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Parameterizing the Morse Potential for Coarse-Grained Modeling of Blood Plasma

机译:参数化莫尔斯电势用于粗粒化血浆模型

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摘要

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters are systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.
机译:诸如血液之类的流体的多尺度模拟代表了在表征此类复杂流体的分子和宏观运输现象之间耦合不同时空尺度的主要计算挑战。在本文中,开发了一种粗粒(CG)粒子模型,用于通过修改Morse势来模拟血流,Morse势通常用于“分子动力学”中,用于对振动结构进行建模。修改后的莫尔斯电势可通过有效质量标尺进行参数化,以重现血液粘性流动特性,包括密度,压力,粘度,可压缩性和人体血浆流体的特征流动动力学。参数化遵循标准的反问题方法,在该方法中,通过逐渐将松散相关的参数空间去耦,系统地搜索最佳的微观参数,以匹配粘性血流的宏观物理量。该基于粒子的多尺度模型的预测与经典粘性流解决方案(例如Counter-Poiseuille和Couette流)相比具有优势。它证明了这种粗糙的颗粒模型可以被应用来复制粘性血流的动力学,其优点是弥合了宏观血流规模和表征血流的细胞规模之间的差距,而连续血流模型无法充分处理这种情况。

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