scholarly journals Experimental Assessment of RANS Models for Wind Load Estimation over Solar-Panel Arrays

2021 ◽  
Vol 11 (6) ◽  
pp. 2496
Author(s):  
Alejandro Güemes ◽  
Pablo Fajardo ◽  
Marco Raiola
Keyword(s):  
Separated Flow ◽  
Wind Load ◽  
Solar Panel ◽  
Navier Stokes ◽  
Large Reynolds Number ◽  
Pressure Measurements ◽  
Mean Flow ◽  
Shear Model ◽  
Rans Models ◽  
Reynolds Averaged Navier Stokes

This paper reports a comparison between wind-tunnel measurements and numerical simulations to assess the capabilities of Reynolds-Averaged Navier-Stokes models to estimate the wind load over solar-panel arrays. The free airstream impinging on solar-panel arrays creates a complex separated flow at large Reynolds number, which is severely challenging for the current Reynolds-Averaged Navier-Stokes models. The Reynolds-Averaged Navier-Stokes models compared in this article are k-ϵ, Shear-Stress Transport k-ω, transition and Reynolds Shear Model. Particle Image Velocimetry measurements are performed to investigate the mean flow-velocity and turbulent-kinetic-energy fields. Pressure taps are located in the surface of the solar panel model in order to obtain static pressure measurements. All the Reynolds-Averaged Navier-Stokes models predict accurate average velocity fields when compared with the experimental ones. One of the challenging factor is to predict correctly the thickness of the turbulent wake. In this aspect, Reynolds Shear provides the best results, reproducing the wake shrink observed on the 3rd panel in the experiment. On the other hand, some other features, most notably the blockage encountered by the flow below the panels, are not correctly reproduced by any of the models. The pressure distributions over the 1st panel obtained from the different Reynolds-Averaged Navier-Stokes models show good agreement with the pressure measurements. However, for the rest of the panels Reynolds-Averaged Navier-Stokes fidelity is severely challenged. Overall, the Reynolds Shear model provides the best pressure estimation in terms of pressure difference between the front and back sides of the panels.

Experimental and numerical analyses of gas–solid-multiphase jet in cross-flow

2012 ◽  
Vol 227 (1) ◽  
pp. 61-79 ◽  
Author(s):  
Yao Fu ◽  
Tong Wang ◽  
Chuangang Gu
Keyword(s):  
Flow Field ◽  
Transient Flow ◽  
Cross Flow ◽  
Jet Flow ◽  
Navier Stokes ◽  
Detached Eddy Simulation ◽  
Calculation Methods ◽  
Mean Flow ◽  
Eddy Simulation ◽  
Reynolds Averaged Navier Stokes

In this article, jet influence on a gas–solid-multiphase channel flow was experimentally and numerically studied. The jet flow was found to have a diameter-selective controlling effect on the particles’ distribution. Jet flow formed a gas barrier in the channel for particles. While tiny particles could travel around and large particles could travel through, only particles on the 10 -µm scale were obviously affected. Three different calculation methods, Reynolds averaged Navier–Stokes, unsteady Reynolds averaged Navier–Stokes, and detached eddy simulation, were used to simulate this multiphase flow. By comparing the calculation results to the experimental results, it is found that all the three calculation methods could capture the basic phenomenon in the mean flow field. Nevertheless, there exist great differences in the transient flow field and particle distribution.

Compressible Reynolds-Averaged Navier-Stokes Analysis of Wind Turbine Turbulent Flows Using a Fully-Coupled Low-Speed Preconditioned Multigrid Solver

2014 ◽  
Author(s):  
M. S. Campobasso ◽  
M. Yan ◽  
J. Drofelnik ◽  
A. Piskopakis ◽  
M. Caboni
Keyword(s):  
Turbulence Model ◽  
Static Pressure ◽  
Navier Stokes ◽  
Acoustic Analogy ◽  
Mean Flow ◽  
Noise Propagation ◽  
Low Speed ◽  
Analysis And Design ◽  
Reynolds Averaged Navier Stokes ◽  
Fully Coupled

The high-fidelity aeromechanical analysis and design of multi-megawatt horizontal axis wind turbines can be performed by means of Reynolds-averaged Navier-Stokes codes. The compressible or incompressible formulation of the fluid equations can be used. One of the objectives of the paper is to quantify the effects of flow compressibility on the aerodynamics of large turbine rotors with particular attention to the tip region of a 82 m rotor blade featuring a relative Mach number of about 0.3 near rated conditions. Noticeable local static pressure variations due to compressibility are observed. Such variations point to the better suitability of compressible solvers for turbine aerodynamics, not only when the solver is used for direct aeroacoustic simulation of the near field noise propagation, but also when it is used to provide the surface static pressure to be used as input for acoustic analogy noise propagation codes. On the numerical side, a novel numerical approach to low-speed preconditioning of the mean flow and turbulence model equations for the fully coupled integration of the flow equations coupled to a two-equation turbulence model is presented and implemented in a compressible Navier-Stokes research code for the steady and yawed wind-induced time-dependent flows analyzed herein.

scholarly journals Comparison and verification of turbulence Reynolds-averaged Navier–Stokes closures to model spatially varied flows

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Kudzai Chipongo ◽  
Mehdi Khiadani ◽  
Kaveh Sookhak Lari
Keyword(s):  
Water Surface ◽  
Turbulence Models ◽  
Flow Region ◽  
Reynolds Stress Model ◽  
Navier Stokes ◽  
Leeward Side ◽  
Lateral Inflow ◽  
Rans Turbulence Models ◽  
Rans Models ◽  
Reynolds Averaged Navier Stokes

Abstract The robustness and accuracy of Reynolds-averaged Navier–Stokes (RANS) models was investigated for complex turbulent flow in an open channel receiving lateral inflow, also known as spatially varied flow with increasing discharge (SVF). The three RANS turbulence models tested include realizable k–ε, shear stress transport k–ω and Reynolds stress model based on their prominence to model jets in crossflows. Results were compared to experimental laser Doppler velocimetry measurements from a previous study. RANS results in the uniform flow region and farther from the jet centreline were more accurate than within the lateral inflow region. On the leeward side of the jet, RANS models failed to capture the downward velocity vectors resulting in major deviations in vertical velocity. Among RANS models minor variations were noted at impingement and near the water surface. Regardless of inadequately predicting complex characteristics of SVF, RANS models matched experimental water surface profiles and proved more superior to the theoretical approach currently used for design purposes.

Thermofluid Characteristics of Czochralski Melt Convection Using 3D URANS Computations

2019 ◽  
Vol 11 (6) ◽  
Author(s):  
Sudeep Verma ◽  
Anupam Dewan
Keyword(s):  
Turbulence Modeling ◽  
Three Dimensional ◽  
Comparative Assessment ◽  
Navier Stokes ◽  
Thermal Gradients ◽  
Melt Flow ◽  
Turbulent Characteristics ◽  
Eddy Structures ◽  
Rans Models ◽  
Reynolds Averaged Navier Stokes

Turbulent characteristics of Czochralski melt flow are presented using the unsteady Reynolds-averaged Navier–Stokes (URANS) turbulence modeling approach. Three-dimensional, transient computations were performed using the Launder and Sharma low-Re k-ε model and Menter shear stress transport (SST) k-ω model on an idealized Czochralski setup with counterrotating crystal and crucible. A comparative assessment is performed between these two Reynolds-averaged Navier–Stokes (RANS) models in capturing turbulent thermal and flow behaviors. It was observed that the SST k-ω model predicted a better resolution of the Czochralski melt flow capturing the near wall thermal gradients, resolving stronger convective flow at the melt free surface, deciphering more number of characteristics Czochralski recirculating cells along with predicting large number of coherent eddy structures and vortex cores distributed in the melt and hence a larger level of turbulent intensity in the Czochralski melt compared with that by Launder and Sharma low-Re k-ε model.

Note on Turbulent Kinetic Energy Production for Reynolds-Averaged Navier–Stokes Models

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Solkeun Jee ◽  
Gorazd Medic ◽  
Georgi Kalitzin
Keyword(s):  
Kinetic Energy ◽  
Strain Rate ◽  
Turbulent Kinetic Energy ◽  
Energy Equation ◽  
Boussinesq Approximation ◽  
Navier Stokes ◽  
Mean Flow ◽  
Production Term ◽  
The Mean ◽  
Reynolds Averaged Navier Stokes

Linear eddy-viscosity Reynolds-Averaged Navier–Stokes (RANS) turbulence models are based on the Boussinesq approximation that asserts the Reynolds stresses to be linearly dependent on the mean strain rate. Using the Boussinesq approximation for the Reynolds stress yields a production term in the turbulent kinetic energy equation that is proportional to the square of the magnitude of the strain rate tensor. For some flows, this relation to the strain causes overproduction of turbulence. Widely used ad hoc modifications of the production term using vorticity lead to an inconsistent energy balance in the mean flow kinetic energy equation, violating the energy conservation. In this note, how to obtain a consistent RANS framework for a given production term modification is shown.

Computer Simulations of Airflow Field Around a Cube: Comparisons of LES and RANS Models

2010 ◽  
Author(s):  
Behtash Tavakoli ◽  
Goodarz Ahmadi
Keyword(s):  
Experimental Data ◽  
Computational Models ◽  
Transport Model ◽  
Separated Flow ◽  
Realistic Model ◽  
Navier Stokes ◽  
Reynolds Stress Transport Model ◽  
Rans Models ◽  
Airflow Field ◽  
Computationally Intensive

Simulations of flow field around wall mounted square cylinders have been used extensively for validation of computational models in the literature. In this paper the airflow fields around a square cylinder were simulated using the Reynolds Averaged Navier-Stokes (RANS) models as well as the Large Eddy Simulations (LES). Particular attention was given to the case with Reynolds number of 80,000 for which the experimental data of Hussein and Matinuzzi [1] are available. The nature of the 3D wakes behind the cube as well as the vortices in front and at the back of the cube were investigated. The simulation results were compared with the experimental data and the accuracy of different models were studied. While the LES better captured the features of this separated flow, it is computationally intensive. The Reynolds Stress Transport Model (RSTM) did not properly predict some features of this separated flow, but is comparatively more economical. The accuracy of RSTM for predicting the turbulence features of separated flows was discussed, and its application for the flow around a realistic model of a building was pointed out.

scholarly journals A data-assimilation method for Reynolds-averaged Navier–Stokes-driven mean flow reconstruction

2014 ◽  
Vol 759 ◽  
pp. 404-431 ◽  
Author(s):  
Dimitry P. G. Foures ◽  
Nicolas Dovetta ◽  
Denis Sipp ◽  
Peter J. Schmid
Keyword(s):  
Data Assimilation ◽  
Stokes Equations ◽  
Navier Stokes ◽  
Infinite Cylinder ◽  
Time Averaging ◽  
Identification Algorithm ◽  
Mean Flow ◽  
Flow Measurements ◽  
Navier Stokes Equations ◽  
Reynolds Averaged Navier Stokes

AbstractWe present a data-assimilation technique based on a variational formulation and a Lagrange multipliers approach to enforce the Navier–Stokes equations. A general operator (referred to as the measure operator) is defined in order to mathematically describe an experimental measure. The presented method is applied to the case of mean flow measurements. Such a flow can be described by the Reynolds-averaged Navier–Stokes (RANS) equations, which can be formulated as the classical Navier–Stokes equations driven by a forcing term involving the Reynolds stresses. The stress term is an unknown of the equations and is thus chosen as the control parameter in our study. The data-assimilation algorithm is derived to minimize the error between a mean flow measurement and the measure performed on a numerical solution of the steady, forced Navier–Stokes equations; the optimal forcing is found when this error is minimal. We demonstrate the developed data-assimilation framework on a test case: the two-dimensional flow around an infinite cylinder at a Reynolds number of $\mathit{Re}=150$. The mean flow is computed by time-averaging instantaneous flow fields from a direct numerical simulation (DNS). We then perform several ‘measures’ on this mean flow and apply the data-assimilation method to reconstruct the full mean flow field. Spatial interpolation, extrapolation, state vector reconstruction and noise filtering are considered independently. The efficacy of the developed identification algorithm is quantified for each of these cases and compared with more traditional methods when possible. We also analyse the identified forcing in terms of unsteadiness characterization, present a way to recover the second-order statistical moments of the fluctuating velocities and finally explore the possibility of pressure reconstruction from velocity measurements.

scholarly journals Evaluation of two wind flow models for wind resource assessment for a site

2020 ◽  
Vol 167 ◽  
pp. 05001
Author(s):  
Vilas Warudkar ◽  
Pramod Sharma ◽  
Siraj Ahmed
Keyword(s):  
Numerical Models ◽  
Resource Assessment ◽  
Navier Stokes ◽  
Wind Flow ◽  
Flow Models ◽  
Wind Resource Assessment ◽  
Rans Models ◽  
Reynolds Averaged Navier Stokes ◽  
A Site ◽  
Wind Resource

There are different numerical wind flow models are existing to simulate atmosphere flows. The conventional approach has been relying on JacksonHunt linear wind flow models, computational fluid dynamics and Reynolds- averaged Navier Stokes models has been explored in research to predict wind resource for a site. The present work aims to analyze the performance of two wind flow models to predict the variation of wind speed. The two are 1) WAsP (linear JacksonHunt model) and 2) CFD/RANS models. The wind flow numerical models are compared with high-quality measurements from single meteorological mast. It has been found that the root meant square error for the WAsP model is 23% greater than the Reynolds- averaged Navier Stokes model.

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