Use of massively parallel computing to improve modelling accuracy within the nuclear sector

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Evans, Li M. et al.: Use of massively parallel computing to improve modelling accuracy within the nuclear sector. In: International Journal of Mulitphysics 10 (2016), Nr. 2, S. 215-236. DOI: http://dx.doi.org/10.21152/1750-9548.10.2.215

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/4811

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Sum total of downloads: 116




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Abstract: 
The extreme environments found within the nuclear sector impose large safety factors on modelling analyses to ensure components operate in their desired manner. Improving analysis accuracy has clear value of increasing the design space that could lead to greater efficiency and reliability. Novel materials for now reactor designs often exhibit nonlinear behaviouradditionally material properties evolve due to in-service damage a combination that is difficult to model accurately. To better describe these complex behaviours a range of modelling techniques previously under pursued due to computational expense are being developed. This work presents recent advancements in three techniques: Uncertainty quantification (UQ). Cellular automata finite element (CAFE)Image based finite element methods (IBFEM). Case studies are presented demonstrating their suitability for use in nuclear engineering made possible by advancements in parallel computing hardware that is projected to be available for industry within the next decade costing of the order of $100k.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2016
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 47 40.52%
2 image of flag of United States United States 36 31.03%
3 image of flag of China China 8 6.90%
4 image of flag of United Kingdom United Kingdom 5 4.31%
5 image of flag of Czech Republic Czech Republic 5 4.31%
6 image of flag of Russian Federation Russian Federation 2 1.72%
7 image of flag of India India 2 1.72%
8 image of flag of Canada Canada 2 1.72%
9 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 1 0.86%
10 image of flag of Bulgaria Bulgaria 1 0.86%
    other countries 7 6.03%

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