Multi-physics and multi-scale benchmarking and uncertainty quantification within OECD/NEA framework

被引:11
|
作者
Avramova, M. [1 ]
Ivanov, K. [1 ]
Kozlowski, T. [2 ]
Pasichnyk, I. [3 ]
Zwermann, W. [3 ]
Velkov, K. [3 ]
Royer, E. [4 ]
Yamaji, A. [5 ]
Gulliford, J. [5 ]
机构
[1] Penn State Univ, University Pk, PA 16802 USA
[2] Univ Illinois, Urbana, IL 61801 USA
[3] Gesell Anlagen & Reaktorsicherheit GRS mbH, Munich, Germany
[4] INSTN CEA Saclay, Saclay, France
[5] OECD NEA, Paris, France
关键词
Benchmark; Uncertainty; Multi-physics; Multi-scale; TRACE/PARCS; VALIDATION;
D O I
10.1016/j.anucene.2014.12.014
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
The development of multi-physics multi-scale coupled methodologies for Light Water Reactor (LWR) analysis requires comprehensive validation and verification procedures, which include well-established benchmarks developed in international cooperation. The Nuclear Energy Agency (NEA) of the Organization for Economic Co-operation and Development (OECD) has provided such framework, and over the years a number of LWR benchmarks have been developed and successfully conducted. The first set of NEA/OECD benchmarks that permits testing of the neutronics/thermal-hydraulics coupling, and verifying the capability of the coupled codes to analyze complex transients with coupled core/plant interactions have been completed and documented. These benchmarks provided a validation basis for the new generation of coupled "best-estimate" codes. The above mentioned OECD/NEA LWR benchmark activities have also stimulated follow up developments and benchmarks to test these developments. The models utilized have been improved when moving from one benchmark to the next and this created a need to validate them using high-quality experimental data. Second set of the NEA/OECD benchmarks have been initiated by the Expert Group on Uncertainty Analysis in Modelling (EGUAM) at the Nuclear Science Committee (NSC), NEA/OECD to address the current trends in the development of LWR multi-physics and multi-scale modeling and simulation. These benchmarks include the following common features, which address some of the issues identified in the first set of OECD/NEA benchmarks: (a) utilization of high-quality experimental data; (b) refined local scale modeling in addition to global predictions; (c) more detailed comparisons and analysis; (d) including uncertainty and sensitivity analysis of modeling predictions. The paper presents each of these new benchmarks by providing description and discussion of comparative analysis of obtained results. Special attention is devoted to uncertainty propagation in LWR multi-physics and multi-scale simulations for design and safety evaluations. (c) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:178 / 196
页数:19
相关论文
共 50 条
  • [21] Multi-physics and Multi-scale Electromagnetic Modeling and High Performance Algorithms
    Wu, Yu Mao
    Jin, Ya-Qiu
    2019 INTERNATIONAL APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY SYMPOSIUM - CHINA (ACES), VOL 1, 2019,
  • [22] Multi-Scale, Multi-Physics NEGF Quantum Transport for Nitride LEDs
    Geng, Junzhe
    Sarangapani, Prasad
    Nelson, Erik
    Wordelman, Carl
    Browne, Ben
    Kubis, Tillmann
    Klimeck, Gerhard
    2016 INTERNATIONAL CONFERENCE ON NUMERICAL SIMULATION OF OPTOELECTRONIC DEVICES (NUSOD), 2016, : 107 - 108
  • [23] Advanced computations of multi-physics, multi-scale effects in beam dynamics
    Amundson, J. F.
    Macridin, A.
    Spentzouris, P.
    Stern, E. G.
    SCIDAC 2009: SCIENTIFIC DISCOVERY THROUGH ADVANCED COMPUTING, 2009, 180
  • [24] A multi-scale multi-physics modeling framework of laser powder bed fusion additive manufacturing process
    Zhang J.
    Zhang Y.
    Lee W.H.
    Wu L.
    Choi H.-H.
    Jung Y.-G.
    Zhang, Jing (jz29@iupui.edu), 2018, Elsevier Ltd (73) : 151 - 157
  • [25] Innovations in Multi-Physics Methods Development, Validation, and Uncertainty Quantification
    Avramova, Maria
    Abarca, Agustin
    Hou, Jason
    Ivanov, Kostadin
    JOURNAL OF NUCLEAR ENGINEERING, 2021, 2 (01): : 44 - 56
  • [26] UNCERTAINTY QUANTIFICATION IN METALLIC ADDITIVE MANUFACTURING THROUGH DATA-DRIVEN MODELLING BASED ON MULTI-SCALE MULTI-PHYSICS MODELS AND LIMITED EXPERIMENT DATA
    Wang, Zhuo
    Jiang, Chen
    Horstemeyer, Mark F.
    Hu, Zhen
    Chen, Lei
    PROCEEDINGS OF THE ASME 2020 15TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE (MSEC2020), VOL 1A, 2020,
  • [27] Multi-Scale, Multi-Physics Analysis for Device, Chip, Package, and Board Level
    Chew, Weng C.
    2012 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN (ICCAD), 2012, : 497 - 497
  • [28] OpenCMISS: A multi-physics & multi-scale computational infrastructure for the VPH/Physiome project
    Bradley, Chris
    Bowery, Andy
    Britten, Randall
    Budelmann, Vincent
    Camara, Oscar
    Christie, Richard
    Cookson, Andrew
    Frangi, Alejandro F.
    Gamage, Thiranja Babarenda
    Heidlauf, Thomas
    Krittian, Sebastian
    Ladd, David
    Little, Caton
    Mithraratne, Kumar
    Nash, Martyn
    Nickerson, David
    Nielsen, Poul
    Nordbo, Oyvind
    Omholt, Stig
    Pashaei, Ali
    Paterson, David
    Rajagopal, Vijayaraghavan
    Reeve, Adam
    Roehrle, Oliver
    Safaei, Soroush
    Sebastian, Rafael
    Steghoefer, Martin
    Wu, Tim
    Yu, Ting
    Zhang, Heye
    Hunter, Peter
    PROGRESS IN BIOPHYSICS & MOLECULAR BIOLOGY, 2011, 107 (01): : 32 - 47
  • [29] Multi-scale, multi-physics challenges for future aircraft and hierarchical zonal modelling
    Tucker, Paul G.
    ENGINEERING COMPUTATIONS, 2021, 38 (03) : 1187 - 1208
  • [30] Multi-scale and multi-physics: towards next-generation engineering materials
    Emilio Barchiesi
    Continuum Mechanics and Thermodynamics, 2020, 32 : 541 - 554