Zobrazeno 1 - 9
of 9
pro vyhledávání: '"G. N. Sashi Kumar"'
Autor:
A. K. Tiwari, T.K. Radhakrishnan, A. K. Kalburgi, S. Manoj Kumar, J. Sarat Chandra Babu, G. N. Sashi Kumar, Bhuvaneswari Govindan
Publikováno v:
International Journal of Computational Fluid Dynamics. 34:249-266
Accurate modelling of fluid and particle flow is essential for reliable predictions of gas–solid reactions in the multiphase reactor. Due to the promising features such as short contact time, less ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::441fd8738ec18702053e06e4279907de
https://doi.org/10.1080/10618562.2020.1743274
https://doi.org/10.1080/10618562.2020.1743274
Autor:
G. N. Sashi Kumar, N. K. Maheshwari
Publikováno v:
International Journal of Computational Fluid Dynamics. 32:19-34
A numerical scheme for simulating multi-species shock accelerated flows using lattice Boltzmann approach has been proposed. It uses the moment conservation approach of Yang, Shu, and Wu and extends it to multi-species fluid problems. The multi-specie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f830b8c6106130482bbfb611e60ddd7e
https://doi.org/10.1080/10618562.2018.1456654
https://doi.org/10.1080/10618562.2018.1456654
Autor:
G. N. Sashi Kumar, N. K. Maheshwari
Publikováno v:
Computers & Fluids. 203:104539
The Onsager Bhatnagar Gross Krook kinetic model proposed by Mahendra et al. [32, 33] has been extended to arrive at the viscous compressible flow equations for a multi-species diffusion problem. The multi-species model ensures (i) correct exchange co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e8d12ce2637b78721cf3ef2e0372311
https://doi.org/10.1016/j.compfluid.2020.104539
https://doi.org/10.1016/j.compfluid.2020.104539
Autor:
G. N. Sashi Kumar
Publikováno v:
Evolutionary Computation: Techniques and Applications
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4bc6a38eb53dd43b70361e23aed71553
https://doi.org/10.1201/9781315366388-15
https://doi.org/10.1201/9781315366388-15
Publikováno v:
Computers & Fluids. 46:298-305
An adaptation of a parametric ant colony optimization (ACO) to multi-objective optimization (MOO) is presented in this paper. In this algorithm (here onwards called MACO) the concept of MOO is achieved using the reference point (or goal vector) optim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac6c575249fedbbc83c324f0aaab0150
https://doi.org/10.1016/j.compfluid.2011.01.016
https://doi.org/10.1016/j.compfluid.2011.01.016
Publikováno v:
Desalination and Water Treatment. 1:88-106
The MSFSIM, a simulator which predicts the performance of a multi-stage flash (MSF) desalination plant, has been coupled with a genetic algorithm (GA) optimizer. The nuclear desalination demonstration project (NDDP) at Kalpakkam, India, has a MSF pla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e0eb758214900c3f9d88e39c823874bc
https://doi.org/10.5004/dwt.2009.121
https://doi.org/10.5004/dwt.2009.121
Autor:
V. K. Suri, G. N. Sashi Kumar
Publikováno v:
2014 9th International Conference on Industrial and Information Systems (ICIIS).
Nelder-Mead's simplex (NMS) algorithm has been the work horse for numerous problems in various fields of engineering since its introduction in 1965 [1, 2]. Being a multi dimensional direct search method its performance is commendable for unconstraine
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e241eb6557383f75334c18a499bd2419
https://doi.org/10.1109/iciinfs.2014.7036549
https://doi.org/10.1109/iciinfs.2014.7036549
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642172977
SEAL
SEAL
This paper introduces a hybrid shape optimization method (M-HYBRID) for multiple objectives (MO) using Genetic Algorithm (GA) and Ant Colony Optimization (ACO) in combination with a meshless computational fluid dynamics solver. It uses the reference
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77fc30687f6cdec97ab0a2b0655b3ad1
https://doi.org/10.1007/978-3-642-17298-4_61
https://doi.org/10.1007/978-3-642-17298-4_61
Publikováno v:
18th AIAA Computational Fluid Dynamics Conference.
This paper introduces a new hybrid shape optimization method using Genetic Algorithm (GA) and Ant Colony Optimization (ACO) coupled with a meshless Computational Fluid Dynamics (CFD) solver. This method converges faster to a better optimum compared t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eee40d055f61f0d56b7d903d5e97e303
https://doi.org/10.2514/6.2007-3830
https://doi.org/10.2514/6.2007-3830