Diffuser Optimization Using Computational Fluid Dynamics and Micro-Genetic Algorithms.(Dept.M)
2021
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.
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