scholarly journals Wind noise spectra in small Reynolds number turbulent flows

2017 ◽  
Vol 142 (5) ◽  
pp. 3227-3233 ◽  
Author(s):  
Sipei Zhao ◽  
Eva Cheng ◽  
Xiaojun Qiu ◽  
Ian Burnett ◽  
Jacob Chia-chun Liu
Keyword(s):  
Reynolds Number ◽  
Turbulent Flows ◽  
Small Reynolds Number ◽  
Wind Noise ◽  
Noise Spectra

Simulating flow separation from continuous surfaces: routes to overcoming the Reynolds number barrier

2009 ◽  
Vol 367 (1899) ◽  
pp. 2885-2903 ◽  
Author(s):  
Michael Leschziner ◽  
Ning Li ◽  
Fabrizio Tessicini
Keyword(s):  
Reynolds Number ◽  
Turbulent Flows ◽  
Major Elements ◽  
Wall Layer ◽  
Navier Stokes ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Rans Models ◽  
High Reynolds ◽  
Near Wall

This paper provides a discussion of several aspects of the construction of approaches that combine statistical (Reynolds-averaged Navier–Stokes, RANS) models with large eddy simulation (LES), with the objective of making LES an economically viable method for predicting complex, high Reynolds number turbulent flows. The first part provides a review of alternative approaches, highlighting their rationale and major elements. Next, two particular methods are introduced in greater detail: one based on coupling near-wall RANS models to the outer LES domain on a single contiguous mesh, and the other involving the application of the RANS and LES procedures on separate zones, the former confined to a thin near-wall layer. Examples for their performance are included for channel flow and, in the case of the zonal strategy, for three separated flows. Finally, a discussion of prospects is given, as viewed from the writer's perspective.

scholarly journals Angular velocity of a sphere in a simple shear at small Reynolds number

2016 ◽  
Vol 1 (8) ◽  
Author(s):  
J. Meibohm ◽  
F. Candelier ◽  
T. Rosén ◽  
J. Einarsson ◽  
F. Lundell ◽  
...  
Keyword(s):  
Reynolds Number ◽  
Angular Velocity ◽  
Simple Shear ◽  
Small Reynolds Number

Small Reynolds Number Electro-Hydrodynamic Flow Around Drops and the Resulting Deformation

1979 ◽  
Vol 46 (3) ◽  
pp. 510-512 ◽  
Author(s):  
M. B. Stewart ◽  
F. A. Morrison
Keyword(s):  
Reynolds Number ◽  
Flow Field ◽  
Order Approximation ◽  
Creeping Flow ◽  
Small Reynolds Number ◽  
Zeroth Order ◽  
Regular Perturbation ◽  
Low Reynolds Number Flow ◽  
Reynolds Number Flow ◽  
Number Flow

Low Reynolds number flow in and about a droplet is generated by an electric field. Because the creeping flow solution is a uniformly valid zeroth-order approximation, a regular perturbation in Reynolds number is used to account for the effects of convective acceleration. The flow field and resulting deformation are predicted.

Drag force on micron-sized objects with different surface morphologies in a flow with a small Reynolds number

2015 ◽  
Vol 47 (8) ◽  
pp. 564-570 ◽  
Author(s):  
Arif Md. Rashedul Kabir ◽  
Daisuke Inoue ◽  
Yuri Kishimoto ◽  
Jun-ichi Hotta ◽  
Keiji Sasaki ◽  
...  
Keyword(s):  
Reynolds Number ◽  
Drag Force ◽  
Small Reynolds Number ◽  
Surface Morphologies

Parameter Extension Simulation of Turbulent Flows in a Compressor Cascade With a High Reynolds Number

2020 ◽  
Author(s):  
Yan Jin
Keyword(s):  
Reynolds Number ◽  
Turbulent Flow ◽  
Turbulent Flows ◽  
Stokes Equations ◽  
Simulation Method ◽  
Potential Method ◽  
Navier Stokes ◽  
Reference Solution ◽  
Compressor Cascade ◽  
High Reynolds

Abstract The turbulent flow in a compressor cascade is calculated by using a new simulation method, i.e., parameter extension simulation (PES). It is defined as the calculation of a turbulent flow with the help of a reference solution. A special large-eddy simulation (LES) method is developed to calculate the reference solution for PES. Then, the reference solution is extended to approximate the exact solution for the Navier-Stokes equations. The Richardson extrapolation is used to estimate the model error. The compressor cascade is made of NACA0065-009 airfoils. The Reynolds number 3.82 × 105 and the attack angles −2° to 7° are accounted for in the study. The effects of the end-walls, attack angle, and tripping bands on the flow are analyzed. The PES results are compared with the experimental data as well as the LES results using the Smagorinsky, k-equation and WALE subgrid models. The numerical results show that the PES requires a lower mesh resolution than the other LES methods. The details of the flow field including the laminar-turbulence transition can be directly captured from the PES results without introducing any additional model. These characteristics make the PES a potential method for simulating flows in turbomachinery with high Reynolds numbers.

Direct numerical simulation of turbulent channel flow up to

2015 ◽  
Vol 774 ◽  
pp. 395-415 ◽  
Author(s):  
Myoungkyu Lee ◽  
Robert D. Moser
Keyword(s):  
Numerical Simulation ◽  
Reynolds Number ◽  
Direct Numerical Simulation ◽  
Turbulent Flows ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Streamwise Velocity ◽  
Mean Velocity ◽  
Layer Structures ◽  
High Reynolds

A direct numerical simulation of incompressible channel flow at a friction Reynolds number ($\mathit{Re}_{{\it\tau}}$) of 5186 has been performed, and the flow exhibits a number of the characteristics of high-Reynolds-number wall-bounded turbulent flows. For example, a region where the mean velocity has a logarithmic variation is observed, with von Kármán constant ${\it\kappa}=0.384\pm 0.004$. There is also a logarithmic dependence of the variance of the spanwise velocity component, though not the streamwise component. A distinct separation of scales exists between the large outer-layer structures and small inner-layer structures. At intermediate distances from the wall, the one-dimensional spectrum of the streamwise velocity fluctuation in both the streamwise and spanwise directions exhibits $k^{-1}$ dependence over a short range in wavenumber $(k)$. Further, consistent with previous experimental observations, when these spectra are multiplied by $k$ (premultiplied spectra), they have a bimodal structure with local peaks located at wavenumbers on either side of the $k^{-1}$ range.

Direct Transmission Loss Calculation of Simplified Muffler Configurations Using a Lattice-Boltzmann Method

2013 ◽  
Author(s):  
Adrien Mann ◽  
Franck Pérot
Keyword(s):  
Lattice Boltzmann Method ◽  
Turbulent Flows ◽  
Spatial Resolution ◽  
Lattice Boltzmann ◽  
Transmission Loss ◽  
Fan Noise ◽  
Wind Noise ◽  
Simulation Domain ◽  
Flow Induced Noise ◽  
Boltzmann Method

Lattice-Boltzmann Method (LBM) is broadly used for the simulation of aeroacoustics problems. This time-domain CFD/CAA approach is transient, explicit and compressible and offers an accurate and efficient solution to simultaneously resolve turbulent flows and their corresponding flow-induced noise radiation. Some examples of applications are ground transportation wind-noise problems, buffeting, Heating, Ventilation, and Air Conditioning (HVAC), fan noise, etc. As shown in previous studies, LBM can also be used to accurately handle linear acoustics problems if the source of noise is not a flow but a simple acoustic source. This set of capabilities makes LBM a suitable candidate for evaluating the acoustics performances of exhaust systems and mufflers. Compared to other traditional acoustics methods, LBM presents the advantage to skip tedious volume meshing operations since the mesh generation is fully automatic. Furthermore, considering that all geometrical details are included in the simulation domain and that LBM is explicit, high frequencies mechanisms up to 10–20 kHz can be captured. The upper frequency limit is indeed solely driven by the spatial resolution used to discretize the system. In this paper, three academic 3-D geometries representative of production muffler systems are studied. Transmission Loss (TL) measurements are performed on three configurations and these experiments are reproduced numerically with LBM. The experimental setup is described in a first part and the numerical details are given in a second part and third part. In particular, the method used to calculate the TL in the simulation and the convergence of the results with respect to the spatial resolution are shown. In a third part, the simulations are compared to the TL measurements and a numerical investigation of the effect of geometry details on the simulated results is proposed. This study highlights the sensitivity of acoustics measurements to geometry details.

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