Gandolfo Scialabba, M. Sc.
E-Mail: g.scialabba(at)itv.rwth-aachen.de
Adresse:
Institut für Technische Verbrennung
RWTH Aachen University
Templergraben 64
52056 Aachen
Telefon: +49 (0)241 80-94544
Telefax: +49 (0)241 80-92923
Büro: 219 (2. Etage)
Arbeitsgebiete
Forschung: - Soot Modelling
Lehre: - Numerische Strömungssimulation (Übungsassistent)
Publikationen
- G. Scialabba, A. Attili, F. Loffredo and H. Pitsch. Study on soot oxidation and leakage in turbulent non-premixed jet flames. In 19th International Conference on Numerical Combustion, 2024.
- K. Niemietz, G. Scialabba and H. Pitsch. Prediction of Gas Turbine Emissions II. The FVV Transfer + Networking Event, Würzburg, 2024.
- G. Scialabba, A. Attili and H. Pitsch. Soot break-through in turbulent non-premixed jet flames. International Sooting Flame Workshop, July 20-21, Milan, Italy, 2024.
- G. Scialabba, A. Attili, L. Berger and H. Pitsch. SootDNS: Studying soot oxidation based on direct numerical simulation of a turbulent non-premixed ethylene/air jet flame. HLRS Annual Review Workshop, Stuttgart, 2023.
- T. Grenga, L. Nista, C. Schumann, A. N. Karimi, G. Scialabba, A. Attili and H. Pitsch. Predictive Data-Driven Model Based on Generative Adversarial Network for Premixed Turbulence-Combustion Regimes. Combustion Science and Technology, vol. 195 no. 15, pages 3923-3946, 03 2022. [DOI]
- G. Scialabba, A. Attili, L. Berger and H. Pitsch. Direct numerical simulation of soot oxidation in a three-dimensional turbulent non-premixed ethylene jet flame. 18th International Conference on Numerical Combustion, 2022.
- L. Nista, C.D.K Schumann, G. Scialabba, T. Grenga, A. Attili and H. Pitsch. The influence of adversarial training on turbulence closure modelling. AIAA SciTech 2022 Forum, 4-9 January 2022, 2022.
- T. Grenga, L. Nista, C. D. K. Schumann, A. N. Karimi, G. Scialabba, M. Bode, A. Attili and H. Pitsch. Predictive data driven turbulence-combustion model through Super Resolution Generative Adversarial Network. In Proceedings of the 10th European Combustion Meeting, April 14-15, Naples (Italy) / Online, 2021.
- L. Nista, C. D. K. Schumann, T. Grenga, A. N. Karimi, G. Scialabba, M. Bode, A. Attili and H. Pitsch. Turbulent mixing predictive model with physics-based Generative Adversarial Network. In Proceedings of the 10th European Combustion Meeting, April 14-15, Naples (Italy) / Online, 2021.
- A. Attili, N. Sorace, L. Nista, C. Schumann, A. Karimi, G. Scialabba, T. Grenga and H. Pitsch. Investigation of the Extrapolation Performance of Machine Learning Models for LES of Turbulent Premixed Combustion. In Proceedings of the 10th European Combustion Meeting, April 14-15, Naples (Italy) / Online, 2021.
- G. Scialabba, R. Langer, A. Attili, L. Berger and H. Pitsch. The relevance of soot diffusion in counterflow laminar flame configurations. In Proceedings of the 10th European Combustion Meeting, April 14-15, Naples (Italy) / Online, 2021.
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