Efficient Conservative High-Order Solution-Flux Domain Decomposition Methods and Local Refinements for Flows in Porous Media and Electromagnetics

多孔介质和电磁学中流动的高效保守高阶解-通量域分解方法和局部细化

• 批准号: RGPIN-2022-04571
• 负责人: Liang, Dong
• 金额: $ 1.31万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=759038
• 关键词: Efficient; Conservative; Order; Solution; Flux

Modeling contamination flow in porous media plays a crucial role in understanding and predicting complex physical, chemical and flow processes, as well as in preventing and controlling pollution in groundwater modeling and environmental protection. Modeling the propagation of electromagnetic waves is also critically important for many applications of electromagnetic science. Recent rapid growth in the use of electromagnetics in materials and metamaterials includes biomedical imaging and processing, radio-frequency identification (RFID), wireless power transmission, holographic processing, nanolithography, and cloaking devices, etc. The mathematical models describing these processes are complex and there are challenges in the development of accurate methods that preserve the important natural physical properties.  When modeling contamination flows in porous media, mathematical models are nonlinear systems of coupled partial differential equations (PDEs) that involve challenging features such as transport dominance, moving steep fronts, nonlinearity, adsorption, interface and heterogeneity. Solving these problems is driving the development and analysis of efficient, accurate, and conservative domain decomposition methods for long-term, large-scale field prediction problems in parallel computing.  Since modeling faces with the challenges of micro-scale, local solution behavior, complex and refined structure, and long-time response, it is of utmost importance to develop efficient and conservative local mesh-refined methods for electromagnetics. The proposed research program includes: (1) Develop time second-order conservative characteristic domain decomposition methods for contamination porous media flows; (2) Develop conservative fourth-order block-centered compact-difference solution-flux domain decomposition method for contamination flows; (3) Develop energy-preserving local mesh-refined fourth-order S-FDTD schemes for Maxwell's equations; (4) Develop energy-preserving curvilinear-coordinated local mesh-refined S-FDTD schemes for electromagnetics; and (5) Develop global energy-preserving local mesh-refined S-FDTD schemes for metamaterial electromagnetics. The research program will benefit Canada through the establishment of methods, theories, algorithms and applications of conservative domain decomposition and local refinement techniques for computational fluid dynamics in porous media and computational electromagnetics. It will also train students and postdocs to meet the growing demand for highly qualified personnel in the environmental and electromagnetic industries and in the computing technology.

多孔介质中的污染流建模对于理解和预测复杂的物理、化学和流动过程以及地下水建模和环境保护中的污染预防和控制起着至关重要的作用。电磁波传播建模对于电磁科学的许多应用也至关重要。最近，电磁学在材料和超材料中的应用迅速增长，包括生物医学成像和处理、射频识别 (RFID)、无线电力传输、全息处理、纳米光刻和隐形装置等。描述这些过程的数学模型非常复杂，在开发保留重要自然物理特性的精确方法方面存在挑战。  在对多孔介质中的污染物流进行建模时，数学模型是耦合偏微分方程 (PDE) 的非线性系统，涉及具有挑战性的特征，例如传输优势、移动陡峭锋面、非线性、吸附、界面和异质性。解决这些问题正在推动针对并行计算中长期、大规模现场预测问题的高效、准确和保守的域分解方法的开发和分析。  由于建模面临着微观尺度、局部解行为、复杂精细结构和长时间响应的挑战，因此开发高效且保守的电磁学局部网格细化方法至关重要。拟研究项目包括：（1）开发污染多孔介质流的时间二阶保守特征域分解方法； (2) 发展保守的四阶块中心紧致差分解-通量域污染流分解方法； (3) 为麦克斯韦方程组开发能量守恒的局部网格细化四阶S-FDTD方案； (4) 开发电磁学节能曲线协调局部网格细化S-FDTD方案； (5) 开发超材料电磁学的全局节能局部网格细化 S-FDTD 方案。该研究计划将通过建立多孔介质计算流体动力学和计算电磁学的保守域分解和局部细化技术的方法、理论、算法和应用，使加拿大受益。它还将培训学生和博士后，以满足环境和电磁行业以及计算技术领域对高素质人才不断增长的需求。