Optimization of thermal conductivity of UO2–Mo composite with continuous Mo channel based on finite element method and machine learning

Optimization of thermal conductivity of UO2–Mo composite with continuous Mo channel based on finite element method and machine learning

•A new finite element modeling method similar to ‘PixelMapPaint’ was introduced for UO2-Mo composite.•The thermal conductivity of UO2-2 vol% Mo optimized by machine learning was higher by about 20% than that of pure UO2.•A model for predicting thermal conductivity of anisotropy composite was built w...

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Veröffentlicht in:International journal of heat and mass transfer 2020-10, Vol.159, p.120067, Article 120067
Hauptverfasser: Yan, Biaojie, Gao, Rui, Liu, Pengchuang, Zhang, Pengcheng, Cheng, Liang
Format: Artikel
Sprache:eng
Schlagworte:
Finite element analysis
Finite element method
Heat conductivity
Heat transfer
Machine learning
Microstructure
Nuclear engineering
Nuclear fuels
Nuclear reactors
Nuclear safety
Optimization
Structural characteristics
Thermal conductivity
UO2-Mo composite
Uranium
Uranium dioxide
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Beschreibung
Zusammenfassung:•A new finite element modeling method similar to ‘PixelMapPaint’ was introduced for UO2-Mo composite.•The thermal conductivity of UO2-2 vol% Mo optimized by machine learning was higher by about 20% than that of pure UO2.•A model for predicting thermal conductivity of anisotropy composite was built with relative error
ISSN:0017-9310
1879-2189
DOI:10.1016/j.ijheatmasstransfer.2020.120067