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CHS: Small: Novel methods for material point method simulations of multiphase fluids

CHS：小型：多相流体质点法模拟的新方法

基本信息

批准号：
2006570
负责人：
Craig Schroeder
金额：
$ 50万
依托单位：
University of California-Riverside
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2006570&HistoricalAwards=false
关键词：
CHS Small Novel methods material

项目摘要

The material point method (MPM) is a versatile computational tool for simulating solids, fluids, granular and complex materials in scientific and engineering applications where interactions between separate fluid phases, or between solids and fluids, play an important role. Cascading avalanches, solidifying lava, sandy pools, and gooey toothpaste are among the many physical phenomena that can be simulated with MPM, which is therefore used extensively for engineering applications and physics-based animation. But the method suffers from problems of nonphysical particle mixing and thus presents challenges in the simulation of multiphase fluids and solid-fluid interaction phenomena. This research will alleviate these issues by enabling the coupling of fluids with granular materials (sand, snow, soil liquefaction) as well as complex materials that exhibit solid-like and fluid-like properties (gels, foams), combinations that are common in civil engineering where sedimentation and wind and water erosion are major concerns for bridge and dam constructions. Similarly, air-snow coupling is important for modeling avalanches and pyroclastic flows, where it can be used to make life-saving predictions. The algorithms produced as part of this project will be publicly released to encourage adoption, reproduction, and further advancements. Additional broad impacts will derive from integration of the research into the team's training, educational, and outreach efforts to students at both the undergraduate and graduate levels in their university, which is a research-intensive Hispanic Serving Institution.While the hybrid particle/grid framework of MPM underpins its strengths, it also leads to a major downside: particles from different materials tend to mix and stick together in ways that are physically impossible. This limits the accuracy of MPM in simulating multiphase fluid and solid-fluid coupling phenomena. To alleviate this deficiency, three novel algorithms will be developed. First, a novel buoyancy force correction on particles will allow for unmixing of multiphase fluids based on density differences. Second, a surface tension algorithm for multiphase fluids based on particle interactions will encourage unmixing by decoupling constitutive models of materials from interaction forces between different materials. The third algorithm will extend the second to general constitutive models, to simulate problems of solid-fluid coupling where particles interact with solids, thereby allowing MPM to be used for multiphase fluids and solid-fluid coupling without the need to maintain or construct a separate surface representation; notably, the unmixing forces are purely meshless and do not rely on any explicit representation for the boundary, which avoids the difficulties of computing accurate curvature from the reconstructed surface. Compared with existing pairwise formulations of surface tension forces, this work will use a statistical formulation for an equation of state to avoid pairwise interactions except near the interface, thereby drastically reducing the computational cost and allowing accurate results to be obtained even with heavily mixed particle configurations where no meaningful surface representation exists, something existing formulations cannot do without violating conservation laws. It is furthermore expected that this approach will automatically capture wetting due to surface tension without any special modeling.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

物质点法（MPM）是一种通用的计算工具，用于模拟科学和工程应用中的固体，流体，颗粒和复杂材料，其中分离的流体相之间或固体和流体之间的相互作用起着重要作用。雪崩、凝固的熔岩、桑迪池和粘糊糊的牙膏都是可以用MPM模拟的许多物理现象，因此MPM广泛用于工程应用和基于物理的动画。但该方法存在非物理颗粒混合的问题，因此在多相流体和固-流相互作用现象的模拟中提出了挑战。这项研究将缓解这些问题，使流体与颗粒材料（沙，雪，土壤液化）以及表现出固体和流体性质的复杂材料（凝胶，泡沫）的耦合，这些组合在土木工程中很常见，其中沉积和风和水的侵蚀是桥梁和大坝建设的主要问题。同样，气-雪耦合对于雪崩和火山碎屑流的建模也很重要，可以用来进行救生预测。作为该项目的一部分产生的算法将公开发布，以鼓励采用，复制和进一步发展。其他广泛的影响将来自于研究整合到团队的培训，教育和推广工作，以学生在本科和研究生水平在他们的大学，这是一个研究密集型的西班牙裔服务机构。虽然MPM的混合粒子/网格框架巩固了其优势，它也导致了一个主要的缺点：来自不同材料的颗粒倾向于以物理上不可能的方式混合和粘在一起。这限制了MPM在模拟多相流和固流耦合现象时的精度。为了缓解这一缺陷，将开发三种新型算法。首先，对颗粒的新浮力校正将允许基于密度差的多相流体的非混合。第二，基于颗粒相互作用的多相流体的表面张力算法将通过将材料的本构模型与不同材料之间的相互作用力解耦来鼓励解混。第三种算法将第二种扩展到一般的本构模型，以模拟颗粒与固体相互作用的固-流耦合问题，从而允许MPM用于多相流体和固-流耦合，而不需要保持或构造单独的表面表示;值得注意的是，分离力是纯无网格的，并且不依赖于边界的任何显式表示，这避免了从重构表面计算精确曲率的困难。与现有的表面张力的成对公式相比，这项工作将使用状态方程的统计公式，以避免除了界面附近的成对相互作用，从而大大降低计算成本，并允许获得准确的结果，即使在没有有意义的表面表示存在的情况下，现有的配方不能不违反守恒定律。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。