Published November 2020 | Version v1
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Compression of multi-physics simulation output data using Principle Component Analysis

  • 1. Ulsan National Institute of Science and Technology, Ulsan (Korea, Republic of)
  • 2. University of Technology Malaysia, Skudai, Johor (Malaysia)

Description

High-fidelity multi-physics reactor core simulation includes the pin-by-pin neutronics, thermal-hydraulics, thermal-mechanics and fuel performance physical models. Every run of a high-fidelity code consumes a lot of computation time, memory and usually requires an expansive multi-core computational cluster. All output data is to be saved for further analysis if one does not want to repeat the expansive calculations. The memory amount of high-fidelity output data can be too large, e.g. in the case of uncertainty analysis. Therefore, the data compression algorithms are needed for reduction of the memory without accuracy loose. In this paper we suggest such algorithm based on Principle Component Analysis (PCA) adopted for multi-physics data. (author)

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Part of:
Proceedings of reactor physics Asia conference 2019 (RPHA19)

Additional details

Publishing Information

Imprint Title
Proceedings of reactor physics Asia conference 2019 (RPHA19)
Imprint Pagination
[321 p.]
Journal Page Range
p. 170-174
Report number
KURNS-EKR--5

Conference

Title
Reactor physics Asia conference 2019
Acronym
RPHA19
Dates
2-3 Dec 2019
Place
Osaka (Japan)

Optional Information

Notes
11 refs., 4 figs., 2 tabs.