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SPECIAL SECTION ON RANS/LES/DES/DNS: THE FUTURE PROSPECTS OF TURBULENCE MODELING

Nonboundary Conforming Methods for Large-Eddy Simulations of Biological Flows

[+] Author and Article Information
Elias Balaras1

Department of Mechanical Engineering,  University of Maryland, College Park, MD 20742balaras@eng.umd.edu

Jianming Yang

Department of Mechanical Engineering,  University of Maryland, College Park, MD 20742

1

Corresponding author.

J. Fluids Eng 127(5), 851-857 (Apr 19, 2005) (7 pages) doi:10.1115/1.1988346 History: Received July 22, 2004; Revised April 19, 2005

In the present paper a computational algorithm suitable for large-eddy simulations of fluid/structure problems that are commonly encountered in biological flows is presented. It is based on a mixed Eurelian-Lagrangian formulation, where the governing equations are solved on a fixed grid, which is not aligned with the body surface, and the nonslip conditions are enforced via local reconstructions of the solution near the solid interface. With this strategy we can compute the flow around complex stationary/moving boundaries and at the same time maintain the efficiency and optimal conservation properties of the underlying Cartesian solver. A variety of examples, that establish the accuracy and range of applicability of the method are included.

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Copyright © 2005 by American Society of Mechanical Engineers
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Figures

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Figure 1

Staggered grid arrangement near the body for the 2D problem. Grey area denotes the location of the body at tk−1 and black at tk; ◻ p; ▵ ui.

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Figure 2

Sketch of computational domain for the case of the sphere (top) and oscillating cylinder (bottom)

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Figure 3

Error in the drag coefficient for the flow around the sphere as a function of grid resolution

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Figure 4

Vortical structures in the wake of the sphere for Re=300. Isosurfaces of Q=0.001 are shown.

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Figure 5

Temporal evolution of the lift and drag coefficients for the case of the cylinder oscillating in a cross flow. (a) fe∕fo=1.0; (b) fe∕fo=1.2. —,CD; – – –, CL.

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Figure 6

Variation of: 엯, C¯D; ▵, CDrms; ◻, CLrms for the case of the cylinder oscillating in a cross flow as a function of fe∕fo

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Figure 7

Spanwise vorticity isolines for fe∕fo=1.0

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Figure 8

Schematic of the computational domain for the case of flow in a model of arterial stenosis

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Figure 9

Phase-averaged spanwise vorticity distribution. (a) T=250 deg; (b) T=320 deg; (c) T=100 deg. The accelerating part of the cycle is from T=180 deg to T=360 deg and the decelerating part is from T=0 deg to T=180 deg.

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Figure 10

Phase-averaged streamwise velocity statistics at T=270 deg. —, simulation; 엯, experiment (28). (a) ⟨u⟩; (b) urms.

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Figure 11

Phase-averaged streamwise velocity statistics at T=350 deg. —, simulation; 엯, experiment (28). (a) ⟨u⟩; (b) urms.

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