Effect of wall proximity on the flow over a cube and the implications for the noise emitted

2019 ◽  
Vol 31 (7) ◽  
pp. 077101 ◽  
Author(s):  
David Thompson
Keyword(s):  
2021 ◽  
Vol 33 (4) ◽  
pp. 049901
Author(s):  
Chuangxin He ◽  
Yingzheng Liu ◽  
Lian Gan ◽  
Lutz Lesshafft

1962 ◽  
Vol 12 (1) ◽  
pp. 35-48 ◽  
Author(s):  
Howard Brenner

A general theory is put forward for the effect of wall proximity on the Stokes resistance of an arbitrary particle. The theory is developed completely for the case where the motion of the particle is parallel to a principal axis of resistance. In this case, the wall-effect correction can be calculated entirely from a knowledge of the force experienced by the particle in anunboundedfluid, providing (i) that the wall correction is already known for a spherical particle and (ii) that the particle is small in comparison to its distance from the boundary. Experimental data are cited which confirm the theory. The theory is extended to the wall effect on a particlerotatingnear a boundary.


2016 ◽  
Vol 3 (1) ◽  
pp. 40
Author(s):  
Uriel Goldberg

A turbulence closure based on transport equations for the square-root of the kinetic energy of turbulence, q=k1/2 and the length-scale, , is proposed and tested. The model is topography parameter free (no wall distance needed), uses local wall proximity indicators instead, and is meant to be applicable to both wall-bounded and free shear flows. Solving directly for the turbulence length-scale, invoking Dirichlet boundary conditions for both q and  and the fact that q varies linearly across the viscous sublayer contribute to reduced sensitivity of this model to near-wall grid concentration (as long as the sublayer is resolved) and to less numerical stiffness, hence faster convergence. A variable Cm parameter is featured in this model to account for non-simple shear where mean strain and vorticity rates are different. Several cases, covering a wide variety of flows, are presented to demonstrate the model’s performance. Fluids engineers whose work involves complex 3D topologies, particularly with non-stationary grids which require re-computing wall distance arrays at each time-step (a heavy demand on time and budget) may appreciate the fact that no distance arrays are needed for the q-  model.


2010 ◽  
Vol 14 (1) ◽  
pp. 183-197 ◽  
Author(s):  
Afshin Mohsenzadeh ◽  
Mousa Farhadi ◽  
Kurosh Sedighi

Numerical simulations of forced convective incompressible flow in a horizontal plane channel with adiabatic walls over two isothermal tandem triangular cylinders of equal size are presented to investigate the effect of wall proximity of obstacles, gap space (i.e. gap between two squares), and Reynolds number. Computations have been carried out for Reynolds numbers of (based on triangle width) 100, 250, and 350. Results show that, wall proximity has different effect on first and second triangle in fluid characteristics especially in lower gap spaced, while for heat transfer a fairly same behavior was seen.


1997 ◽  
Vol 119 (3) ◽  
pp. 605-611 ◽  
Author(s):  
P. D. Smout ◽  
P. C. Ivey

An experimental study of wedge probe wall proximity effects is described in Part 1 of this paper. Actual size and large-scale model probes were tested to understand the mechanisms responsible for this effect, by which free-stream pressure near the outer wall of a turbomachine may be overindicated by up to 20 percent dynamic head. CFD calculations of the flow over two-dimensional wedge shapes and a three-dimensional wedge probe were made in support of the experiments, and are reported in this paper. Key flow structures in the probe wake were identified that control the pressures indicated by the probe in a given environment. It is shown that probe aerodynamic characteristics will change if the wake flow structures are modified, for example by traversing close to the wall, or by calibrating the probe in an open jet rather than in a closed section wind tunnel. A simple analytical model of the probe local flows was derived from the CFD results. It is shown by comparison with experiment that this model captures the dominant flow features.


2003 ◽  
Vol 34 (5) ◽  
pp. 585-596 ◽  
Author(s):  
R. J. Martinuzzi ◽  
S. C. C. Bailey ◽  
G. A. Kopp

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