Computational Fluid Dynamics Laboratory
Oklahoma State University

We are developing advanced computational methods for nonlinear dynamical systems driven by multiscale and multiphysics processes. The systems studied in our lab range from engineering flow problems to geophysical flow problems with different levels of complexities. There is an emphasis on modeling and analysis of turbulent flows across a variety of spatial and temporal scales. More information about our research activities can be found here.  We are located at the third floor of Advanced Technology Research Center building on OSU's Stillwater campus (ATRC 303 & 319).

Our current efforts are centered in the development of hybrid approaches in LES and ROM frameworks. 
We focus on establishing guidelines for a “hybrid analytics” paradigm combining machine learning with the physics-based models, which will contribute a firm unified foundation for the computational modeling and simulation of multiscale and multiphysics transport problems. We believe that generating robust "digital twins" of such physical processes would be extremely useful, 
especially in settings where repeated model evaluations are required over a large range of parameter values or ensemble realizations (e.g., optimal control, data assimilation and uncertainty quantification). 
An illustrative description of the hybrid analytics framework. 
This is a joint work with Dr. Adil Rasheed (
Norwegian University of Science and Technology, Tronheim & SINTEF Digital, Norway). Further details can be found in Fluids 3(4), 86 (2018) by Mashfiqur Rahman, Omer San and Adil Rasheed.
Closure modeling analogy between large eddy simulation (LES) and reduced 
order modeling (ROM) where higher m index refers to smaller scales. Further descriptions of this analogy can be found in the 
Imran Akhtar, Zhu Wang, Jeff Borggaard and Traian Iliescu

A snapshot of the density field for the stratified turbulence problem where we assess the validity of the proposed blind deconvolution approach. Maulik and San, J. Fluid Mech. 2017; 831: 151-181

Evolution of the x-component vorticity iso-surfaces for the Taylor-Green problem, exhibiting well-known vortex stretching mechanism in isotropic, homogeneous turbulent flows and the consequent production of small eddies. San, Staples, and Iliescu, Int J Comput Fluid D 2015; 29: 40-66 

A high resolution snapshot of the double shear layer problem obtained by the Roe solver, where we test the implicit and explicit LES models. Maulik and San, Fluids 2017; 2:14

Rayleigh-Benard natural convection: Streamfunction (top), vorticity (middle) and temperature (bottom) fields for Ra= 10,000 (left) and Ra=100,000 (right). Maulik and San, Int. J. Heat Mass Transfer, 2017; 108: 1656-1675

Evolution of temperature field for the Marsigli flow problem (also known as the lock-exchange problem), a strong shear flow problem exhibiting the Kelvin-Helmholtz instability. San and Borggaard, Int J Numer Meth Fluids, 2015;  78: 37-62

Instantaneous Q surface plot for a turbulent channel at Re_t=395, colored by the magnitude of the absolute vorticity. Presented in the Coalition for Advancing Digital Research & Education (CADRE) conference, Oklahoma State University, Stillwater, April 17, 2018.