Flow Computation and Physics Lab

Onkar Sahni, RPI


Location and Affiliations

Flow Computation and Physics Lab is located at Rensselaer Polytechnic Institute (RPI) within the Department of Mechanical, Aerospace and Nuclear Engineering (MANE). It is headed by Prof. Onkar Sahni and is affiliated with the Scientific Computation Research Center (SCOREC), Center for Flow Physics and Control (CeFPaC) and Center for Future Energy Systems (CFES) at Rensselaer.


Research Interests

Flow Computation and Physics Lab is interested in predictive methods and tools for fluid flow problems with a focus on turbulence and flow control. Specifically, for flow problems that exhibit multiscale phenomena and are of stochastic nature due to uncertain inputs. Our group tackles these problems by formulating and applying advanced models and methods. Our research places emphasis on multiscale methods, unstructured meshes, parallel and anisotropic adaptive procedures, and uncertainty quantification techniques. When possible, we compare our predictions with experimental data and/or other "reliable" predictions (e.g., DNS).


Funding Sources

NSF, DoE, NASA, DoD-ARMY, ARO, NYSERDA, Boeing, Sikorsky, Corning, IBM


Research Highlights

(only recent highlights are provided in brief - for more details please see our publications)


  1. US Army tested a prototype of our new cannon design with passive flow control for blast overpressure attenuation, up to ~50% reduction was measured (matches with predictions made in Carson and Sahni, CAF (2015)) - paper is under preparation.

  3. Arbitrary Lagrangian-Eulerian (ALE) formulation for LES of flow over oscillating bluff bodies, where we employ Lagrangian dynamic subgrid-scale model - presented at the 8th BBAA conference.

  5. A novel dynamic procedure based on a local formulation of the variational Germano identity (submitted - Tran and Sahni, J. of Turbulence (2016)).

  7. Finite element based LES of complex flows using a combined subgrid-scale model based on the RBVMS model and dynamic Smagorinsky eddy-viscosity model, where we employ a Lagrangian averaging scheme (accepted - Tran and Sahni, CAF (2016); and submitted - Tran and Sahni, J. of Turbulence (2016)).

  9. A new scaling law for the peak overpressure due to a cannon blast, which accounts for polar angle dependence (Carson and Sahni, JFE (2016)).

  11. Stochastic VMS based on a gPC approximation of the stabilization parameter, where we employ efficient projection techniques including for fractional exponents - paper is underway.

  13. High-order VMS for advective-diffusive-reactive systems, where we observe nodal exactness in 1D up to p=3 (polynomial order) - paper is under preparation.

  15. Parallel boundary layer mesh adaptation to generate anisotropic meshes for complex problems with billions of elements on tens of thousands on processors - see Sahni et al. EWC (2016).

  17. Anisotropic p-resolution for boundary layer problems using a mixed B-spline setting on hybrid/layered meshes - see Zhang and Sahni, AIAA Paper 2016-1099.

  19. Active flow control in compact inlet ducts (joint experimental and numerical investigation) - see Vaccaro et al. IJHFF (2015).

  21. A new cannon design with passive flow control (based on the channel leak method) for blast overpressure attenuation is proposed based on numerical predictions - see Carson and Sahni, Shock Waves (2014).

  23. Variational multiscale analysis for stochastic partial differential equations, where we analyze the fine-scale Green's function - see Jagalur Mohan et al., SIAM/ASA JUQ (2014).

  25. Strong scaling on millions of processes for unstructured adapted meshes with up to 92 billion elements - see Rasquin et al. Computing in Science & Engineering (2014).