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Boundary Layer Separation from a Curved Backward-Facing Step Using Improved Delayed Detached-Eddy Simulation
Boundary Layer Separation from a Curved Backward-Facing Step Using Improved Delayed Detached-Eddy Simulation
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Boundary Layer Separation from a Curved Backward-Facing Step Using Improved Delayed Detached-Eddy Simulation
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Boundary Layer Separation from a Curved Backward-Facing Step Using Improved Delayed Detached-Eddy Simulation
Boundary Layer Separation from a Curved Backward-Facing Step Using Improved Delayed Detached-Eddy Simulation

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Boundary Layer Separation from a Curved Backward-Facing Step Using Improved Delayed Detached-Eddy Simulation
Boundary Layer Separation from a Curved Backward-Facing Step Using Improved Delayed Detached-Eddy Simulation
Journal Article

Boundary Layer Separation from a Curved Backward-Facing Step Using Improved Delayed Detached-Eddy Simulation

2025
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Overview
Curved surfaces are a feature of many engineering applications, and as such, the accurate prediction of separation and reattachment from a curved surface is of great engineering importance. In this study, improved delayed detached eddy simulation (IDDES) is used, in conjunction with synthetic turbulence injection using the synthetic eddy method (SEM), to investigate the boundary layer separation from a curved backward-facing step for which large eddy simulation (LES) results are available. The commercial code Star CCM+ was used with the k-ω shear stress transport (SST) variation of the IDDES model to assess the accuracy of the code for this class of problem. The IDDES model predicted the separation length within 10.4% of the LES value for the finest mesh and 25.5% for the coarsest mesh, compared to 36.2% for the RANS simulation. Good agreement between the IDDES and LES was also found in terms of the distribution of skin friction, velocity, and Reynolds stress, demonstrating an acceptable level of accuracy, as has the prediction of the separation and reattachment location. The model has, however, found it difficult to capture the pressure coefficient accurately in the region of separation and reattachment. Overall, the IDDES model has performed well against a type of geometry that is typically a challenge to the hybrid RANS-LES method (HRLM).

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