Rishikesh Ranade

Investigation of deep learning methods for efficient high-fidelity simulations in turbulent combustion

COMBUSTION AND FLAME, 236, 111814.

Algorithmically-consistent deep learning frameworks for structural topology optimization

Engineering Applications of Artificial Intelligence.

An Efficient Machine-Learning Approach for PDF Tabulation in Turbulent Combustion Closure

Combustion Science and Technology, 193(7), 1258–1277.

DiscretizationNet: A machine-learning based solver for Navier–Stokes equations using finite volume discretization

Computer Methods in Applied Mechanics and Engineering, 378, 113722.

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.

DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization

Ranade, R. (2020, May 17).

A Framework for Data-Based Turbulent Combustion Closure: A Priori Validation

Ranade, R., & Echekki, T. (2019, May 20). Combustion and Flame, Vol. 206, pp. 490–505.

A framework for data-based turbulent combustion closure: A posteriori validation

Combustion and Flame, 210, 279–291.

An ANN based hybrid chemistry framework for complex fuels

Fuel, 241, 625–636.

An extended hybrid chemistry framework for complex hydrocarbon fuels

FUEL, 251, 276–284.