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• W4282942719 startingPage "106182" @default.
• W4282942719 abstract "Realizing accurate measurement for thermal contact conductance (TCC) is difficult and needs many additional measurements. In this paper, we design a three-layer back propagation artificial neural network (ANN) model to retrieve TCC of two contact solid specimens. The model can retrieve TCC only according to the measured temperatures and loading pressures, and the effects of loading pressure, temperature and surface roughness on TCC are considered. Besides, thermal conductivity, heat flux and the parameter of the TCC empirical fitting formula can be obtained simultaneously. The retrieved results are validated by experimental values. The results show that for two contact pairs with different surface roughness, the retrieved parameters of TCC empirical fitting formula are clear reasonable and can be explained conceptually compared with the published studies." @default.
• W4282942719 created "2022-06-16" @default.
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• W4282942719 date "2022-07-01" @default.
• W4282942719 modified "2023-09-25" @default.
• W4282942719 title "Exploring thermal contact conductance between two contact solids by artificial neural network" @default.
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• W4282942719 doi "https://doi.org/10.1016/j.icheatmasstransfer.2022.106182" @default.
• W4282942719 hasPublicationYear "2022" @default.
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