重新评估流体的运输特性:一种象征回归方法
Dimitrios Angelis1, Filippos Sofos1, Theodoros E Karakasidis1
1Condensed Matter Physics Laboratory, Department of Physics, University of Thessaly, Lamia 35100, Greece.
Physical review. E
|February 17, 2024
概括
符号回归 (SR) 准确地模拟了流体的传输特性,如粘度和热导率. 这种数据驱动的方法在整个相空间中提供了透明,可解释和计算高效的分析表达式.
科学领域:
- 热力学和统计力学的热力学.
- 计算物理 计算物理
- 材料科学 材料科学 材料科学
背景情况:
- 精确预测流体传输特性 (粘度,热导率) 对各种科学和工程应用至关重要.
- 像分子动力学模拟这样的传统方法是计算密集且耗时的.
- 现有的理论和实证模型可能缺乏准确性或在不同的流体状态上广泛适用性.
研究的目的:
- 为流体运输特性开发准确,透明和计算效率高的闭式表达式.
- 使用符号回归 (SR) 来从原子级模拟数据中提取这些关系.
- 为整个相位空间 (稀释气体到密集液体) 提供估计属性的方法.
主要方法:
- 在从原子尺度模拟中生成的数据上使用符号回归 (SR) 技术.
- 提取粘度和导热系数的闭式分析表达式.
- 根据既定的理论,经验和近似方程验证衍生关系.
主要成果:
- 符号回归成功地产生了粘度和导热性的封闭形式关系.
- 衍生的表达式显示了与现有模型相比较的高准确性.
- 提出了新的分析表达式,可用于整个相位空间,仅使用密度和温度.
结论:
- 符号回归提供了一个强大的,数据驱动的方法,用于导出准确和可解释的流体运输属性模型.
- 提出的分析表达式为昂贵的模拟提供了一个计算效率高的替代方案.
- 这种方法有助于更深入地了解控制流体行为的潜在物理机制.
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