Abstract

This talk provides an overview of computational combustion research in the Advanced Propulsion Concepts Lab at University of Michigan. The focus of this research group is the development of computational tools for modeling complex reacting flows, with application to propulsion and energy conversion devices. Recently, research in detonation engines are being conducted to understand the propagation of shock waves through a reactive medium. Here, detailed numerical simulations were conducted to understand the structure of detonation waves. In particular, the reaction structure behind the shock wave was resolved in order to determine the ignition process. Simultaneously, computational tools for simulating complex geometries was also developed. Preliminary results from this UMdetFoam solver will be presented..

Biography

Venkat Raman received his PhD from Iowa State University in 2003 in the department of chemical engineering. He was a NASA/Center for Turbulence Research Postdoctoral Fellow at Stanford University from 2003-2004, and a research associate in the Center for Integrated Turbulence Simulations from 2004-2005. From 2005-2014, he was on the faculty of Aerospace Engineering and Engineering Mechanics Department at The University of Texas at Austin, initially as an assistant professor (2005-2011) and later as tenured associate professor (2011-2014).
Raman received an NSF CAREER award in 2008, a distinguished paper award at the International Combustion Symposium in 2013, and the Moncrief Grand Challenge Award in 2013. He held the Eli. H and Ramona Thornton Centennial Fellow in Engineering at UT Austin from 2013-2014. His research focuses on the development of computational models for turbulent reacting flows with application to aircraft and scramjet engines, stationary power generation, and synthesis of novel materials. His research group uses high-performance supercomputers and detailed numerical simulations to study the performance of combustion devices. His recent focus has been in the areas of numerical error analysis, uncertainty quantification, and failure predictions, aimed towards modeling catastrophic and rare events in complex devices and natural systems.
 
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