HCC: Small: Collaborative Research: Asynchrony and Persistence for Complex Contact Simulations

HCC：小型：协作研究：复杂接触模拟的异步性和持久性

• 批准号: 0916129
• 负责人: Eitan Grinspun
• 金额: $ 24.92万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916129&HistoricalAwards=false
• 关键词: HCC; Small; Collaborative; Research; Asynchrony

IIS - 0916129 HCC: Small: Collaborative Research: Asynchrony and Persistence for Complex Contact SimulationsGrinspun, Eitan Columbia UniversityCollaborative ProposalsIIS - 0914833 Guibas, Leonidas J Stanford UniversityABSTRACTThis proposal addresses the challenge of complex contact simulations by working entirely in an asynchronous setting. The project operates along three lines, combining tools from Asynchronous Variational Integrators (AVIs) and Kinetic Data Structures (KDSs) with a novel effort to perform and exploit qualitative analysis of contact simulation data. The first investigation will show that AVIs, meant to handle the continuous aspects of the physics, can be integrated well with KDSs, meant to handle discrete geometric events. The second research component addresses the fundamental problem of event scheduling when future trajectories are uncertain. Methods will be explored that improve event detection times, reduce the number of auxiliary events that have to be processed, and allow events to be processed in parallel. The third research task will be to initiate a study of the qualitative behavior of contact simulation by building a hierarchy of coarser models which can then be used for better resource allocation, for the validation of various approximations, and in improved simulation design to attain desired effects.

IIS - 0916129 HCC：小型：协作研究：复杂接触模拟的异步性和持久性Grinspun，Eitan 哥伦比亚大学协作提案IIS - 0914833 Guibas，Leonidas J 斯坦福大学摘要该提案通过完全在异步设置中工作来解决复杂接触模拟的挑战。该项目沿着三个方向运作，将异步变分积分器 (AVI) 和动力学数据结构 (KDS) 的工具与执行和利用接触模拟数据的定性分析的新颖努力相结合。第一项研究将表明，用于处理物理连续方面的 AVI 可以与用于处理离散几何事件的 KDS 很好地集成。第二个研究部分解决了未来轨迹不确定时事件调度的基本问题。将探索改进事件检测时间、减少必须处理的辅助事件数量以及允许并行处理事件的方法。 第三个研究任务是通过建立较粗糙的模型层次结构来启动接触模拟的定性行为研究，然后将其用于更好的资源分配、验证各种近似值以及改进模拟设计以获得预期效果。