Comparative study on numerical performances of log-conformation representation and standard conformation representation in the simulation of viscoelastic fluid turbulent drag-reducing channel flow

2021 ◽  
Vol 33 (2) ◽  
pp. 023101
Author(s):  
Wen-Hua Zhang ◽  
Jingfa Li ◽  
Qiankun Wang ◽  
Yu Ma ◽  
Hong-Na Zhang ◽  
...  
Keyword(s):  
Comparative Study ◽  
Channel Flow ◽  
Viscoelastic Fluid ◽  
Turbulent Drag

Effects of Surfactant Additives on Flow Characteristics at Different Wall-Normal Locations in Turbulent Channel Flow

2016 ◽  
Author(s):  
Lu Wang ◽  
Zhi-Ying Zheng ◽  
Ping-An Liu ◽  
Yue Wang ◽  
Wei-Hua Cai ◽  
...  
Keyword(s):  
Buffer Layer ◽  
Channel Flow ◽  
Viscoelastic Fluid ◽  
Reynolds Shear Stress ◽  
Scaling Law ◽  
Flow Characteristics ◽  
Turbulent Channel Flow ◽  
Flow Properties ◽  
Substrate Layer ◽  
Turbulent Drag

Large eddy simulation (LES) was performed for turbulent channel flow with and without surfactant additives at Reτ = 590. Since turbulent channel flow can be divided into linear substrate layer, buffer layer, logarithm layer and outer layer along the wall-normal direction, so study on the flow properties at different layers in turbulent channel flow of viscoelastic fluid is significant for investigating turbulent drag-reducing mechanism and realizing the control of turbulent drag-reducing flow in the future. In this present work, the influences of surfactant additives on flow properties at different y locations were analyzed by researching the mean streamwise velocity, the root-mean-square velocity fluctuations, Reynolds shear stress and the contributions of different parts to turbulent kinetic energy, as well as the scaling law for four layers by two-dimensional wavelet transform. From the viewpoint of the above results, it is showed that the buffer layer tends to get wider in viscoelastic fluid and it is also demonstrated that viscoelastic effect mainly inhibits the coherent structures in the buffer layer, which are ejected from the linear substrate layer.

scholarly journals Comparative Study of Standard Smagorinsky Model and Dynamic Smagorinsky Model in Large Eddy Simulation of Turbulent Channel Flow

2020 ◽  
Vol 12 (1) ◽  
pp. 39-53
Author(s):  
M. S. I. Mallik ◽  
M. A. Hoque ◽  
M. A. Uddin
Keyword(s):  
Large Eddy Simulation ◽  
Comparative Study ◽  
Channel Flow ◽  
Flow Simulation ◽  
Turbulent Channel Flow ◽  
Smagorinsky Model ◽  
Order Accuracy ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Contour Plots

This paper presents results of comparative study of large eddy simulation (LES) that is applied to a plane turbulent channel flow. The LES is performed by using a finite difference method of second order accuracy in space and a low-storage explicit Runge-Kutta method with third order accuracy in time. In the LES for subgrid-scale (SGS) modelling, Standard Smagorinsky Model (SSM) and Dynamic Smagorinsky Model (DSM) are used. Essential turbulence statistics from the two LES approaches are calculated and compared with those from direct numerical simulation (DNS) data. Comparing the results throughout the calculation domain, it has been found out that SSM performs better than DSM in the turbulent channel flow simulation. Flow structures in the computed flow field by the SSM and DSM are also discussed and compared through the contour plots and iso-surfaces.

Predictability Study of Viscoelastic Turbulent Channel Flow Using Deep Learning

2019 ◽  
Author(s):  
Atsushi Nagamachi ◽  
Takahiro Tsukahara
Keyword(s):  
Channel Flow ◽  
Viscoelastic Fluid ◽  
Coherent Structures ◽  
Turbulent Channel Flow ◽  
Wall Region ◽  
Nonlinear Relationship ◽  
Multi Layer Perceptron ◽  
Numerical Instability ◽  
Z Score ◽  
Score Normalization

Abstract We tested Artificial Neural Networks (ANNs) to predict a fully-developed turbulent channel flow of a viscoelastic fluid in preparation for elucidating flow phenomenon and solving the difficulty in DNS (Direct Numerical Simulation) due to numerical instability of the viscoelastic fluid. Two kinds of ANNs (multi-layer perceptron (MLP) and U-Net) were trained using DNS data to predict conformation stress from given instantaneous field. The MLP showed accurate predictions and predictions got better with z-score normalization. ANN predicted accurately in near-wall region having coherent structures. In addition, we demonstrated that ANN get the nonlinear relationship between velocity gradient and viscoelastic stress partially.

Extended Self-Similarity in Drag-Reduced Turbulent Flow of Viscoelastic Fluid

2010 ◽  
Author(s):  
Feng-Chen Li ◽  
Hong-Na Zhang ◽  
Wei-Hua Cai ◽  
Juan-Cheng Yang
Keyword(s):  
Channel Flow ◽  
Viscoelastic Fluid ◽  
Isotropic Turbulence ◽  
Scaling Law ◽  
Viscoelastic Fluids ◽  
Turbulent Channel Flow ◽  
Elastic Model ◽  
Homogeneous Isotropic Turbulence ◽  
Self Similarity ◽  
Extended Self

Direct numerical simulations (DNS) have been performed for drag-reduced turbulent channel flow with surfactant additives and forced homogeneous isotropic turbulence with polymer additives. Giesekus constitutive equation and finite extensible nonlinear elastic model with Peterlin closure were used to describe the elastic stress tensor for both cases, respectively. For comparison, DNS of water flows for both cases were also performed. Based on the DNS data, the extended self-similarity (ESS) of turbulence scaling law is investigated for water and viscoelastic fluids in turbulent channel flow and forced homogeneous isotropic turbulence. It is obtained that ESS still holds for drag-reduced turbulent flows of viscoelastic fluids. In viscoelastic fluid flows, the regions at which δu(r)∝r and Sp(r)∝S3(r)ζ(p) with ζ(p) = p/3, where r is the scale length, δu(r) is the longitudinal velocity difference along r and Sp(r) is the pth-order moment of velocity increments, in the K41 (Kolmogorov theory)-fashioned plots and ESS-fashioned plots, respectively, are all broadened to larger scale for all the investigated cases.

Turbulent drag reduction in channel flow with viscosity stratified fluids

2018 ◽  
Vol 176 ◽  
pp. 260-265 ◽  
Author(s):  
Somayeh Ahmadi ◽  
Alessio Roccon ◽  
Francesco Zonta ◽  
Alfredo Soldati
Keyword(s):  
Drag Reduction ◽  
Channel Flow ◽  
Stratified Fluids ◽  
Turbulent Drag Reduction ◽  
Turbulent Drag

Simulation Results for Micro-Bubbles and Turbulent Drag Reduction (Keynote)

2003 ◽  
Author(s):  
M. R. Maxey ◽  
J. Xu ◽  
S. Dong ◽  
G. E. Karniadakis
Keyword(s):  
Drag Reduction ◽  
Numerical Simulations ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Turbulent Drag Reduction ◽  
Void Fractions ◽  
Turbulent Drag ◽  
Simulation Results ◽  
Small Bubbles ◽  
Near Wall

A series of numerical simulations of small bubbles seeded in a turbulent channel flow have been made at average void fractions up to 10%. Initial near-wall seeding in general leads to a transient reduction in drag while smaller bubbles are more effective in producing sustained drag reduction.

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