most citedA Synergistic Framework Leveraging Autoencoders and Generative Adversarial Networks for the Synthesis of Computational Fluid Dynamics Results in Aerofoil Aerodynamics

2 citations · 4 across the 2 of their papers we have counts for

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2 papers

physics.flu-dyn2023★ 2 cited

A Synergistic Framework Leveraging Autoencoders and Generative Adversarial Networks for the Synthesis of Computational Fluid Dynamics Results in Aerofoil Aerodynamics

Tanishk Nandal, Vaibhav Fulara, Raj Kumar Singh

In the realm of computational fluid dynamics (CFD), accurate prediction of aerodynamic behaviour plays a pivotal role in aerofoil design and optimization. This study proposes a nov…

physics.flu-dyn2021★ 2 cited

Parameterization of Forced Isotropic Turbulent Flow using Autoencoders and Generative Adversarial Networks

Kanishk, Tanishk Nandal, Prince Tyagi +1

Autoencoders and generative neural network models have recently gained popularity in fluid mechanics due to their spontaneity and low processing time instead of high fidelity CFD s…