Innovative Time Integrators for Stiff and Highly Oscillatory Systems

科学和工程的进步越来越需要快速准确的计算方法来模拟复杂的多物理过程及其在广泛的时间尺度或高频率下发生的相互作用。数值天气预报和气候建模是依赖原始方程的计算解的此类应用的显著示例，原始方程用于预测大气、海洋、陆地表面、冰等的行为，以及它们之间复杂的相互作用。这种多物理场问题的数值解仍然是一项具有挑战性的任务，由于存在多个时间尺度的系统中，不同的过程需要不同的时间来完成。因此，开发能够提供快速可靠解决方案的先进数值方法对于许多依赖复杂系统大规模模拟的应用至关重要。该项目的总体目标是为刚性和高振荡系统开发新的时间积分方法，并在数值天气预报，海洋建模和分子动力学模拟等应用中展示其性能。此外，该项目旨在培养一名博士生，并为密西西比州立大学的数学本科生和研究生提供机会。预计至少有一名研究生就拟议工作的主题进行培训。该项目有四个主要目标。首先，研究者将推导出新的混合指数积分器和预处理的有理指数积分器的刚性系统，并实现它们。其次，研究人员将开发刚性准确的嵌入式多速率指数方法添加分区系统。第三，研究人员将开发严格精确的指数Nyström方法。第四，研究人员将研究新开发的方法在数值天气预报，海洋建模和分子动力学模拟中的应用性能。研究人员将建立在他以前的专业知识，在构建，分析和实施指数和多速率时间积分方法，以实现这些目标。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。

Advancements in science and engineering increasingly require fast and accurate computational methods for simulating complex multi-physical processes and their interactions occurring at a wide range of temporal scales or high frequencies. Numerical weather prediction and climate modeling are notable examples of such applications that rely on the computational solution of primitive equations, which are used to predict the behavior of the atmosphere, oceans, land surface, ice, etc., as well as the complex interactions among them. Numerical solutions of such multiphysics problems remain a challenging task due to the presence of multiple time scales in the system where different processes take different amounts of time to complete. As such, developing advanced numerical methods capable of offering fast and reliable solutions is crucial for many applications that rely on large-scale simulations of complex systems. The overall goal of this project is to develop novel time integration methods for stiff and highly oscillatory systems and demonstrate their performance on applications such as numerical weather prediction, ocean modeling, and molecular dynamics simulations. Additionally, the project aims to train one doctoral student and offer opportunities to undergraduate and graduate students in mathematics at Mississippi State University. Training of at least one graduate student on the topics of the proposed work is expected. The project has four primary aims. First, the investigator will derive novel mixed exponential integrators and preconditioned rational exponential integrators for stiff systems and implement them. Second, the investigator will develop stiffly-accurate embedded multirate exponential methods for additively partitioned systems. Third, the investigator will develop stiffly-accurate exponential Nyström methods. Fourth, the investigator will investigate the performance of the newly developed methods on applications in numerical weather prediction, ocean modeling, and molecular dynamics simulations. The investigator will build off of his previous expertise in constructing, analyzing, and implementing exponential and multirate time integration methods to achieve these aims. Ongoing collaborations with numerical analysts, meteorologists, and computer scientists will also contribute to the success of the project.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.