PSAM 16 - Paper Overview

PSAM 16 Conference Paper Overview

Welcome to the PSAM 16 Conference paper and speaker overview page.

Lead Author: Yong-Joon Choi Co-author(s): Yunyeong Heo (yyheo0207@unist.ac.kr) Eunseo So (eunseo.so@inl.gov) Mohammad Abdo (mohammad.abdo@inl.gov) Cole Blakely (cole.blakely@inl.gov) Carlo Parisi (carlo.parisi@inl.gov) Jarrett Valeri (jarrett.valeri@fpolisolutions.com) Chris Gosdin (cgosdin@fpolisolutions.com) Gabrielle Palamone (gabrielle.palamone@fpolisolutions.com) Cesare Frepoli (frepolc@fpolisolutions.com) Jason Hou (jhou8@ncsu.edu)

Demonstration of the Plant Fuel Reload Process Optimization for an Operating PWR
The US Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed Systems Analysis (RISA) Pathway plant reload optimization project aims to develop and demonstrate an automatized generic platform that can generate optimized fuel load configurations in the reactor core of a nuclear power plant. The project targets to optimize reactor core thermal limits through the implementation of state-of-the-art computational and modeling techniques. The optimization of core thermal limits allows a smaller fuel batch size to produce the same amount of electricity, which reduces new fuel costs and saves a significant amount of money on the back-end of the fuel cycle by reducing the volume of spent fuel that needs to be processed. The cost of a typical fuel reload for a light water reactor is about $50M and this project that a cost reduction of at least 5% is attainable by consolidating methods and core design procedures and practices. . This equates to a savings in excess of $2M per reactor per reload. There could be additional savings achievable in the back-end cost reduction in spent fuel management. The major research and development area of the project includes the development of an artificial intelligence-based "genetic algorithm" for the platform and demonstration of plant reload optimization with selective design basis accident scenarios for licensing support during fuel reloading. This research is very timely considering that the industry is actively getting ready to transition to accident tolerance fuels, and this platform will be capable to perform all necessary accident tolerance fuel evaluations. An additional benefit of this platform is an integrated workflow that incorporates seamlessly all the steps required for the fuel reload analysis, which traditionally is a labor-intensive and time-consuming process. This paper summarizes the recent research outcomes., This project progressed from the planning and methodology development phase to the early demonstration phase including the development of a multi-objective optimization process using genetic algorithms; development and testing of an approach for acceleration of optimization using artificial intelligence that significantly reduces the computational burden; demonstration of the fuel reload optimization framework for a generic pressurized water reactor; and demonstration of selective scenarios for evaluation of the transition from deterministic to risk-informed approach for fuel analyses. On-going activities and future plans are also summarized.

Demonstration of the Plant Fuel Reload Process Optimization for an Operating PWR

The US Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed Systems Analysis (RISA) Pathway plant reload optimization project aims to develop and demonstrate an automatized generic platform that can generate optimized fuel load configurations in the reactor core of a nuclear power plant. The project targets to optimize reactor core thermal limits through the implementation of state-of-the-art computational and modeling techniques. The optimization of core thermal limits allows a smaller fuel batch size to produce the same amount of electricity, which reduces new fuel costs and saves a significant amount of money on the back-end of the fuel cycle by reducing the volume of spent fuel that needs to be processed. The cost of a typical fuel reload for a light water reactor is about $50M and this project that a cost reduction of at least 5% is attainable by consolidating methods and core design procedures and practices. . This equates to a savings in excess of $2M per reactor per reload. There could be additional savings achievable in the back-end cost reduction in spent fuel management. The major research and development area of the project includes the development of an artificial intelligence-based "genetic algorithm" for the platform and demonstration of plant reload optimization with selective design basis accident scenarios for licensing support during fuel reloading. This research is very timely considering that the industry is actively getting ready to transition to accident tolerance fuels, and this platform will be capable to perform all necessary accident tolerance fuel evaluations. An additional benefit of this platform is an integrated workflow that incorporates seamlessly all the steps required for the fuel reload analysis, which traditionally is a labor-intensive and time-consuming process. This paper summarizes the recent research outcomes., This project progressed from the planning and methodology development phase to the early demonstration phase including the development of a multi-objective optimization process using genetic algorithms; development and testing of an approach for acceleration of optimization using artificial intelligence that significantly reduces the computational burden; demonstration of the fuel reload optimization framework for a generic pressurized water reactor; and demonstration of selective scenarios for evaluation of the transition from deterministic to risk-informed approach for fuel analyses. On-going activities and future plans are also summarized.

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Author and Presentation Info

Lead Author Name: Yong-Joon Choi (yong-joon.choi@inl.gov)

Bio: Since 2012, Dr. Choi is a program manager and senior research scientist at Idaho National Laboratory. In his capacity, he leads various programs under DOE's Light Water Reactor Sustainability program. He is also a member of RELAP5-3D nuclear thermal-hydraulics code development team. Prior to INL, he worked at the OECD Nuclear Energy Agency for seven years as program manger for developing advanced nuclear fuel cycles and related strategy and policy. Dr. Choi received his Ph.D. and grand master degree on thermal system energy from the University of Marne-La-Vallee, France, M.S. and B.S in nuclear engineering in Kyunghee University, Korea.

Country: United States of America
Company: Idaho National Laboratory
Job Title: Program Manager / Senior Researcher

PSAM 16 Conference Paper Overview

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Paper YO34 Preview

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