Collaborative Research: Efficient, Accurate, and Structure-Preserving Numerical Methods for Phase Fields-Type Models with Applications

合作研究：高效、准确、结构保持的相场型模型数值方法及其应用

• 批准号: 2012634
• 负责人: Steven Wise
• 金额: $ 20万
• 依托单位: University of Tennessee Knoxville
• 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: 2020-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2012634&HistoricalAwards=false
• 关键词: Collaborative; Research; Efficient; Accurate; Structure

The project will develop computational methods for simulations of phase transformations in materials at the atomic and nanometer scales, aiming at understanding behavior at large time scales. With these simulations, the project will contribute to the understanding of processes such as complex biological growth and cancer, multi-phase active-particle and ionic fluids relevant in biological growth and development, and in the study of other complex phenomena in physics, and material engineering. The focus will be on a particular class of models: gradient flow equations with singular energy potentials. The project will develop theory and software; the codes developed in this project will be scaled up to conduct real-world three-dimensional simulations. In addition, some numerical algorithms to be developed could impact the field of deep learning. This project will provide interdisciplinary applied mathematics and scientific computing training and research experiences for both graduate and undergraduate students at the two institutions involved.In the proposed gradient flow models, a singularity is involved in the energy potential, so that the positivity-preserving property becomes a crucial feature to make the numerical approximation well-defined. In addition, energy stability and optimal rate convergence analysis will be considered for these gradient model with singular energy potential, such as the doubly degenerate Cahn-Hilliard model describing surface diffusion, a new phase field crystal model with heat transport for simulating solidification, a new quasi-incompressible Cahn-Hilliard-Navier-Stokes model for two-phase density mismatched flow, the Poisson-Nernst-Plank model for ionic mixtures, and multi-phase magneto-hydrodynamics equations. Novel finite difference, mixed finite element, and/or Fourier pseudo-spectral spatial approximations will be utilized. Convergence analysis up to the third order temporal accuracy will be investigated in details, which will be the first such work for gradient flows with singular potential. Moreover, numerical solvers for these highly nonlinear schemes will be designed and analyzed, based on the preconditioned steepest decent and Nesterov accelerated methods. Highly efficient adaptive nonlinear multigrid methods based will also be tested and studied in details.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.

该项目将开发用于在原子和纳米尺度上模拟材料相变的计算方法，旨在了解大时间尺度上的行为。通过这些模拟，该项目将有助于理解复杂的生物生长和癌症、与生物生长和发育相关的多相活性粒子和离子流体等过程，以及物理和材料工程中其他复杂现象的研究。重点将放在一类特殊的模型上：具有奇异能量势的梯度流动方程。该项目将开发理论和软件；在这个项目中开发的代码将扩大规模，以进行现实世界的三维模拟。此外，一些正在开发的数值算法可能会影响深度学习领域。该项目将为两所院校的研究生和本科生提供跨学科的应用数学和科学计算培训和研究经验。在所提出的梯度流模型中，由于能量势中存在一个奇点，因此保持正性成为使数值近似定义良好的关键特征。此外，对于具有奇异能量势的梯度模型，如描述表面扩散的双简并Cahn-Hilliard模型、模拟凝固的具有热输运的新相场晶体模型、模拟两相密度不匹配流动的新的准不可压缩Cahn-Hilliard- navier - stokes模型、离子混合物的Poisson-Nernst-Plank模型等，将考虑能量稳定性和最优速率收敛性分析。多相磁流体力学方程。新的有限差分、混合有限元和/或傅立叶伪谱空间近似将被利用。将详细研究三阶时间精度的收敛分析，这将是具有奇异势的梯度流的首次此类工作。此外，这些高度非线性格式的数值解将设计和分析，基于预条件的最陡和Nesterov加速方法。本文还对基于高效自适应非线性多重网格的方法进行了详细的测试和研究。该奖项反映了美国国家科学基金会的法定使命，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。

项目成果

A Third Order Accurate in Time, BDF-Type Energy Stable Scheme for the Cahn-Hilliard Equation

• DOI: 10.4208/nmtma.oa-2021-0165
• 发表时间: 2022-06
• 期刊: Numerical Mathematics: Theory, Methods and Applications
• 作者: Kelong Cheng;Cheng Wang;S. Null;Yanmei Wu

Doubly degenerate diffuse interface models of surface diffusion

• DOI: 10.1002/mma.7116
• 发表时间: 2019-09
• 期刊: Mathematical Methods in the Applied Sciences
• 影响因子: 2.9
• 作者: M. Salvalaglio;A. Voigt;S. Wise

Preconditioned Accelerated Gradient Descent Methods for Locally Lipschitz Smooth Objectives with Applications to the Solution of Nonlinear PDEs

• DOI: 10.1007/s10915-021-01615-8
• 发表时间: 2020-06
• 期刊: Journal of Scientific Computing
• 影响因子: 2.5
• 作者: Jea-Hyun Park;A. Salgado;S. Wise

Structure-preserving, energy stable numerical schemes for a liquid thin film coarsening model

液体薄膜粗化模型的结构保持、能量稳定数值方案

• DOI: 10.1137/20m1375656
• 发表时间: 2020-12
• 期刊: SIAM Journal on Scientific Computing
• 影响因子: 3.1
• 作者: Juan Zhang;Cheng Wang;Steven M. Wise;Zhengru Zhang
• 通讯作者: Zhengru Zhang

A positivity-preserving, energy stable scheme for a ternary Cahn-Hilliard system with the singular interfacial parameters

具有奇异界面参数的三元 Cahn-Hilliard 系统的保正性、能量稳定方案

• DOI: 10.1016/j.jcp.2021.110451
• 发表时间: 2021-06-08
• 期刊: JOURNAL OF COMPUTATIONAL PHYSICS
• 影响因子: 4.1
• 作者: Dong, Lixiu;Wang, Cheng;Zhang, Zhengru
• 通讯作者: Zhang, Zhengru