Diffuser optimization using computational fluid dynamics and micro-genetic algorithms

Abstract EN

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 (μ- GA).

The CFD model is based on the Reynolds-averaged Navier-Stokes equations, with the standard k-ε 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.