Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Georgios Bakalis"'
Autor:
Georgios Bakalis, Hoi Dick Ng
Publikováno v:
Energies, Vol 17, Iss 7, p 1747 (2024)
In this work, a previously developed three-feature Artificial Neural Network (ANN) model with dimensional inputs is directly applied to predict the cell size of hydrocarbon/ammonia/nitrous oxide mixtures and compare these to experimental data. This m
Externí odkaz:
https://doaj.org/article/315510b7619546f4828f06382178c7e7
Publikováno v:
Fuel Communications, Vol 14, Iss , Pp 100084- (2023)
In this paper, we develop a series of Artificial Neural Networks (ANN) using different chemical kinetic and thermodynamic input parameters to predict detonation cell sizes. The feedforward neural networks are trained and validated using available exp
Externí odkaz:
https://doaj.org/article/536152ce01754d97aaf5db6fe4938dec
Autor:
Dimos Zachos, Nikolaos Xafoulis, Konstantinos Bakalis, Nikolaos Alamanis, Georgios Bakalis, Grigorios Papageorgiou
Publikováno v:
Energy Systems. 12:989-1002
In the present paper, the distribution of ground impulses in diaphragm retaining walls is investigated. The research focuses on ground support methods, based on the limit equilibrium method and is implemented in accordance with the provisions of Euro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db497b260deb550b08d5b2afdb8f4288
https://doi.org/10.1007/s12667-021-00429-9
https://doi.org/10.1007/s12667-021-00429-9
Publikováno v:
Computers & Mathematics with Applications. 83:111-126
The deflagration-to-detonation transition via the interaction of a weak shock with a series of discrete laminar flames is analyzed computationally based on the unsteady reactive Navier–Stokes equations with one-step Arrhenius chemistry. For compari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38ebb1a9822601d0a44e50b19e285bb1
https://doi.org/10.1016/j.camwa.2020.05.016
https://doi.org/10.1016/j.camwa.2020.05.016