Neural network method for solving parabolic two-temperature microscale heat conduction in double-layered thin films exposed to ultrashort-pulsed lasers

被引：16

作者：

Bora, Aniruddha ^{[1
]}

Dai, Weizhong ^{[1
]}

Wilson, Joshua P. ^{[1
]}

Boyt, Jacob C. ^{[1
]}

机构：

[1] Louisiana Tech Univ, Math & Stat, Coll Engn & Sci, Ruston, LA 71272 USA

来源：

INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER | 2021年 / 178卷

关键词：

Micro; nanoscale heat conduction; Ultrashort-pulsed laser heating; Artificial neural network method; Convergence; Thin film; FINITE-DIFFERENCE SCHEME; HYPERBOLIC 2-STEP MODEL; CONVERGENCE CONDITIONS; TRANSPORT-EQUATIONS; THERMAL-BEHAVIOR; FRAMEWORK; METALS;

D O I：

10.1016/j.ijheatmasstransfer.2021.121616

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

Simulation of the micro/nanoscale heat conduction induced by ultrashort-pulsed laser heating has been attracting great attention. Additionally, machine and deep learning techniques are becoming an important tool in engineering and science research. This article presents an artificial neural network (ANN) method for solving the parabolic two-temperature heat conduction equations in double-layered thin films exposed to ultrashort-pulsed lasers. Convergence of the ANN solution to the analytical solution is theoretically analyzed. Finally, the ANN method is used to predict the electron and lattice temperatures in a gold film padding on a chromium film when exposed to ultrashort-pulsed lasers, which is based on the parabolic two-temperature heat conduction model. (c) 2021 Elsevier Ltd. All rights reserved.

引用

页数：13

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