通过进化模糊聚类对流体粒子进行粗粒度映射:作为压力校正机制的成员-进化术语
Jiale Han1, Yixuan Feng1, Jian Wu2
1State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China.
Journal of chemical theory and computation
|February 27, 2026
概括
我们开发了一种使用模糊聚类和时光光滑的新粗粒度方法. 这种方法通过考虑粒子分离和准确地恢复系统压力来改善流体粒子描述.
科学领域:
- 计算物理学的计算物理.
- 化学物理 化学物理
- 材料科学是一种材料科学.
背景情况:
- 在流体模拟中,粗粒度 (CG) 方法可以跨越原子和介面尺度.
- 固定的CG映射与流体粒子的动态,不捆绑的性质作斗争.
研究的目的:
- 开发一种改进的CG方法,解决固定映射的局限性.
- 调查模糊粒子集群成员的演变对CG准确性的影响.
- 建立CG流体动力学压力校正的自下而上的方法.
主要方法:
- 采用了一个调节的模糊集群算法,具有时间光滑约束.
- 力量匹配框架将集群相互作用分解为粒子相互作用和成员进化术语.
- 该方法应用于Lennard-Jones (L-J) 流体和水系统.
主要成果:
- 一个中间的模糊度水平优化了辐射分布函数中的结构特征.
- 成员资格-进化术语始终在各个系统中贡献了一种排斥力.
- 包括CG动力学模拟中的会员演变术语,恢复了L-J流体的系统压力.
结论:
- 拟议的模糊聚类CG方法提高了结构描述和流体中的压力精度.
- 会员演变术语提供了一个物理接地压力校正机制.
- 这项工作为设计流体系统的先进粗粒度策略提供了洞察力.
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