1 1.2 Research Assumptions .............................................................................................................. 1.1 1.3 Organization of Report .............................................................................................................. 1.2 2.0 Background ........................................................................................................................................ 2.1 2.1 Overview and Operational Characteristics for Advanced Reactors .......................................... 2.1 2.2 Brief Overview of ERMs for Advanced Reactors ..................................................................... 2.3 3.0 Prototypic ERM Framework Evaluation ........................................................................................... 3.1 3.1 Economic Model ....................................................................................................................... 3.1 3.2 Component Aging ..................................................................................................................... 3.1 3.3 Evaluation of Prototypic ERM Framework ............................................................................... 3.2 3.3.1 Changes to Maintenance Strategy .................................................................................. 3.2 3.3.2 Prognostic Result ............................................................................................................ 3.9 3.3.3 Evaluation Summary .................................................................................................... 3.11 4.0 Integration of ERM Module with Supervisory Control System Framework ..................................... 4.1 4.1 Overview ................................................................................................................................... 4.1 4.1.1 ERM Software Design ................................................................................................... 4.1 4.1.2 Evaluation Scenarios ...................................................................................................... 4.1 4.2 Integration Specification ........................................................................................................... 4.2 4.2.1 Valve Prognostic Modules ............................................................................................. 4.3 4.3 Progress Summary..................................................................................................................... 4.3 4.3.1 Integration ...................................................................................................................... 4.4 4.3.2 Evaluation of Valve Prognostic Model .......................................................................... 4.5 5.0 Summary ............................................................................................................................................ 5.1 5.1 Envisioned Role of ERM in O&M for Advanced Reactors ...................................................... 5.1 5.2 Research Contributions towards Advanced Reactor O&M Optimization................................. 5.2 5.2.1 Overview of Achievements during this Project.............................................................. 5.2 5.2.2 Recommended Path Forward ......................................................................................... 5.2 6.0 References ......................................................................................................................................... 6.1 Appendix A – Specification for Integration of Diagnostics and Prognostics Module of Enhanced Risk Monitoring with Supervisory Control System ......................................................................... A.1

Progress towards prognostic health management of passive components in advanced reactors — Model selection and evaluation

This paper presents recent progress towards developing a prognostic health management framework for passive components of advanced reactors (AR). The focus of this paper is on lifecycle prognostics for passive components using a Bayesian prognostic algorithm that provides a natural framework for incorporating different sources of variability and uncertainties inherent in the operations of AR. High-temperature creep damage, a prototypic failure mechanism in AR materials, is used as the context for this research. A Bayesian model selection approach is implemented to select the appropriate creep degradation model at any given time, using relevant sensor measurements reflecting the material degradation state. The model selection approach, based on reversible jump Markov chain Monte Carlo methods, is integrated with Bayesian particle filter-based prognostic framework. The proposed approach is evaluated using strain measurements obtained from accelerated creep testing of stainless steel specimens. Results indicate feasibility of the proposed approach in accurately identifying the creep degradation stage from the available measurements at a given time. Effect of uncertainties in material degradation model and measurement noise on the performance of the prognostic algorithm is also investigated.

Research gaps and technology needs in development of PHM for passive AdvSMR components

Advanced small modular reactors (AdvSMRs), which are based on modularization of advanced reactor concepts, may provide a longer-term alternative to traditional light-water reactors and near-term small modular reactors (SMRs), which are based on integral pressurized water reactor (iPWR) concepts. SMRs are challenged economically because of losses in economy of scale; thus, there is increased motivation to reduce the controllable operations and maintenance costs through automation technologies including prognostics health management (PHM) systems. In this regard, PHM systems have the potential to play a vital role in supporting the deployment of AdvSMRs and face several unique challenges with respect to implementation for passive AdvSMR components. This paper presents a summary of a research gaps and technical needs assessment performed for implementation of PHM for passive AdvSMR components.