Articles dans des revues avec comité de lecture (158)
  1. 10. Fiorina, B., Luu, T. P., Dillon, S., Mercier, R., Wang, P., Angelilli, L., Ciottoli, P. P., Hernández Pérez, F. F., Valorani, M., Im, H. G., Massey, J. C., Li, Z., Chen, Z. X., Swaminathan, N., Popp, S., Hartl, S., Nicolai, H., Hasse, C., Dreizler, A., Butz, D., Geyer, D., Breicher, A., Zhang, K., Duwig, C., Zhang, W., Han, W., van Oijen, J., Pequin, A., Parente, A., Engelmann, L., Kempf, A., Hansinger, M., Pfitzner, M., & Barlow, R. S. (2023). A joint numerical study of multi-regime turbulent combustion. Applications in Energy and Combustion Science, 100221. doi:10.1016/j.jaecs.2023.100221
  2. 11. Tonelli, D., Rosa, L., Gabrielli, P., Caldeira, K., Parente, A., & Contino, F. (2023). Global land and water limits to electrolytic hydrogen production using wind and solar resources. Nature communications, 14(1). doi:10.1038/s41467-023-41107-x
  3. 12. Pequin, A., Evans, M. M., Chinnici, A., Medwell, P. R., & Parente, A. (2023). The reactor-based perspective on finite-rate chemistry in turbulent reacting flows: A review from traditional to low-emission combustion. Applications in Energy and Combustion Science, 16, 100201. doi:10.1016/j.jaecs.2023.100201
  4. 13. Muñoz Salamanca, E., Dave, H., D'Alessio, G., Bontempi, G., Parente, A., & Le Clainche, S. (2023). Extraction and analysis of flow features in planar synthetic jets using different machine learning techniques. Physics of fluids, 35. doi:https://doi.org/10.1063/5.0163833
  5. 14. Savarese, M., Giuntini, L., Malpica Galassi, R., Iavarone, S., Galletti, C., De Paepe, W., & Parente, A. (2023). Model-to-model Bayesian calibration of a Chemical Reactor Network for pollutant emission predictions of an ammonia-fuelled multistage combustor. International journal of hydrogen energy. doi:10.1016/j.ijhydene.2023.08.275
  6. 15. Zdybal, K., Armstrong, E., Parente, A., & Sutherland, J. C. (2023). PCAfold 2.0—Novel tools and algorithms for low-dimensional manifold assessment and optimization. SoftwareX, 23, 101447. doi:10.1016/j.softx.2023.101447
  7. 16. Le Clainche, S., Ferrer, E., Gibson, S., Cross, E., Parente, A., & Vinuesa, R. (2023). Improving aircraft performance using machine learning: A review. Aerospace science and technology, 138, 108354. doi:10.1016/j.ast.2023.108354
  8. 17. Pequin, A., Iavarone, S., Malpica Galassi, R., & Parente, A. (2023). Supervised Clustering for Optimal Sub-model Selection in Reactor-Based Models. Flow, turbulence and combustion. doi:10.1007/s10494-023-00442-1
  9. 18. Da Silva Machado De Freitas, R., Pequin, A., Malpica Galassi, R., Attili, A., & Parente, A. (2023). Model identification in reactor-based combustion closures using sparse symbolic regression. Combustion and flame, 255, 112925. doi:10.1016/j.combustflame.2023.112925
  10. 19. Procacci, A., Donato, L., Amaduzzi, R., Galletti, C., Coussement, A., & Parente, A. (2023). Parameter Estimation Using a Gaussian Process Regression-Based Reduced-Order Model and Sparse Sensing: Application to a Methane/Air Lifted Jet Flame. Flow, turbulence and combustion. doi:10.1007/s10494-023-00446-x
  11. 20. Verleysen, K., Coppitters, D., Parente, A., & Contino, F. (2023). Where to build the ideal solar-powered ammonia plant? Design optimization of a Belgian and Moroccan power-to-ammonia plant for covering the Belgian demand under uncertainties. Applications in Energy and Combustion Science, 14, 100141. doi:10.1016/j.jaecs.2023.100141
  12. 21. Wen, X., Berger, L., Vom Lehn, F., Parente, A., & Pitsch, H. (2023). Numerical analysis and flamelet modeling of NO formation in a thermodiffusively unstable hydrogen flame. Combustion and flame, 253, 112817.
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