Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Alireza Ziamolki"'
Publikováno v:
Frontiers in Energy Research, Vol 11 (2023)
A compressor is one of the key components of a gas turbine engine and its performance and characteristics significantly affect the overall performance of the engine. Axial flow compressors are one of the most conventional types of compressors and are
Externí odkaz:
https://doaj.org/article/ba51dd5eebca48f183780e2737cbeff7
Autor:
Mohammad Ghalandari, Alireza Ziamolki, Amir Mosavi, Shahaboddin Shamshirband, Kwok-Wing Chau, Saeed Bornassi
Publikováno v:
Engineering Applications of Computational Fluid Mechanics, Vol 13, Iss 1, Pp 892-904 (2019)
In this paper, optimization of the first blade of a new test rig is pursued using a hybrid model comprising the genetic algorithm, artificial neural networks and design of experiments. Blade tuning is conducted using three-dimensional geometric param
Externí odkaz:
https://doaj.org/article/d3cffbd0cd094b40bc7a9c42944f5e01
Publikováno v:
International Journal of Numerical Methods for Heat & Fluid Flow. 30:3307-3321
Purpose This study aims at enhancing the performance of a 16-stage axial compressor and improving the operating stability. The adopted approaches for upgrading the compressor are artificial neural network, optimization algorithms and computational fl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d9a4ecbb88ce6d3650bd8c2b8ee9a9b
https://doi.org/10.1108/hff-10-2018-0603
https://doi.org/10.1108/hff-10-2018-0603
Autor:
Amir Mosavi, Kwok Wing Chau, Alireza Ziamolki, Mohammad Ghalandari, Shahaboddin Shamshirband, S. Bornassi
Publikováno v:
Engineering Applications of Computational Fluid Mechanics, Vol 13, Iss 1, Pp 892-904 (2019)
In this paper, optimization of the first blade of a new test rig is pursued using a hybrid model comprising the genetic algorithm, artificial neural networks and design of experiments. Blade tuning is conducted using three-dimensional geometric param
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c67e8d2793132d3855bd943bd67f8b3
https://doi.org/10.1080/19942060.2019.1649196
https://doi.org/10.1080/19942060.2019.1649196