The Advanced Numerical Simulation Laboratory is embarking on a new collaborative research project on curved meshing for high-order finite element methods, in cooperation with Dr. Devina Sanjaya in the Department of Mechanical, Aerospace and Biomedical Engineering at the University of Tennessee.
Commercial air transport of passengers and freight is a significant and growing contributor to greenhouse gas emissions, with total emissions doubling since 1990, despite a 60% decrease in emissions per passenger-kilometer. Continuing this trend in flight efficiency is critical in the face of rapidly growing demand, and requires innovative design of new aircraft. Modern aircraft design, in turn, depends largely on highly accurate, reliable, rapid simulation of the aerodynamic forces that dictate the operating performance and flight envelopes of aircraft. Such simulations are the domain of computational fluid dynamics (CFD). In aerodynamics, CFD tools find application not just for large civilian passenger and cargo planes — the familiar offerings from Boeing, Airbus, and the like — but also for small scale guided and autonomous drones, mid-sized airplanes — including the Canadian-made de Havilland Dash 8 and Twin Otter — and military combat aircraft. This project seeks to make CFD simulations more accurate for a given amount of computational resources, enhancing the tools aerodynamicists use to develop next-generation aircraft of all classes.
Research Objectives and Impacts on Scientific Computing
The overall technical goal of this collaborative project with Dr. Devina P. Sanjaya (University of Tennessee, Knoxville) is to improve the performance and reliability of high-order accurate, adaptive CFD methods for use in aerodynamics. High-order adaptive CFD methods are more efficient than conventional methods at producing accurate simulation results. Recent research shows that creating high-order curved meshes optimized for simulation accuracy can magnify this benefit. We will develop a mathematical framework and robust computational algorithms for high-order, metric-based mesh adaptation and error estimation to improve the efficiency and robustness of high-order CFD. Specifically, we seek to develop i) robust a posteriori, metric based error estimation for high-order CFD methods, ii) mathematical and theoretical foundations of high-order meshes, and iii) efficient global node movement algorithms. The resulting generalized metric-based error estimation and mesh adaptation framework will substantially impact the efficiency and robustness of high-order CFD and enable accurate CFD on coarser meshes. This technical result will harness the full potential of high-order adaptive CFD methods and support their wide-spread deployment in computational aerodynamics. From the point of view of aerospace engineers, this will reduce the amount of computational time and computer memory required for simulations, increasing throughput and allowing them to better understand and control the complex aerodynamic flows they work with daily.
Positions Available
My intention is a hire a post-doctoral researcher and a graduate student for this research project. The post-doc will work closely with me to develop the theory and algorithms for new meshing techniques and design the software architecture for implementing them. Also, the post-doc will have primary responsibility for implementation and testing. The graduate student will work primarily on assessing the impact of improved meshing on flow solution accuracy and efficiency, working with our research meshing code and a state-of-the-art high-order adaptive finite element flow solver.
For more information, see the post-doc advertisement and the grad student advertisement (both advertised online and duplicated here), or contact me directly.