Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Nasrin Sahranavardfard"'
Autor:
Nasrin Sahranavardfard, Damien Aubagnac-Karkar, Gabriele Costante, Faniry N. Z. Rahantamialisoa, Chaouki Habchi, Michele Battistoni
Publikováno v:
Fluids, Vol 9, Iss 3, p 56 (2024)
Machine learning based on neural networks facilitates data-driven techniques for handling large amounts of data, either obtained through experiments or simulations at multiple spatio-temporal scales, thereby finding the hidden patterns underlying the
Externí odkaz:
https://doaj.org/article/d361a5143907434e839de4f5babe51ea
Autor:
Faniry Rahantamialisoa, Michele Battistoni, Alessio Miliozzi, Nasrin Sahranavardfard, Jacopo Zembi
Computational fluid dynamics is used with the aim to gain further insights of the hydrogen injection process in internal combustion engines. To this end, three-dimensional RANS simulations of hydrogen under-expanded jets under a variety of injection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e13218381092fe0b5a67bad067266e6
https://hdl.handle.net/11391/1550014
https://hdl.handle.net/11391/1550014
Autor:
Nasrin Sahranavardfard, Adrian Pandal, Faniry Nadia Zazaravaka Rahantamialisoa, Michele Battistoni
Publikováno v:
Scopus
The efficiency and combustion performance of propulsion systems, like internal combustion (IC) engines and gas turbines, is known to be related to the performance of the fuel and air mixing process. Operating conditions and fuels are rapidly changing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6bc1434b8e38492c4cc08989e338b1bc
https://doi.org/10.1088/1742-6596/2385/1/012136
https://doi.org/10.1088/1742-6596/2385/1/012136
Autor:
Michele Battistoni, Adrian Pandal, Hrvoje Jasak, Hong G. Im, Nasrin Sahranavardfard, B.M. Ningegowda, Jacopo Zembi, Faniry Nadia Zazaravaka Rahantamialisoa
Publikováno v:
International Conference on Liquid Atomization and Spray Systems (ICLASS). 1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58b55fcd1a119d1924f689800781ebc2
https://doi.org/10.2218/iclass.2021.6040
https://doi.org/10.2218/iclass.2021.6040