Dr. Sinan Demir is a research scientist in the Computational Multi-Physics Lab in Argonne’s Transportation and Power Systems (TAPS) division. He has diverse research backgrounds in the areas of artificial intelligence (AI) and machine learning (ML) assisted CFD model/code development and analyses focused on combustion and high speed aerospace propulsion systems, and thermal design and optimization of energy production/storage systems.

At Argonne, he has worked on the development and implementation of deep neural-network based unsteady flamelet progress variable approach (UFPV) where the approach has demonstrated a significant reduction in memory footprint and enabled the use of larger dimensional tabulated manifolds; novel numerical acceleration methods which have enabled orders of magnitude speed-up and convergence for the simulation of the supersonic and hypersonic propulsion systems; and AMR assisted modeling of rotating detonation rocket engines (RDREs). His research and leadership continue on the development/integration of physics-based and data-driven turbulent combustion, and plasma assisted ignition models for hypersonic propulsion problems.

Most of his recent research activities supported by the Department of Energy Office (DOE), National Aeronautics and Space Administration (NASA), Air Force Research Laboratory (AFRL), Office of Naval Research (ONR), Naval Research Laboratory (NRL) and Defense Advanced Research Projects Agency (DARPA). He has collaborations with academic institutions, private industry and other national labs. Dr. Demir is also recipient of Argonne’s 2021 Innovation Research Impact Award for notable achievement in the modeling of supersonic and hypersonic propulsion systems.  

Dr. Demir received his Ph.D. from West Virginia University (Fall 2017) in Mechanical and Aerospace Engineering, and aimed to elucidate and control the basic mechanisms of flame acceleration and deflagration – to − detonation transition (DDT) in order to develop strategies to promote the efficiency of rapid- flame-based combustors (e.g., micro-combustors and rotating detonation engines (RDEs)) and to reduce the risk of unwanted explosions and detonations (e.g, industrial and coal mining explosions) by means of developed analytical approaches and a computational platform. Prior the joining the Argonne, he was a postdoctoral researcher at Georgia Institute of Technology (GT) School of Aerospace Engineering and worked on hybrid subgrid scale modeling approach which enabled LES simulations of flame acceleration and DDT in large scale smooth and obstructed geometries, and explored quantifying uncertainties in problems involving complex physics ranging from shock waves, blast waves with interaction of reactive particles, hydrodynamic instabilities, and combustion.