A general linear method approach to the design and optimization of efficient, accurate, and easily implemented time-stepping methods in CFD
Victor DeCaria, Sigal Gottlieb, Zachary J. Grant, and William J., Layton

TL;DR
This paper develops and tests new general linear time-stepping methods with filtering techniques to improve accuracy, stability, and ease of implementation in CFD simulations, addressing longstanding challenges in fluid dynamics modeling.
Contribution
It introduces a novel filtering approach to enhance existing time-stepping methods, resulting in high-accuracy, stable, and easily implementable schemes for CFD applications.
Findings
New high-order, A-stable methods with low complexity
Effective filtering techniques for popular methods
Identification of failure points in existing schemes
Abstract
In simulations of fluid motion time accuracy has proven to be elusive. We seek highly accurate methods with strong enough stability properties to deal with the richness of scales of many flows. These methods must also be easy to implement within current complex, possibly legacy codes. Herein we develop, analyze and test new time stepping methods addressing these two issues with the goal of accelerating the development of time accurate methods addressing the needs of applications. The new methods are created by introducing inexpensive pre-filtering and post-filtering steps to popular methods which have been implemented and tested within existing codes. We show that pre-filtering and post-filtering a multistep or multi-stage method results in new methods which have both multiple steps and stages: these are general linear methods (GLMs). We utilize the well studied properties of GLMs to…
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Taxonomy
TopicsModel Reduction and Neural Networks · Advanced Numerical Methods in Computational Mathematics · Computational Fluid Dynamics and Aerodynamics
