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publications
Large eddy simulation of transitional channel flow using a machine learning classifier to distinguish laminar and turbulent regions
Published in Physical Review Fluids, 2021
In this paper, we show that bypass and subcritical orderly transition can be simulated using the computationally efficient wall-modeled LES method. We use Self-Organizing Map (SOM) to distinguish Turbulent-Non-Turbulent (T-NT) regions of the flow and selectively apply wall-modeling only in turbulent regions of the flow. We were able to show that this method successfully captures the right trends in the evolution of friction Reynolds number (skin-friction) similar to a DNS at much less computational cost.
Recommended citation: Ghanesh Narasimhan, Charles Meneveau, and Tamer A. Zaki. (2021). "Large eddy simulation of transitional channel flow using a machine learning classifier to distinguish laminar and turbulent regions; Phys. Rev. Fluids . 6, 074608. https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.6.074608
Effects of wind veer on a yawed wind turbine wake in atmospheric boundary layer flow
Published in Physical Review Fluids, 2022
Large Eddy Simulation (LES) is used to study the wind veer effects on the wake of a yawed wind turbine. The veer deflects the wake in the spanwise direction, and this effect can be captured in the wake model by adding a veer correction term. The counter-rotating vortex pair structures previously observed behind yawed turbines can also be recovered by subtracting the background veer vorticity.
Recommended citation: Ghanesh Narasimhan, Dennice F. Gayme, and Charles Meneveau (2022). "Effects of wind veer on a yawed wind turbine wake in atmospheric boundary layer flow; Phys. Rev. Fluids . 7(11), p. 114609. https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.7.114609
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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