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physics.flu-dyn2023
A co-kurtosis PCA based dimensionality reduction with nonlinear reconstruction using neural networks
Dibyajyoti Nayak, Anirudh Jonnalagadda, Uma Balakrishnan +2
For turbulent reacting flows, identification of low-dimensional representations of the thermo-chemical state space is vitally important, primarily to significantly reduce the compu…
physics.flu-dyn2022★ 10 cited
A co-kurtosis based dimensionality reduction method for combustion datasets
Anirudh Jonnalagadda, Shubham P. Kulkarni, Akash Rodhiya +2
Principal Component Analysis (PCA) is a dimensionality reduction technique widely used to reduce the computational cost associated with numerical simulations of combustion phenomen…