Diffuser Optimization Using Computational Fluid Dynamics and Micro-Genetic Algorithms. | ||||
| MEJ- Mansoura Engineering Journal | ||||
| Article 7, Volume 28, Issue 4, December 2003, Page 15-34 PDF (394.78 K) | ||||
| Document Type: Research Studies | ||||
| DOI: 10.21608/bfemu.2021.142398 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Berge Ohaness Djebedjian 
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| Mechanical Power Engineering Department., Faculty of Engineering., El-Mansoura University., El-Mansoura 35516, Egypt. | ||||
| Abstract | ||||
| An approach for the optimization of turbulent flow in diffusers is presented. A methodology is developed to integrate a finite volume-based computational fluid dynamics (CFD) model and an optimization tool uses micro-genetic algorithms (u GA). The CFD model is based on the Reynolds-averaged Navier-Stokes equations, with the standard k-e closure turbulence model. This methodology is tested on two cases. The first is the estimation of the conical diffuser length, which gives the maximum pressure recovery coefficient, for a given diffuser area ratio. Good agreement between the computational and experimental results is obtained. The second case is the optimization through wall contouring of a given two-dimensional diffuser area ratio and length ratio. The results indicate that the diffuser performance can be improved by this method. | ||||
| Keywords | ||||
| Optimization; Genetic Algorithms; Diffuser; Turbulent Flow | ||||
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