Shape optimization of a feedback-channel fluidic oscillator

Han-Sol Jeong,Kwang-Yong Kim

doi:10.1080/19942060.2017.1379441

Han-Sol Jeong, Kwang-Yong Kim

Open Access

https://doi.org/10.1080/19942060.2017.1379441

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Abstract

ABSTRACTIn this study, a fluidic oscillator was optimized based on the three-dimensional unsteady Reynolds-averaged Navier-Stokes analysis to enhance peak jet velocity at the outlet and simultaneously reduce pressure drop. A multi-objective genetic algorithm performed the optimization with surrogate modeling. The ratios of the inlet nozzle width and the distance between the splitters to the throat width were chosen as the design variables. And, two objective functions related to peak jet velocity at the outlet and pressure drop through the fluidic oscillator were selected for the optimization. Ten design points were selected in the design space using a Latin hypercube sampling method; the objective functions were calculated by unsteady Reynolds-averaged Navier-Stokes analysis at these design points to construct surrogate models that were used to approximate the objective functions. Two different surrogate models, namely response surface approximation and Kriging models were tested. Pareto-optimal front representing a compromise between the two objective functions was obtained from the multi-objective optimization. The optimization results indicated that a jet velocity-oriented optimum design increased the peak jet velocity ratio at the outlet and the friction factor by 11.18% and 16.82%, respectively, when compared to those of a friction factor-oriented design.

Highlights

Any viscous flow subjected to an adverse pressure gradient is prone to separation from a wall
The results indicated that the optimal number of grid nodes was approximately 2,600,000
The findings revealed that the response surface approximation (RSA) model exhibited better prediction accuracies for the optimum objective functions with maximum relative errors of 3.85% compared to the unsteady Reynoldsaveraged Navier-Stokes (RANS) calculation using the KRG model

Summary

Introduction

Any viscous flow subjected to an adverse pressure gradient is prone to separation from a wall. Separation control using fluidic oscillators is a fast growing state of the art technology. A fluidic oscillator injects high momentum fluid into the boundary layer. A jet ejected from the fluidic oscillator entrains high momentum fluid and energizes the boundary layer. The pulsing jet increases the mixing rate across the flow field and thereby enhances momentum transfer. In this manner, the pulsing jet ejected from the fluidic oscillator allows viscous fluid to overcome a strong adverse pressure gradient and controls the flow separation

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Results

Conclusion