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Assessment of Computational Fluid Dynamic for Surface Combatant 5415 at Straight Ahead and Static Drift β = 20 deg
Journal article   Peer reviewed

Assessment of Computational Fluid Dynamic for Surface Combatant 5415 at Straight Ahead and Static Drift β = 20 deg

Shanti Bhushan, Hyun-Se Yoon, Frederick Stern, Emmanuel Guilmineau, Michel Visonneau, Serge Toxopeus, Claus Simonsen, Shawn Aram, Sungeun Kim and Gregory Grigoropoulos
Journal of fluids engineering, Vol.141(5), 051101
05/01/2019
DOI: 10.1115/1.4041229
url
https://hal.science/hal-02391259View
Open Access

Abstract

Collaboration is described on assessment of computational fluid dynamics (CFD) predictions for surface combatant model 5415 at static drift β = 0 deg and 20 deg using recent tomographic particle image velocimetry (TPIV) experiments. Assessment includes N-version verification and validation to determine the confidence intervals for CFD solutions/codes, and vortex onset, progression, instability, and turbulent kinetic energy (TKE) budget analysis. The increase in β shows the following trends. Forces and moment increase quadratically/cubically, and become unsteady due to shear layer, Karman and flapping instabilities on the bow. Wave elevation becomes asymmetric; its amplitude increases, but the total wave elevation angle remains same. The vortex strength and TKE increase by about two orders of magnitude, and for large β, the primary vortices exhibit helical mode instability similar to those for delta wings. Forces and moment for both β and wave elevation for β = 0 deg are compared within 4% of the data, and are validated at 7% interval. Wave elevation for β = 20 deg, and vortex core location and velocities for both β are compared within 9% of the data, and are validated at 12% interval. The vortex strength and TKE predictions show large 70% errors and equally large scatter and are not validated. Thus, both errors and scatter need reduction. TKE budgets show transport of turbulence into the separation bubble similar to canonical cases, but pressure transport is dominant for ship flows. Improved CFD predictions require better grids and/or turbulence models. Investigations of solution-adaptive mesh refinement for better grid design and hybrid Reynolds-averaged Navier-Stokes/large eddy simulation models for improved turbulent flow predictions are highest priority.
Computer Science Mathematics Mechanics Numerical Analysis Physics Distributed, Parallel, and Cluster Computing Engineering Sciences Fluids mechanics Mechanics of the fluids Mechanics of the structures

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