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Alessandro Porcarelli holds a BSc in Aerospace Engineering from PoliTO (2019) and an MSc in Aerospace Engineering from KTH (2021), where he gained experience in CFD simulations of both external and internal flows, performing aerodynamic design and heat transfer assessments. His PhD at TU Delft (2021–2026) focused on highly strained lean premixed hydrogen flames, revealing how intensive strain reduces NOx emissions and suppresses intrinsic flame instabilities. He also developed a LES model to improve predictions of thermodiffusive instability-turbulence interactions in strained hydrogen flames. Currently, as a postdoc, he is running DNS of strained lean premixed hydrogen flames with water spray for the ERC-funded OTHERWISE project and developing reduced-order models to predict and control emissions and instabilities and design strained hydrogen combustors.
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Collaborations and top research areas from the last five years
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Assessment of tabulated-chemistry models for lean premixed strained hydrogen flames with low-dimensional manifolds
Porcarelli, A., Lapenna, P. E., Creta, F. & Langella, I., 2026, In: Combustion Theory and Modelling. 30, 2, p. 239-265 27 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile1 Downloads (Pure) -
Highly Strained Lean Premixed Hydrogen Flames: Emissions, Stability and Modelling
Porcarelli, A., 2026, 174 p.Research output: Thesis › Dissertation (TU Delft)
Open AccessFile8 Downloads (Pure) -
Investigation of tangential strain rate impact on NO emissions in turbulent premixed hydrogen flames using the Eulerian Stochastic Fields approach
Masucci, A., Porcarelli, A., Ghisu, T. & Langella, I., 2026, In: Combustion and Flame. 287, 13 p., 114887.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile1 Downloads (Pure) -
Influence of Soret effect on flame structure and NOx emissions in highly strained lean premixed counterflow hydrogen flames
Acquaviva, M. R., Porcarelli, A. & Langella, I., 2025, In: Fuel. 395, 16 p., 134939.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile4 Link opens in a new tab Citations (Scopus)54 Downloads (Pure) -
Stability analysis of thermodiffusively unstable counterflow lean premixed hydrogen flames
Porcarelli, A., Lapenna, P. E., Creta, F. & Langella, I., 2025, In: Proceedings of the Combustion Institute. 41, 8 p., 105906.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile2 Link opens in a new tab Citations (Scopus)1 Downloads (Pure)
Datasets
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Data underlying Chapter 3 of the PhD thesis - NOx emissions analysis in lean premixed and strained hydrogen flamelets
Porcarelli, A. (Creator) & Langella, I. (Creator), TU Delft - 4TU.ResearchData, 1 Oct 2025
DOI: 10.4121/11EE4306-9C7C-42C8-824E-E30484B05B18, https://doi.org/10.1016/j.ijhydene.2023.08.110
Dataset/Software: Dataset
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Data underlying Chapter 5 of the PhD thesis - Stability analysis of thermo-diffusively unstable lean premixed and strained hydrogen flames
Porcarelli, A. (Creator) & Langella, I. (Creator), TU Delft - 4TU.ResearchData, 1 Oct 2025
DOI: 10.4121/BEE79E25-62C0-4078-8045-8AF699CBC5F9
Dataset/Software: Dataset
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Datasets underlying the PhD Thesis: Highly-strained hydrogen combustion modelling for stable and low-NOx premixed hydrogen flames
Porcarelli, A. (Creator) & Langella, I. (Creator), TU Delft - 4TU.ResearchData, 1 Oct 2025
DOI: 10.4121/1C3C25B3-F001-4DBA-BAC7-C70BEAD7F421
Dataset/Software: Dataset
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Data underlying Chapter 6 of the PhD thesis - Assessment of tabulated chemistry models for lean premixed strained hydrogen flames with low-dimensional manifolds
Porcarelli, A. (Creator) & Langella, I. (Creator), TU Delft - 4TU.ResearchData, 1 Oct 2025
DOI: 10.4121/A9B7B9FD-B6AC-4761-9769-3F5E097DB922
Dataset/Software: Dataset
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Data underlying Chapter 4 of the PhD thesis - Effect of strain on hydrogen flame structure and dynamics
Porcarelli, A. (Creator) & Langella, I. (Creator), TU Delft - 4TU.ResearchData, 1 Oct 2025
DOI: 10.4121/8444102F-9674-419E-8356-88641E582B85
Dataset/Software: Dataset