Scientific focus

Research topics

Direct Numerical Simulation (DNS) of turbulent reacting flows
Pore-resolved Simulations (PRS) of ammonia conversion in Porous Inert Media (PIM)

Research projects

Non-premixed ammonia combustion in tailor-made ceramic porous inert media

CV

From	Pathankot, India
2013-2017	B.Tech in Mechanical Engineering, Punjabi University Patiala, India
2018-2020	Test Engineer, Infosys Limited, India
2020-2023	M.Sc. in Computer Aided Conception in Mechanical Engineering, RWTH Aachen
Since 2023	Scientific staff, Engler-Bunte Institute of KIT

Publications

Influence of dispersion length on volume-averaged simulations of ammonia/air combustion in porous media burners
Puri, R.; Kretzler, D.; Bock-Seefeld, B.; Stelzner, B.; Brachhold, N.; Hubálková, J.; Trimis, D.; Aneziris, C.; Stein, O. T.; Zirwes, T.
2025. Proceedings of the Combustion Institute, 41, 105856. doi:10.1016/j.proci.2025.105856

Experimental and numerical investigation of non-premixed ammonia flames stabilized on a heated slot burner
Kretzler, D.; Puri, R.; Stelzner, B.; Zirwes, T.; Hagen, F. P.; Stein, O. T.; Trimis, D.
2025. Proceedings of the Combustion Institute, 41, 105854. doi:10.1016/j.proci.2025.105854

Pore-resolved simulations of ammonia combustion in porous inert media
Puri, R.; Zirwes, T.; Stein, O. T.
2025. doi:10.5445/IR/1000184969

Influence of dispersion length for volume-averaged simulations of ammonia/air combustion in porous media burners
Puri, R.; Kretzler, D.; Bock-Seefeld, B.; Stelzner, B.; Brachhold, N.; Hubálková, J.; Trimis, D.; Aneziris, C.; Stein, O. T.; Zirwes, T.
2025, April 8. 12th European Combustion Meeting (ECM 2025), Edinburgh, United Kingdom, April 7–10, 2025

Predicting NOx emissions from porous media burners using physics-informed graph neural networks
Puri, R.; Stein, O. T.; Zirwes, T.
2025. Proceedings of the 35th Parallel CFD International Conference 2024, 35th Parallel CFD International Conference 2024, ParCFD 2024, Bonn, Germany, 2 Sep 2024 - 4 Sep 2024, Forschungszentrum Jülich GmbH. doi:10.34734/FZJ-2025-02463

Predicting NOx emissions from porous media burners using physics-informed graph neural networks
Puri, R.; Stein, O. T.; Zirwes, T.
2024, September 2. 35th Parallel Computational Fluid Dynamics (ParCFD 2024), Bonn, Germany, September 2–4, 2024

On the choice of physical constraints in artificial neural networks for predicting flow fields
Puri, R.; Onishi, J.; Rüttgers, M.; Sarma, R.; Tsubokura, M.; Lintermann, A.
2024. Future Generation Computer Systems. doi:10.1016/j.future.2024.07.009