Seminar in AUGUST, 58th NIA CFD Seminar Webcast: M4D, an Open Source Research CFD Code for the Calculation of Classical and Turbulent/Transitional Flows by Joan G. Moore and John Moore

May 21, 2015 - Leave a Response

58th NIA CFD Seminar

Topic: M4D, an Open Source Research CFD Code for the Calculation of Classical and Turbulent/Transitional Flows

Date: Tuesday, August 4, 2015

Time: 11:00am-noon (EST)

Room: NIA, Rm137

Speaker: Joan G. Moore and John Moore

Speaker Bio: It is fifty years since Joan and John Moore met in M.I.T.’s Gas Turbine Laboratory. John had come with a B.Sc. (Eng.) in Mechanical Engineering from Imperial College, London to obtain an S.M. and then an Sc.D from M.I.T. Joan with a B.S. in Applied Mathematics from M.I.T., had the job of writing computer codes and helping Graduate students with theirs. Thus began a life-long CFD and turbulence modeling collaboration. John is currently a Professor Emeritus of Mechanical Engineering at Virginia Tech. Their first ‘retirement’ project, their book “Functional Reynolds Stress Modeling” was published in 2006. And now Joan has written her 4th CFD code, M4D, but her first one unfettered by external sponsorship.

Abstract: M4D features unsteady convection adapted control volumes and the MARV/MARVS Reynolds stress models. Convection adapted control volumes are a paradigm shift in CFD. Used with tri-linear discretization of convected properties in space over a fixed grid (formally 3-d 2nd-order accurate), they provide a balance between accuracy and stability not found in fixed volume methods. The MARV/MARVS Reynolds stress models are advanced turbulence models which calculate transition naturally based on an understanding of homogeneous shear flow at high dimensionless strain rates.
The presentation will concentrate on the convection adapted control volumes – the method, the combination of stability and accuracy, with the examples of an inviscid Kelvin-Helmholtz shear layer instability and near-DNS of flow in a square channel. The steady flow Reynolds stress model examples of transitional flow and heat transfer in a turbine cascade (Butler et al.) and of a backward facing step (Kasagi) also use the convection adapted control volumes.

Additional information, including the webcast link, can be found at the NIA CFD Seminar website, which is temporarily located at

http://www.hiroakinishikawa.com/niacfds/index.html

 
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TODAY: 57th NIA CFD Seminar Webcast: Towards aerospace design in the age of extreme-scale supercomputing by Qiqi Wang

January 29, 2015 - Leave a Response

57th NIA CFD Seminar

Topic: Towards Aerospace Design in the Age of Extreme-Scale Supercomputing

Date: Thursday, January 29, 2015

Time: 11:00am-noon (EST)

Room: NIA, Rm137

Speaker: Qiqi Wang

Speaker Bio: Qiqi Wang is an assistant professor of aeronautics and astronautics at MIT. He obtained his PhD from Stanford in 2009, and B.S. from University of Science and Technology of China in 2004.

Abstract: Extreme scale supercomputing will soon offer a million times the computing power of a desktop – an as drastic upgrade as that from a slide rule to a desktop computer in the 1990s. I believe this will revolutionize how we aerospace engineers work. It will enable us to rapidly and confidently refine and optimize our designs. But this revolution can only happen through innovating our computational algorithms. In Computational Fluid Dynamics, high-fidelity simulations such as Large Eddy Simulation can often reliably predict the performance of aerospace vehicles and engines. But with today’s algorithms, these simulations take days if not weeks. With today’s optimization algorithms, it may take months if not years for us to reach a good design. Can we shorten each high fidelity CFD simulation to minutes, by innovating how we solve PDEs, better utilizing the skyrocketing concurrency in supercomputers? Better, can we shorten an entire high fidelity optimization to minutes by innovating how we do optimization, again utilizing more concurrency than we currently can? Even better, can we shorten a high fidelity optimization with hundreds of design parameters to minutes, by computing high fidelity design gradients, even when the simulations are turbulent and chaotic, and gradients in the traditional sense would diverge? I believe that the answers are yes, yes and yes. In this talk, I will show you why I believe so, and discuss how we all can advance aerospace design into the age of extreme-scale supercomputing.

Additional information, including the webcast link, can be found at the NIA CFD Seminar website, which is temporarily located at

http://www.hiroakinishikawa.com/niacfds/index.html

 
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