Professor D.W. Zingg
University of Toronto
Institute for Aerospace Studies
4925 Dufferin St., Ontario, Canada M3H 5T6
Email: david (dot) zingg (at) utoronto (dot) ca
- Ph.D. – University of Toronto
- M.A.Sc. – University of Toronto
- B.A.Sc. – University of Toronto
Awards and Honors
- Tier I Canada Research Chair in Computational Aerodynamics and Environmentally Friendly Aircraft Design 2001-2015
- University of Toronto Distinguished Professor in Computational Aerodynamics and Sustainable Aviation
- Fellow of the Canadian Academy of Engineering
- University of Toronto Faculty Award
- Guggenheim Fellowship
Professor Zingg’s research areas include aerodynamics, computational fluid dynamics (CFD), aerodynamic shape optimization, and aerostructural optimization. His current research concentrates on both algorithm development and application of aerodynamic and aerostructural optimization to the design of unconventional low-drag aircraft configurations motivated by the need to reduce greenhouse gas emissions from aircraft. Together with colleagues from NASA, he is a co-author of the textbooks Fundamentals of Computational Fluid Dynamics and Fundamental Algorithms in Computational Fluid Dynamics, published by Springer in 2001 and 2014, respectively. He held a Tier I Canada Research Chair in Computational Aerodynamics and Environmentally Friendly Aircraft Design from 2001 to 2015 and currently holds the title of University of Toronto Distinguished Professor of Computational Aerodynamics and Sustainable Aviation. He was awarded a prestigious Guggenheim Fellowship in 2004 for research in the design of environmentally friendly aircraft and the J.J. Berry Smith Doctoral Supervision Award in 2016.
The motivation for the research in the computational aerodynamics group is based on two premises. The first is that we require a substantial reduction in greenhouse gas emissions per passenger-km from the next generation of aircraft. Although the current contribution of civil aviation to climate change is relatively modest, demand for air travel is projected to increase at 3-4% per year, while emissions per passenger-km have historically decreased at a rate of 1% per year. This situation is not sustainable, and we need aggressive R&D to obtain larger reductions in emissions. The second premise is that CFD and aerodynamic shape optimization can play an important role in achieving this goal through the development and evaluation of new concepts and aircraft configurations for drag reduction. The specific goals of the computational aerodynamics group are:
1. To advance the state of the art in algorithms for CFD as well as aerodynamic and aerostructural optimization.
2. To apply these algorithms to the development of drag reduction techniques and the next generation of aircraft with greatly reduced greenhouse gas emissions per passenger-km.
The group currently has strong interactions with several organizations, most notably Bombardier Aerospace, Airbus, and the NASA Ames Research Center.
At the core of the research are novel algorithms for CFD and aerodynamic shape optimization developed by the group. The parallel implicit flow solver Diablo combines an efficient Newton-Krylov-Schur algorithm with a higher-order spatial discretization based on summation-by-parts operators and simultaneous approximation terms applicable to multi-block structured grids. This combination provides a unique and powerful algorithm for the numerical solution of the Reynolds-averaged Navier-Stokes equations as well as large-eddy and direct simulations of turbulent flows. The optimization code Jetstream utilizes this flow solver in conjunction with an adjoint technique for gradient evaluation and novel approaches to mesh movement, geometry parameterization, and geometry control. Jetstream has been applied to the optimization of various wings and aircraft, including nonplanar wings and unconventional aircraft configurations.
Several current projects in the computational aerodynamics group are aimed at the development of novel high-order operators for CFD based on the summation-by-parts property for both structured and unstructured grids. In recent years, the group has made some important contributions in this area that have led to numerous opportunities for future research. In addition several projects are aimed at the development of new algorithms for aerodynamic and aerostructural optimization and their application to the design of new aircraft configurations with reduced drag as well as active flow control techniques for drag reduction and morphing wings. Within these general areas, there are numerous exciting thesis topics.
Applications from talented students are always welcome. Please see Professor Zingg’s web site for more up-to-date information. Several recent papers are posted there.