The Concordia Computational Aerodynamics Laboratory
Department of Mechanical, Industrial, and Aerospace Engineering
1455 De Maisonneuve Blvd. O.
Montreal, Quebec, Canada
Interested in computational aerodynamics? Download our free open-source textbook. It includes a thorough explanation of physics and numerics. Using open-source tools including Gmsh, SU2, and Paraview, you will be running simulations on your own computer in just minutes without any pesky licenses.
A free library for rapid aerodynamic analysis of airfoil sections, finite wings, performance of aircraft, and static and dynamic stability. A useful set of Jupyter notebooks targetted to undergraduate students and clubs for preliminary aircraft design. Runs in the cloud without having to install a thing!
A new article in the Journal of Computational Physics by Carlos Pereira on hybridization of the flux reconstruction approach. This allows us to get solutions for high-Reynolds number flows with a fraction of the computational cost.
A new journal article in Computers & Fluids by Mohsen Hamedi shows how optimal filter functions can be obtained for stabilizing high-order simulations of turbulent flow. Improved stability for negligible computational cost.
A new journal artivle in Computers & Fluids by Hamid Karbasian shows that we can perform aerodynamic shape optimization using high-fidelity simulations. By improving the accuracy of the underlying flow simulations, it is possible to provide increase confidence in aerodynamic design.
A new journal article in Physics of Fluids by Hamid Karbasian shows that we can perform aerodynamic shape optimization in the presence of chaotic turbulent flows. Through a combination of reduced order modelling and machine learning, the approach is thousands of times faster than anything prior.
A new journal article in the Journal of Fluid Mechanics by Hamid Karbasian shows that we can successfully extract the sensitivity of aerodynamic systems to design paramaters. This enables gradient-based optimizaton of chaotic systems, and is a significant step forward in taming the chaos of turbulent flows.
A new journal article in the Journal of Scientific Computing by Siavash Hedeyati Nasab and Carlos Pereira. We create optimal explicit Runge-Kutta methods for high-order schemes in multiple dimensions. Up to twice as fast as classical methods, a few minutes to implement, and free to download.
A new journal article by Dr. Brian Vermeire on the design of new families of IMEX methods. These are up to 5 times faster than existing methods and can be optimized for any spatial discretization. If you are solving a stiff system of equations these are a great start, and free to download