NUMERICAL MODELING OF BACKWARD-FACING STEP FLOW VIA COMPUTATIONAL FLUID DYNAMICS

Year 2023, Issue: 054, 176 - 193, 30.09.2023

İlker Göktepeli , Ulaş Atmaca

https://doi.org/10.59313/jsr-a.1300047

Abstract

As a fundamental case for problems of fluid mechanics, examination of flow separation and its reattachment is important for engineering applications. Considering the significance of the subject, backward-facing step flow has been modeled via Computational Fluid Dynamics (CFD) based on an experimental study previously done at Re = 5000. Steady simulations have been conducted by k-ε Renormalization Group (RNG) considering the same flow conditions of the reference study. Pressure distributions, streamwise and cross-stream velocity components, velocity magnitude values with streamline patterns and turbulence kinetic energy values have been presented by using contour graphics. Furthermore, the stations for pressure distributions, velocity profiles for streamwise components and turbulence kinetic energy values have been defined for evolution of related data. Lower pressure zone for the wake region of the backward-facing step has been attained due to flow separation. Separation of the upstream boundary layer has been seen and it became a curved one. Moreover, turbulence level of the step wake has been obtained as higher than those of any other points. Transition to core flow has been attained at y* = 1.1 that is above the step height. Flow oscillations have been observed for x* ≥ 2 and y* ≤ 1 since the fluctuations for these values were effective in the wake region. To sum up, the dimensionless reattachment length has been numerically obtained as 5.92 which is very good agreement with the experimental results at same Reynolds number. The deviation from the reference results is from 0.34 % to 1.33 %.

Keywords

Backward-facing step, Flow separation, k-ε RNG, Reattachment length, Turbulence

Supporting Institution

Konya Technical University - Academic Staff Training Program

Project Number

2018-OYP-046

Thanks

The present study has been supported by Konya Technical University Academic Staff Training Program with the project number of 2018-OYP-046.

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