TEMPERATURE FLIED RAPID ESTIMATION OF SPACE NUCLEAR THERMIONIC REACTOR BASED ON REDUCED-ORDER MODEL

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In order to overcome the shortcomings of Computational Fluid Dynamics (CFD), which needs to consume a lot of computational resources and time to obtain the flow field information. In this paper, a non-intrusive reduced-order model was developed based on the POD an BP neural network. Then the established ROM was applied in the temperature filed rapid estimation of the space thermionic reactor, TOPAZ-II. ANSYS Fluent are used to obtain the data snapshot samples of the temperature field of TOPAZ-II. Under the new operating conditions, the temperature field was rapidly reconstructed by training-completed ROM. The ROM was validated by comparing the ROM results with Fluent results. The maximum absolute error of temperature is 0.2 K with speed-up on the order 4.8 × 103. Therefore, the methodology in this paper provides a reference for real-time monitoring of the thermionic reactor operation in orbit.

Original languageEnglish
Title of host publicationThermal-Hydraulics and Safety Analysis
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791888261
DOIs
StatePublished - 2024
Event2024 31st International Conference on Nuclear Engineering, ICONE 2024 - Prague, Czech Republic
Duration: 4 Aug 20248 Aug 2024

Publication series

NameProceedings of 2024 31st International Conference on Nuclear Engineering, ICONE 2024
Volume6

Conference

Conference2024 31st International Conference on Nuclear Engineering, ICONE 2024
Country/TerritoryCzech Republic
CityPrague
Period4/08/248/08/24

Keywords

  • Proper orthogonal decomposition (POD)
  • Rapid estimation
  • Reduced-order model(ROM)
  • Space Nuclear Thermionic Reactor
  • Temperature field

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