论文标题
AI辅助的多尺度建模生理上重要的血凝块
AI-aided multiscale modeling of physiologically-significant blood clots
论文作者
论文摘要
我们已经开发了AI AID多时间步进（AI-MTS）算法和多尺度建模框架（AI-MSM），并在类似峰会的超级计算机AIMOS上实现了它们。 AI-MSM是将多物理集整合在内的第一个类型，包括插入物质内，平台间和流体 - 平台相互作用，纳入一个系统。它已经模拟了1.02亿个颗粒的记录的多尺度血液凝结模型，其中70个流动和180个聚集的血小板，在耗散粒子动力学下为粗粒分子动力学。通过自适应调整时间段尺寸以匹配基本动力学的特征时间尺度，AI-MTS最佳平衡了模拟的速度和准确性。
We have developed an AI-aided multiple time stepping (AI-MTS) algorithm and multiscale modeling framework (AI-MSM) and implemented them on the Summit-like supercomputer, AIMOS. AI-MSM is the first of its kind to integrate multi-physics, including intra-platelet, inter-platelet, and fluid-platelet interactions, into one system. It has simulated a record-setting multiscale blood clotting model of 102 million particles, of which 70 flowing and 180 aggregating platelets, under dissipative particle dynamics to coarse-grained molecular dynamics. By adaptively adjusting timestep sizes to match the characteristic time scales of the underlying dynamics, AI-MTS optimally balances speeds and accuracies of the simulations.
