CHS: Small: Physically-Based Simulation of Strand-Liquid Interaction

CHS：小型：线-液体相互作用的基于物理的模拟

• 批准号: 1717178
• 负责人: Eitan Grinspun
• 金额: $ 35.4万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1717178&HistoricalAwards=false
• 关键词: CHS; Small; Physically; Based; Simulation

This project develops algorithms that predict the dynamics of liquids interacting with thin flexible strands. The interaction of strands with each other, and with liquids, is a fundamental physical consideration in myriad contexts. Therefore, the development of computer algorithms that can predict the physics of liquid-strand interaction has the potential to spur advances in many important scientific and engineering fields of investigation. New algorithms are needed to improve realism in virtual reality, one of the grand challenges in engineering as recognized by the National Academy of Engineering, and also to advance important problems in biology, transoceanic communications, robotics, graphical animation, and industrial product design. A fundamental challenge addressed by this project is accounting for the many ways in which liquids and strands interact. These interactions involve numerous physical ingredients at distinct spatiotemporal scales. Efficient integration of these components in numerical algorithms remains an important and challenging problem. Solving this problem will involve development of algorithms that model complex, multi-scale, multi-physics systems. The process of designing such algorithms will itself produce new insights transferrable across scientific, engineering, and creative disciplines. Students trained by this project will become highly skilled in developing, extending, and harnessing numerical and graphical algorithms for applications spanning the natural sciences and engineering. The investigators will encourage participation from underrepresented groups at the doctoral, masters, and undergraduate levels.The research studies numerical modeling of liquid-strand interactions involving the consideration of multiple physical ingredients, including strand elasticity, liquid inertia, capillary action, wetting-induced tribological changes, inter-strand contact and friction, as external forces like gravity, and dimensionless groups, at multiple spatiotemporal scales, and over transient periods. Unlike existing methods that model certain specific processes in isolation, this project emphasizes broad-purpose simulation of liquid-strand interaction. This focus requires thoughtful selection of a computer model for each physical ingredient, as well as special attention to compatibility between choices, so that reconciliation of all the ingredients in different combinations becomes tractable. In particular, this project will be carried out with two major thrusts, namely, the numerical modeling of strands interacting with Newtonian and Non-Newtonian fluids. These thrusts will also crosscut research on robust simulation of hair contacts and performance acceleration for interactive simulation.

该项目开发了预测液体与柔韧细丝相互作用动力学的算法。在许多情况下，线与线之间以及与液体之间的相互作用是一个基本的物理问题。因此，能够预测液链相互作用的物理性质的计算机算法的发展有可能刺激许多重要的科学和工程研究领域的进展。需要新的算法来提高虚拟现实的真实感，这是美国国家工程院认可的工程领域的重大挑战之一，同时也需要新的算法来推进生物学、跨洋通信、机器人、图形动画和工业产品设计等领域的重要问题。该项目解决的一个基本挑战是解释液体和链相互作用的多种方式。这些相互作用涉及不同时空尺度上的许多物理成分。在数值算法中如何有效地整合这些成分仍然是一个重要而富有挑战性的问题。要解决这个问题，需要开发算法来模拟复杂、多尺度、多物理系统。设计这种算法的过程本身将产生新的见解，可在科学、工程和创造性学科之间转移。通过该项目训练的学生将在开发、扩展和利用数值和图形算法方面具有很高的技能，这些算法将用于跨越自然科学和工程的应用。研究人员将鼓励未被充分代表的群体在博士、硕士和本科阶段的参与。该研究研究了液-链相互作用的数值模拟，包括考虑多种物理成分，包括链弹性、液体惯性、毛细作用、润湿引起的摩擦变化、链间接触和摩擦，以及重力等外力和无因次群，在多个时空尺度和瞬态时间内。与现有的方法不同，这些方法孤立地模拟某些特定的过程，该项目强调液体-链相互作用的广泛模拟。这种关注需要为每种物理成分深思熟虑地选择计算机模型，并特别注意选择之间的兼容性，以便在不同组合中协调所有成分变得易于处理。特别是，这个项目将有两个主要的推力，即股与牛顿流体和非牛顿流体相互作用的数值模拟。这些研究也将交叉研究头发接触的鲁棒模拟和交互模拟的性能加速。

项目成果

Hybrid discrete-continuum modeling of shear localization in granular media

• DOI: 10.1016/j.jmps.2021.104404
• 发表时间: 2021-03
• 期刊: Journal of The Mechanics and Physics of Solids
• 影响因子: 5.3
• 作者: Peter Yichen Chen;Maytee Chantharayukhonthorn;Yonghao Yue;E. Grinspun;K. Kamrin

Natural Boundary Conditions for Smoothing in Geometry Processing

• DOI: 10.1145/3186564
• 发表时间: 2017-07
• 期刊: ACM Transactions on Graphics (TOG)
• 作者: Oded Stein;E. Grinspun;M. Wardetzky;Alec Jacobson

A Simple Discretization of the Vector Dirichlet Energy

• DOI: 10.1111/cgf.14070
• 发表时间: 2020-08
• 期刊: Computer Graphics Forum
• 影响因子: 2.5
• 作者: Oded Stein;M. Wardetzky;Alec Jacobson;E. Grinspun

A multi-scale model for simulating liquid-hair interactions

• DOI: 10.1145/3072959.3073630
• 发表时间: 2017-07
• 期刊: ACM Transactions on Graphics (TOG)
• 作者: Yun Fei;H. Maia;Christopher Batty;Changxi Zheng;E. Grinspun

A multi-scale model for coupling strands with shear-dependent liquid

• DOI: 10.1145/3355089.3356532
• 发表时间: 2019-11
• 期刊: ACM Transactions on Graphics (TOG)
• 作者: Yun Fei;Christopher Batty;E. Grinspun;Changxi Zheng