Passive scalar interface in a spatially evolving mixing layer (A. Attili and D. Denker)

Quartz nozzle sampling (D. Felsmann)

Dissipation element analysis of a planar diffusion flame (D. Denker)

Turbulent/non-turbulent interface in a temporally evolving jet (D. Denker)

Dissipation elements crossing a flame front (D. Denker and B. Hentschel)

Particle laden flow (E. Varea)

Turbulent flame surface in non-premixed methane jet flame (D. Denker)

DNS of primary break up (M. Bode)

Diffusion flame in a slot Bunsen burner (S. Kruse)

Various quantities in spatially evolving jet diffusion flame (D. Denker)

OH layer in a turbulent wall bounded flame (K. Niemietz)

Ludovico Nista, M. Sc.

E-Mail:  l.nista(at)itv.rwth-aachen.de

Adresse:
              Institut für Technische Verbrennung
              RWTH Aachen University
              Templergraben 64
              52056 Aachen

Telefon: +49 (0)241 80-94619
Telefax: +49 (0)241 80-92923

Büro:  217 (2. Etage)


Arbeitsgebiete

Main Research Interests:

  • Development of data-driven closure models for non-reactive and reactive turbulent flows.
  • Computational fluid dynamics and high performance computing.

Teaching:

  • Teaching Assistant of Turbulent Flows

Publikationen

  • Nista, L., Schumann, C. D. K., Grenga, T., Attili, A., & Pitsch, H. (2022). Investigation of the generalization capability of a generative adversarial network for large eddy simulation of turbulent premixed reacting flows. Proceedings of the Combustion Institute.
  • Grenga T., Nista L., Schumann C., Scialabba G., Attili A., and Pitsch H. (2022). "Predictive data-driven model based on generative adversarial network for premixed turbulence-combustion regimes." In Combustion Science and Technology.
  • Nista L., Schumann C., Scialabba G., Grenga T., Attili A., and Pitsch H. (2022). "The influence of adversarial training on turbulence closure modeling." In AIAA Scitech 2022 Forum (p. 0185).
  • Attili A., Sorace N., Nista L., Schumann C., Karimi A., Scialabba G., Grenga T., and Pitsch H. (2021). "Investigation of the Extrapolation Performance of Machine Learning Models for LES of Turbulent Premixed Combustion." In 10th European Combustion Meetings
  • Grenga T., Nista L., Schumann C., Karimi A., Scialabba G., Bode M., Attili A., and Pitsch, H. (2021). "Predictive data-driven turbulent combustion model through Super Resolution Generative Adversarial Network." In 10th European Combustion Meetings
  • Nista L., Schumann C., Grenga T., Karimi A., Scialabba G., Bode M., Attili A., and Pitsch, H. (2021). "Turbulent mixing predictive model with physics-based Generative Adversarial Network". In 10th European Combustion Meetings
  • Ozden A., Nista L., Saracoglu, B. H. (2020). "Performance evaluations of the STRATOFLY MR3 propulsive nozzle at supersonic speeds." In AIAA Propulsion and Energy 2020 Forum (p. 3716).
  • Nista L., Saracoglu B. H. (2019). "Development of a robust solver to model the flow inside the engines for high-speed propulsion." In MATEC Web of Conferences (Vol. 304, p. 03013). EDP Sciences.
  • Nista L., Saracoglu B. H. (2019). "Numerical investigation of the STRATOFLY MR3 propulsive nozzle during supersonic to hypersonic transition." In AIAA Propulsion and Energy 2019 Forum (p. 3843).
  • Nista L., Ispir A. C., and Saracoglu B. H. (2019). "A detailed combustion solver for detonation engines simulations." In AIAA Scitech 2019 Forum (p. 2250).
  • Ispir A. C., Nista L., Saracoglu B., and Magin, T. (2019). "Detailed Chemistry Investigation of Hydrogen and Hydrocarbon Based Fuel Mixture for Detonation Engine." In AIAA Scitech 2019 Forum (p. 1502).

Offene Stellen/Arbeiten

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