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首页> 外文期刊>International Journal of Heat and Mass Transfer >Neural network method for solving parabolic two-temperature microscale heat conduction in double-layered thin films exposed to ultrashort-pulsed lasers
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Neural network method for solving parabolic two-temperature microscale heat conduction in double-layered thin films exposed to ultrashort-pulsed lasers

机译：用于求解抛光型薄膜的抛物线两温微尺度热传导的神经网络方法，暴露于超短脉冲激光器

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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.
机译：超短脉冲激光加热引起的微/纳米尺度的微/纳米级热传导的模拟一直吸引了极大的关注。 此外，机器和深度学习技术正在成为工程和科学研究的重要工具。 本文介绍了一种人工神经网络（ANN）方法，用于求解暴露于超短脉冲激光器的双层薄膜中的抛物线两温导热方程。 理论上分析了ANN解决方案的ANN解决方案的收敛性。 最后，ANN方法用于预测当暴露于超短脉冲激光器的铬膜上的金膜填充中的电子和晶格温度，这是基于抛物线的双温热导热模型。

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