在有限的纳米通道中提取流体特性,使用分子动力学和象征回归方法
Dimitrios Angelis1, Filippos Sofos1, Konstantinos Papastamatiou1
1Condensed Matter Physics Laboratory, Department of Physics, University of Thessaly, 35100 Lamia, Greece.
Micromachines
|July 29, 2023
概括
本研究引入了符号回归来计算流体传输系数和滑动长度. 这种方法从模拟数据中得出准确的,可解释的方程,从而降低了计算成本.
科学领域:
- 流体动力学 流体动力学
- 计算物理学的计算物理.
- 机器学习 机器学习
背景情况:
- 在纳米导管中计算流体传输系数和滑动长度是计算密集的.
- 这些特性取决于复杂的动态,热和几何因素.
- 现有的方法往往需要进行广泛的模拟.
研究的目的:
- 提出一种替代的,计算效率高的方法来确定流体传输系数和滑动长度.
- 使用遗传编程来导出可解释的,数据驱动的数学表达式.
- 确保导出方程遵守物理原理和现有的领域知识.
主要方法:
- 利用基于遗传编程的象征回归.
- 将该方法应用于分子动力学模拟数据.
- 专注于引出物理可解释的数学表达式.
主要成果:
- 开发了一套准确且不那么复杂的数学方程.
- 所得的方程实际上代表了流体的运输特性.
- 证明了绕过耗时模拟的潜力.
结论:
- 符号回归为计算流体特性提供了一个强大的替代方案.
- 导出方程促进了高效的流体属性插值和外推.
- 这种方法增强了对纳米导管中的流体行为的理解和应用.
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