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LLNL offers tools to model the economics of inertial fusion power plants
Lawrence Livermore National Laboratory has designed a model to help assess the economic impact of future fusion power plant operations—specifically, the operation of inertial fusion energy (IFE) power plants. Further, it has made its Generalized Economics Model (GEM) for Fusion Technology—an Excel spreadsheet—available for download.
Christopher Hunter, Ching Ng, Mehdi Reisi Fard, Zhegang Ma, Sai Zhang
Nuclear Technology | Volume 209 | Number 11 | November 2023 | Pages 1680-1687
PSA 2021 Paper | doi.org/10.1080/00295450.2023.2234714
Articles are hosted by Taylor and Francis Online.
The U.S. Nuclear Regulatory Commission (NRC) and the nuclear power industry have evaluated and discussed various assumptions and methods for the treatment of potential common-cause failures (CCFs) in event and condition assessments (ECAs), specifically risk assessments performed as part of the NRC’s Significance Determination Process (SDP) in recent years. The basis for how a potential CCF is treated in SDP risk assessments is provided in NUREG-2225, “Basis for the Treatment of Potential Common-Cause Failure in the Significance Determination Process.” In light of new information and advancements in probabilistic risk assessment technology, the NRC and Idaho National Laboratory (INL) have continued the development of the causal alpha factor method (CAFM) for potential use in ECAs. The NRC and INL evaluated the suitability of using CAFM in SDP evaluations and reviewed the methodology to identify any potential data gaps.
Furthermore, an investigation was performed on the practice of common-cause component groups to determine if changes are needed to ensure that CCF is appropriately accounted for in the Standardized Plant Analysis Risk models. In addition, a focused review of the existing method that estimates CCF parameters was performed to determine if the assumptions used in the existing process result in CCF parameters that are representative of current industry performance. It was also desired to gather a better understanding of the aspects of the alpha factor method and data calculation process that either have significant effects on the CCF parameters and/or increase the uncertainties associated with these parameters. This paper provides a summary of recently completed work, including insights, conclusions, and recommendations from this effort.