DT-HATS supervisor:

Alessandro Parente

Supervisor DC15

Alessandro Parente is a Full Professor at the Université Libre de Bruxelles

Alessandro Parente is a Full Professor at the Université Libre de Bruxelles (ULB), where he leads the Brussels Institute for Thermal Fluid Systems and Clean Energy (BRITE). He originally joined the ULB Faculty of Engineering and the Department of Aero-Thermo-Mechanics in October 2010.

What is your motivation to join DT-HATS?

The DT-HATS project represents a key effort to develop carbon-neutral solutions, bridging the gap between advanced numerical modelling and the practical deployment of hydrogen and ammonia as energy carriers. My motivation for joining this research stems from the urgent need to develop high-fidelity digital twins that can optimize complex thermal systems in real-time; by mastering these technologies, we are engineering future clean energy technologies.

  • Özden, A., Galassi, R. M., Contino, F., & Parente, A. (2025). Clustering-based data-driven multi-fidelity reduced order modeling of ammonia combustion. Proceedings of the Combustion Institute. https://doi.org/10.1016/j.proci.2025.105881

  • Parente, A., et al. (2024). Data-driven models and digital twins for sustainable combustion technologies. iScience, 27(4), 109463. https://doi.org/10.1016/j.isci.2024.109463

  • Savarese, M., Procacci, A., Iavarone, S., Giuntini, L., De Paepe, W., & Parente, A. (2024). A sparse sensing and Chemical Reactor Network based framework for the development of physics-based digital twins of combustion devices. Proceedings of the Combustion Institute, 40(1-4). https://doi.org/10.1016/j.proci.2024.105536

  • Procacci, A., Cafiero, M., Sharma, S., Kamal, M. M., Coussement, A., & Parente, A. (2023). Digital Twin for Experimental Data Fusion Applied to a Semi-Industrial Furnace Fed with H2-Rich Fuel Mixtures. Energies, 16(2), 662. https://doi.org/10.3390/en16020662

  • Hafeez, M. A., Procacci, A., Coussement, A., & Parente, A. (2024). Challenges and opportunities for the application of digital twins in hard-to-abate industries: a review. Resources, Conservation and Recycling, 209, 107796. https://doi.org/10.1016/j.resconrec.2024.107796

  • Aversano, G., Ferrarotti, M., & Parente, A. (2021). Digital twin of a combustion furnace operating in flameless conditions: Reduced-order model development from CFD simulations. Proceedings of the Combustion Institute, 38(4), 5403-5412. https://doi.org/10.1016/j.proci.2020.06.027

  • Aversano, G., Bellemans, A., Li, Z., Coussement, A., Gicquel, O., & Parente, A. (2019). Application of reduced-order models based on PCA & Kriging for the development of digital twins of reacting flow applications. Computers & Chemical Engineering, 121, 422-441. https://doi.org/10.1016/j.compchemeng.2018.11.014