A Gaussian process regression accelerated multiscale model for conduction-radiation heat transfer in periodic composite materials with temperature-dependent thermal properties

A Gaussian process regression accelerated multiscale model for conduction-radiation heat transfer in periodic composite materials with temperature-dependent thermal properties

Abstract Prediction of the coupled conduction-radiation heat transfer in composite materials with periodic structure is important in high-temperature applications of the materials. The temperature dependence of thermal properties complicates the problem. In this work, a multiscale model is proposed...

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Bibliographic Details
Main Authors: Zi-Xiang Tong, Ming-Jia Li, Zhaolin Gu, Jun-Jie Yan, Wen-Quan Tao
Format: Article
Language:English
Published: SpringerOpen 2022-09-01
Series:Advances in Aerodynamics
Subjects:
Multiscale model
Heat Conduction
Radiative transfer equation
Temperature-dependent
Gaussian process regression
Machine learning
Online Access:https://doi.org/10.1186/s42774-022-00122-0

Internet

https://doi.org/10.1186/s42774-022-00122-0

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