Parties d'ouvrages collectifs (2)
  1. 1. Zdybal, K., D'Alessio, G., Aversano, G., Malik, M. R., Coussement, A., Sutherland, J. C., & Parente, A. (2023). Advancing Reacting Flow Simulations with Data-Driven Models. In Advancing Reacting Flow Simulations with Data-Driven Models (1 ed., pp. 304 - 329). Cambridge University Press. doi:https://doi.org/10.1017/9781108896214.022
  2. 2. Zdybal, K., Malik, M. R., Coussement, A., Sutherland, J. C., & Parente, A. (2023). Reduced-Order Modeling of Reacting Flows Using Data-Driven Approaches. In N. Swaminathan & A. Parente (Eds.), Reduced-Order Modeling of Reacting Flows Using Data-Driven Approaches. Cham: Springer. doi:https://doi.org/10.1007/978-3-031-16248-0_9
    3.   Articles dans des revues avec comité de lecture (60)
  3. 1. Jamshidiha, M., Kamal, M. M., Giuntini, L., Lubrano Lavadera, M., Coussement, A., & Parente, A. (2025). Comparative effects of N2 and CO2 fuel dilution on NOx suppression in non-premixed hydrogen combustion. Applied thermal engineering, 288.
  4. 2. Rahmani, E., Cid Rodríguez, N., Kamal, M. M., Coussement, A., Parente, A., & Lubrano Lavadera, M. (2025). The influence of MILD-to-flame transition on stabilization, reactive structures, and emissions of NH3/H2 mixtures in a semi-industrial furnace. Combustion and flame, 284, 114687. doi:10.1016/j.combustflame.2025.114687
  5. 3. Procacci, A., Iavarone, S., Coussement, A., & Parente, A. (2025). Stochastic reduced-order modeling for the forecast of noisy dynamical systems. Proceedings of the Combustion Institute, 41, 105981.
  6. 4. Hafeez, M. A., Procacci, A., Coussement, A., & Parente, A. (2025). Constrained reduced-order modeling of reacting flows using bounded Gaussian process likelihoods: application to a furnace operating under MILD conditions. Proceedings of the Combustion Institute, 41, 105846. doi:10.1016/j.proci.2025.105846
  7. 5. Cafiero, M., Mustafa Kamal, M., Sharma, S., Nguyen, P. D., Nowakowska, M., Coussement, A., & Parente, A. (2025). Combustion characterization of benzene-doped, hydrogen-rich coke oven gas surrogate mixtures: H2/CH4/CO/N2/CO2. Fuel processing technology, 276, 108241. doi:10.1016/j.fuproc.2025.108241
  8. 6. Biswal, P., Avdijaj, J., Parente, A., & Coussement, A. (2025). Physics informed neural networks to solve radiative transfer equation in absorbing-scattering media. Journal of quantitative spectroscopy & radiative transfer, 344, 109509. doi:10.1016/j.jqsrt.2025.109509
  9. 7. Hafeez, M. A., Procacci, A., Coussement, A., & Parente, A. (2025). Constrained reduced-order modeling using bounded Gaussian processes for physically consistent reacting flow predictions. Energy and AI, 21, 100554. doi:10.1016/j.egyai.2025.100554
  10. 8. Cafiero, M., Kamal, M. M., Sharma, S., Nguyen, P. D., Nowakowska, M., Coussement, A., & Parente, A. (2025). Combustion characterization of benzene-doped, hydrogen-rich coke oven gas surrogate mixtures: H2/CH4/CO/N2/CO2. Fuel processing technology, 276.
  11. 9. Piscopo, A., Giuntini, L., Novelli, C., De Paepe, W., Coussement, A., & Parente, A. (2025). Burning ammonia–hydrogen mixtures in a staged combustor with high efficiency and low pollutant emissions. International journal of hydrogen energy, 118, 343-355. doi:10.1016/j.ijhydene.2025.03.099
  12. 10. Biswal, P., Avdijaj, J., Parente, A., & Coussement, A. (2024). Solving the Radiation Transfer Equation in Participating Media Using Physics Informed Neural Networks. Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering. doi:10.11159/htff24.269
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