RAST-K v2—Three-Dimensional Nodal Diffusion Code for Pressurized Water Reactor Core Analysis

The RAST-K v2, a novel nodal diffusion code, was developed at the Ulsan National Institute of Science and Technology (UNIST) for designing the cores of pressurized water reactors (PWR) and performing analyses with high accuracy and computational performance by adopting state-of-the-art calculation m...

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Main Authors: Jinsu Park, Jaerim Jang, Hanjoo Kim, Jiwon Choe, Dongmin Yun, Peng Zhang, Alexey Cherezov, Deokjung Lee
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Energies
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Online Access:https://www.mdpi.com/1996-1073/13/23/6324
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author Jinsu Park
Jaerim Jang
Hanjoo Kim
Jiwon Choe
Dongmin Yun
Peng Zhang
Alexey Cherezov
Deokjung Lee
author_facet Jinsu Park
Jaerim Jang
Hanjoo Kim
Jiwon Choe
Dongmin Yun
Peng Zhang
Alexey Cherezov
Deokjung Lee
author_sort Jinsu Park
collection DOAJ
description The RAST-K v2, a novel nodal diffusion code, was developed at the Ulsan National Institute of Science and Technology (UNIST) for designing the cores of pressurized water reactors (PWR) and performing analyses with high accuracy and computational performance by adopting state-of-the-art calculation models and various engineering features. It is a three-dimensional multi-group nodal diffusion code developed for the steady and transient states using microscopic cross-sections generated by the STREAM code for 37 isotopes. A depletion chain containing 22 actinides and 15 fission products and burnable absorbers was solved using the Chebyshev rational approximation method. A simplified one-dimensional single-channel thermal-hydraulic calculation was performed with various values for the thermal conductivity. Advanced features such as burnup adaptation and CRUD modeling capabilities are implemented for the multi-cycle analysis of commercial reactor power plants. The performance of RAST-K v2 has been validated with the measured data of PWRs operating in Korea. Furthermore, RAST-K v2 has been coupled with a sub-channel code (CTF), fuel performance code (FRAPCON), and water chemistry code for multiphysics analyses. In this paper, the calculation models and engineering features implemented in RAST-K v2 are described, and then the application status of RAST-K v2 is presented.
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spelling doaj.art-fe98fa4aecaf47fdba5b2dce35ef0bfa2023-11-20T22:59:28ZengMDPI AGEnergies1996-10732020-11-011323632410.3390/en13236324RAST-K v2—Three-Dimensional Nodal Diffusion Code for Pressurized Water Reactor Core AnalysisJinsu Park0Jaerim Jang1Hanjoo Kim2Jiwon Choe3Dongmin Yun4Peng Zhang5Alexey Cherezov6Deokjung Lee7Department of Nuclear Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan 44919, KoreaDepartment of Nuclear Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan 44919, KoreaDepartment of Nuclear Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan 44919, KoreaDepartment of Nuclear Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan 44919, KoreaDepartment of Nuclear Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan 44919, KoreaDepartment of Nuclear Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan 44919, KoreaDepartment of Nuclear Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan 44919, KoreaDepartment of Nuclear Engineering, Ulsan National Institute of Science and Technology, UNIST-gil 50, Ulsan 44919, KoreaThe RAST-K v2, a novel nodal diffusion code, was developed at the Ulsan National Institute of Science and Technology (UNIST) for designing the cores of pressurized water reactors (PWR) and performing analyses with high accuracy and computational performance by adopting state-of-the-art calculation models and various engineering features. It is a three-dimensional multi-group nodal diffusion code developed for the steady and transient states using microscopic cross-sections generated by the STREAM code for 37 isotopes. A depletion chain containing 22 actinides and 15 fission products and burnable absorbers was solved using the Chebyshev rational approximation method. A simplified one-dimensional single-channel thermal-hydraulic calculation was performed with various values for the thermal conductivity. Advanced features such as burnup adaptation and CRUD modeling capabilities are implemented for the multi-cycle analysis of commercial reactor power plants. The performance of RAST-K v2 has been validated with the measured data of PWRs operating in Korea. Furthermore, RAST-K v2 has been coupled with a sub-channel code (CTF), fuel performance code (FRAPCON), and water chemistry code for multiphysics analyses. In this paper, the calculation models and engineering features implemented in RAST-K v2 are described, and then the application status of RAST-K v2 is presented.https://www.mdpi.com/1996-1073/13/23/6324RAST-K v2nodal diffusion codeengineering featuresverification and validationmulti-physics couplingmachine learning
spellingShingle Jinsu Park
Jaerim Jang
Hanjoo Kim
Jiwon Choe
Dongmin Yun
Peng Zhang
Alexey Cherezov
Deokjung Lee
RAST-K v2—Three-Dimensional Nodal Diffusion Code for Pressurized Water Reactor Core Analysis
Energies
RAST-K v2
nodal diffusion code
engineering features
verification and validation
multi-physics coupling
machine learning
title RAST-K v2—Three-Dimensional Nodal Diffusion Code for Pressurized Water Reactor Core Analysis
title_full RAST-K v2—Three-Dimensional Nodal Diffusion Code for Pressurized Water Reactor Core Analysis
title_fullStr RAST-K v2—Three-Dimensional Nodal Diffusion Code for Pressurized Water Reactor Core Analysis
title_full_unstemmed RAST-K v2—Three-Dimensional Nodal Diffusion Code for Pressurized Water Reactor Core Analysis
title_short RAST-K v2—Three-Dimensional Nodal Diffusion Code for Pressurized Water Reactor Core Analysis
title_sort rast k v2 three dimensional nodal diffusion code for pressurized water reactor core analysis
topic RAST-K v2
nodal diffusion code
engineering features
verification and validation
multi-physics coupling
machine learning
url https://www.mdpi.com/1996-1073/13/23/6324
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