2023 article
Physics-Informed Neural Networks for Turbulent Combustion: Toward Extracting More Statistics and Closure from Point Multiscalar Measurements
Taassob, A., Ranade, R., & Echekki, T. (2023, October 31). ENERGY & FUELS, Vol. 10.
2022 journal article
Investigation of deep learning methods for efficient high-fidelity simulations in turbulent combustion
COMBUSTION AND FLAME, 236.
2021 journal article
Algorithmically-consistent deep learning frameworks for structural topology optimization
Engineering Applications of Artificial Intelligence.
2021 journal article
An Efficient Machine-Learning Approach for PDF Tabulation in Turbulent Combustion Closure
Combustion Science and Technology, 193(7), 1258β1277.
2021 journal article
DiscretizationNet: A machine-learning based solver for NavierβStokes equations using finite volume discretization
Computer Methods in Applied Mechanics and Engineering, 378, 113722.
2021 article
Experiment-Based Modeling of Turbulent Flames with Inhomogeneous Inlets
Ranade, R., Echekki, T., & Masri, A. R. (2021, November 16). FLOW TURBULENCE AND COMBUSTION, Vol. 11.
2020 article
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization
(2020, May 17).
2019 article
A Framework for Data-Based Turbulent Combustion Closure: A Priori Validation
Ranade, R., & Echekki, T. (2019, May 20). Combustion and Flame, Vol. 206, pp. 490β505.
Contributors: & T. Echekki nβ nβ
2019 journal article
A framework for data-based turbulent combustion closure: A posteriori validation
Combustion and Flame, 210, 279β291.
Contributors: & T. Echekki nβ nβ
2019 journal article
An ANN based hybrid chemistry framework for complex fuels
FUEL, 241, 625β636.
Contributors: , S. Alqahtaniβ n, A. Farooqβ* & T. Echekki nβ nβ
2019 journal article
An extended hybrid chemistry framework for complex hydrocarbon fuels
FUEL, 251, 276β284.
Contributors: , S. Alqahtaniβ n, A. Farooqβ* & T. Echekki nβ nβ
Updated: November 15th, 2019 20:16
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