Particle Trajectory Study in Submerged Flows With Baffles Using ν2¯−f and k−ε Turbulence Models

2010 ◽  
Vol 132 (5) ◽  
Author(s):  
A. Mehdizadeh ◽  
B. Firoozabadi ◽  
S. A. Sherif
Keyword(s):  
Turbulence Model ◽  
Turbulence Models ◽  
Navier Stokes ◽  
Test Case ◽  
Complex Flow ◽  
Two Phase ◽  
Erosion And Deposition ◽  
Flow Features ◽  
Elliptic Relaxation ◽  
Surface Jet

In this paper, the structure of a wall jet deflected by a baffle along with the trajectory of particles has been studied. This baffle is used to produce a stable deflected surface jet, thereby deflecting the high-velocity supercritical stream away from the bed to the surface. An elliptic relaxation turbulence model (ν2¯−f model) has been used to simulate this submerged flow. In recent years, the ν2¯−f turbulence model has become increasingly popular due to its ability to account for near-wall damping without use of damping functions. In addition, it has been proven that the ν2¯−f model is superior to other Reynolds-averaged Navier-Stokes (RANS) methods in many flows where complex flow features are present. In this study, we compare the results of the ν2¯−f model with available experimental data. Since erosion and deposition are coupled, the study of this problem should consider both of these phenomena using a proper approach. In addition to erosion over the bed, the trajectory of the particles is examined using a Lagrangian–Eulerian approach, the distribution of deposited particles over the bed is predicted for a two-phase test case based on a series of numerical simulations. Results show that the maximum erosion happens in a place in which no particle can be deposited, which causes the bed to deform very rapidly in that region. This should help prevent or reduce erosion over the bed. On the other hand, the study will help predict the trajectory of particles and the deposition rates at any section of the channel, and should thus provide useful information to control the erosion and deposition on the channel bed.

Numerical Simulation of Submerged Flows With Baffles Using v2-f- and k-e Turbulence Models

2006 ◽  
Author(s):  
A. Mehdizadeh ◽  
B. Firoozabadi ◽  
S. A. Sherif
Keyword(s):  
Experimental Data ◽  
Numerical Simulation ◽  
Turbulence Model ◽  
Turbulence Models ◽  
Fluid Flows ◽  
Complex Flow ◽  
Flow Features ◽  
Elliptic Relaxation ◽  
Surface Jet ◽  
Submerged Hydraulic Jump

This paper introduces the concept of a submerged hydraulic jump being used for energy dissipation. A baffle wall is used to produce a stable deflected surface jet, thereby deflecting the high-velocity supercritical stream away from the bed to the surface. An elliptic relaxation turbulence model ([Equation] - f model) has been used to simulate this submerged flow. During the last few years, the [Equation] - f turbulence model has become increasingly popular due to its ability to account for near-wall damping without use of damping functions. In addition, it has been proved that the [Equation] - f model is superior to other RANS methods in many fluid flows where complex flow features are present. In this study, we compared the results of both models with each other and with available experimental data. In addition, based on a series of numerical simulations, a diagram was developed that predicts the effect of baffle position on the friction coefficient over the bed. This feature should help preventing or reducing erosion over the bed. Moreover, we have shown that in numerical simulation, like experimental data, in some cases the flow regimes of submerged flow with baffles can either be a deflected surface jet or reattached wall jet.

Multiscale Partially Averaged Navier Stokes Approach for the Prediction of Flow in Linear Compressor Cascade With Moving Casing

2011 ◽  
Author(s):  
Domenico Borello ◽  
Giovanni Delibra ◽  
Franco Rispoli
Keyword(s):  
Turbulence Models ◽  
Navier Stokes ◽  
Test Case ◽  
Compressor Cascade ◽  
Preliminary Assessment ◽  
Linear Compressor ◽  
Tip Leakage ◽  
Experimental Campaign ◽  
Elliptic Relaxation ◽  
Linear Compressor Cascade

In this paper we present an innovative Partially Averaged Navier Stokes (PANS) approach for the simulation of turbomachinery flows. The elliptic relaxation k-ε-ζ-f model was used as baseline Unsteady Reynolds Averaged Navier Stokes (URANS) model for the derivation of the PANS formulation. The well established T-FlowS unstructured finite volume in-house code was used for the computations. A preliminary assessment of the developed formulation was carried out on a 2D hill flow that represents a very demanding test case for turbulence models. The turbomachinery flow here investigated reproduces the experimental campaign carried out at Virginia Tech on a linear compressor cascade with tip leakage. Their measurements were used for comparisons with numerical results. The predictive capabilities of the model were assessed through the analysis of the flow field. Then an investigation of the blade passage, where experiments were not available, was carried out to detect the main loss sources.

scholarly journals Numerical simulation of compressible cavitating two-phase flows with a pressure-based solver

2017 ◽  
Author(s):  
Marco Cristofaro ◽  
Wilfried Edelbauer ◽  
Manolis Gavaises ◽  
Phoevos Koukouvinis
Keyword(s):  
Stokes Equations ◽  
Navier Stokes ◽  
Test Case ◽  
Time Step ◽  
Two Phase ◽  
Navier Stokes Equations ◽  
Liquid Phases ◽  
Flow Features ◽  
Liquid Evaporation ◽  
Semi Empirical

This work intends to study the effect of compressibility on throttle flow simulations with a pressure–based solver.The simple micro throttle geometry allows easier access for obtaining experimental data compared to a real injector, but still maintaining the main flow features. For this reasons it represents a meaningful and well reported benchmark for validation of numerical methods developed for cavitating injector flows.An implicit pressure–based compressible solver is used on the filtered Navier–Stokes equations. Thus, no stability limitation is applied on the time step. A common pressure field is computed for all phases, but different velocity fields are solved for each phase, following the multi–fluid approach. The liquid evaporation rate is evaluated with a Rayleigh–Plesset equation based cavitation model and the Coherent Structure Model is adopted as closure for the sub–grid scales in the momentum equation.The aim of this study is to show the capabilities of the pressure–based solver to deal with both vapor and liquid phases considered compressible. A comparison between experimental results and compressible simulations is presented. Time–averaged vapor distribution and velocity profiles are reported and discussed.  The distribution of pressure maxima on the surface and the results from a semi–empirical erosion model are in good agreement with the erosion locations observed in the experiments. This test case aims to represent a benchmark for furtherapplication of the methodology to industrial relevant cases.DOI: http://dx.doi.org/10.4995/ILASS2017.2017.4629

Uncertainty Quantification of Spalart–Allmaras Turbulence Model Coefficients for Simplified Compressor Flow Features

2020 ◽  
Vol 142 (9) ◽  
Author(s):  
Xiao He ◽  
Fanzhou Zhao ◽  
Mehdi Vahdati
Keyword(s):  
Turbulence Model ◽  
Parametric Uncertainty ◽  
Navier Stokes ◽  
Stress Profile ◽  
Complex Flow ◽  
Flow Solver ◽  
Uniform Distributions ◽  
Flow Features ◽  
Artificial Neural Network Ann ◽  
Quantities Of Interest

Abstract Turbulence model in Reynolds-averaged Navier–Stokes (RANS) simulations has a crucial effect on predicting the compressor flows. In this paper, the parametric uncertainty of the Spalart–Allmaras (SA) turbulence model is studied in simplified two-dimensional (2D) flows, which includes some of the compressor tip flow features. The uncertainty is quantified by a metamodel-based Monte Carlo method. The model coefficients are represented by uniform distributions within intervals, and the quantities of interest include the velocity profile, the Reynolds stress profile, the shock front, and the separation size. An artificial neural network (ANN) is applied as the metamodel, which is tuned, trained, and tested using databases from the flow solver. The uncertainty of quantities of interest is determined by the range of the metamodel and the database samples from the flow solver. The sensitivity of the model coefficients is quantified by calculating the gradient of quantities of interest from the metamodel. Results show that the high-fidelity data of the quantities of interest cannot be fully enveloped by the uncertainty band in regions with separation and shock. Crucial model coefficients on the quantities of interest are identified. However, recalibration of these coefficients results in contradictory prediction of different quantities of interest across flow regimes, which indicates the need for a modified Spalart–Allmaras turbulence model form to improve the accuracy in predicting complex flow features.

Application of the v2-f Turbulence Model to Turbomachinery Configurations

2007 ◽  
Author(s):  
B. Tartinville ◽  
E. Lorrain ◽  
Ch. Hirsch
Keyword(s):  
Heat Transfer ◽  
Turbulence Model ◽  
Turbulence Models ◽  
Critical Issue ◽  
Secondary Flows ◽  
Navier Stokes ◽  
Test Cases ◽  
Laminar To Turbulent Transition ◽  
Turbulent Transition ◽  
Flow Features

Enhancing the representation of turbulence processes is a critical issue for CFD codes devoted to turbomachinery industry. Though more complex methods are available, Reynolds-Averaged Navier-Stokes models are widely used in the daily design process. Therefore, there is a constant need for improving eddy-viscosity based turbulence models. The present work aims at investigating the capabilities of the v2-f turbulence model for turbomachinery applications. Three types of flow features that are of importance for such applications are investigated in details: heat transfer, secondary flows, and laminar to turbulent transition. From a series of test cases, it appears that the v2-f turbulence model is specially adapted for heat transfer applications and shows potentialities in predicting laminar to turbulent transition.

scholarly journals Turbulence model performance for ventilation components pressure losses

2021 ◽  
Author(s):  
Karsten Tawackolian ◽  
Martin Kriegel
Keyword(s):  
Reynolds Number ◽  
Turbulence Model ◽  
Pressure Loss ◽  
Low Reynolds Number ◽  
Turbulence Models ◽  
Reynolds Numbers ◽  
Test Case ◽  
Pressure Losses ◽  
Loss Coefficients ◽  
Near Wall

AbstractThis study looks to find a suitable turbulence model for calculating pressure losses of ventilation components. In building ventilation, the most relevant Reynolds number range is between 3×104 and 6×105, depending on the duct dimensions and airflow rates. Pressure loss coefficients can increase considerably for some components at Reynolds numbers below 2×105. An initial survey of popular turbulence models was conducted for a selected test case of a bend with such a strong Reynolds number dependence. Most of the turbulence models failed in reproducing this dependence and predicted curve progressions that were too flat and only applicable for higher Reynolds numbers. Viscous effects near walls played an important role in the present simulations. In turbulence modelling, near-wall damping functions are used to account for this influence. A model that implements near-wall modelling is the lag elliptic blending k-ε model. This model gave reasonable predictions for pressure loss coefficients at lower Reynolds numbers. Another example is the low Reynolds number k-ε turbulence model of Wilcox (LRN). The modification uses damping functions and was initially developed for simulating profiles such as aircraft wings. It has not been widely used for internal flows such as air duct flows. Based on selected reference cases, the three closure coefficients of the LRN model were adapted in this work to simulate ventilation components. Improved predictions were obtained with new coefficients (LRNM model). This underlined that low Reynolds number effects are relevant in ventilation ductworks and give first insights for suitable turbulence models for this application. Both the lag elliptic blending model and the modified LRNM model predicted the pressure losses relatively well for the test case where the other tested models failed.

scholarly journals Development of a Numerical Investigation Framework for Ground Vehicle Platooning

Fluids ◽  
2021 ◽  
Vol 6 (11) ◽  
pp. 404
Author(s):  
Charles Patrick Bounds ◽  
Sudhan Rajasekar ◽  
Mesbah Uddin
Keyword(s):  
Turbulence Model ◽  
Turbulence Models ◽  
Navier Stokes ◽  
Ground Vehicle ◽  
Simulation Methodology ◽  
Vehicle Platooning ◽  
Length Separation ◽  
Dynamics Simulations ◽  
The Impact ◽  
Far Wake

This paper presents a study on the flow dynamics involving vehicle interactions. In order to do so, this study first explores aerodynamic prediction capabilities of popular turbulence models used in computational fluid dynamics simulations involving tandem objects and thus, ultimately presents a framework for CFD simulations of ground vehicle platooning using a realistic vehicle model, DrivAer. Considering the availability of experimental data, the simulation methodology is first developed using a tandem arrangement of surface-mounted cubes which requires an understanding on the role of turbulence models and the impacts of the associated turbulence model closure coefficients on the prediction veracity. It was observed that the prediction accuracy of the SST k−ω turbulence model can be significantly improved through the use of a combination of modified values for the closure coefficients. Additionally, the initial validation studies reveal the inability of the Unsteady Reynolds-Averaged Navier-Stokes (URANS) approach to resolve the far wake, and its frailty in simulating tandem body interactions. The Improved Delayed Detached Eddy Simulations (IDDES) approach can resolve the wakes with a reasonable accuracy. The validated simulation methodology is then applied to the fastback DrivAer model at different longitudinal spacing. The results show that, as the longitudinal spacing is reduced, the trailing car’s drag is increased while the leading car’s drag is decreased which supports prior explanations of vortex impingement as the reason for drag changes. Additionally, unlike the case of platooning involving Ahmed bodies, the trailing model drag does not return to an isolated state value at a two car-length separation. However, the impact of the resolution of the far wake of a detailed DrivAer model, and its implication on the CFD characterization of vehicle interaction aerodynamics need further investigations.

Large Eddy Simulation of the Heat Transfer Due to Swirling and Non-Swirling Jet Impingement

2008 ◽  
Author(s):  
Naseem Uddin ◽  
S. O. Neumann ◽  
B. Weigand
Keyword(s):  
Heat Transfer ◽  
Turbulence Models ◽  
Jet Impingement ◽  
Impinging Jet ◽  
Test Case ◽  
Complex Flow ◽  
Free Jet ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Target Wall

Turbulent impinging jet is a complex flow phenomenon involving free jet, impingement and subsequent wall jet development zones; this makes it a difficult test case for the evaluation of new turbulence models. The complexity of the jet impingement can be further amplified by the addition of the swirl. In this paper, results of Large Eddy Simulations (LES) of swirling and non-swirling impinging jet are presented. The Reynolds number of the jet based on bulk axial velocity is 23000 and target-to-wall distance (H/D) is two. The Swirl numbers (S) of the jet are 0,0.2, 0.47. In swirling jets, the heat transfer at the geometric stagnation zone deteriorates due to the formation of conical recirculation zone. It is found numerically that the addition of swirl does not give any improvement for the over all heat transfer at the target wall. The LES predictions are validated by available experimental data.

Application of Wray-Agarwal turbulence model for numerical simulation of gas-solid flows in CFB risers

2021 ◽  
pp. 1-25
Author(s):  
Yali Shao ◽  
Ramesh K. Agarwal ◽  
Xudong Wang ◽  
Baosheng Jin
Keyword(s):  
Turbulence Model ◽  
Circulating Fluidized Bed ◽  
Volume Fraction ◽  
Solid Phase ◽  
Solid Volume Fraction ◽  
Turbulence Models ◽  
Two Phase ◽  
Efficient Simulation ◽  
Pressure Profiles ◽  
First Time

Abstract In recent decades, increasing attention has been focused on accurate modeling of circulating fluidized bed (CFB) risers to provide valuable guidance to design, optimization and operation of reactors. Turbulence model plays an important role in accurate prediction of complex gas-solid flows. Recently developed Wray-Agarwal (WA) model is a one-equation turbulence model with the advantages of high computational efficiency and competitive accuracy with two-equation models. In this paper for the first time, Eulerian-Eulerian approach coupled with different turbulence models including WA model, standard κ-ε model and shear stress transport (SST) κ-ω model is employed to simulate two-phase flows of gas phase and solid phase in two CFB risers, in order to assess accuracy and efficiency of WA model compared to other well-known two-equation models. Predicted gas-solid flow dynamic characteristics including the gas-solid volume fraction distributions in radial and axial directions, pressure profiles and solid mass flux distributions are compared with data obtained from experiment in detail. The results demonstrate WA model is very promising for accurate and efficient simulation of gas-solid multiphase flows.

Study on Influence of Nozzle Structure on Flow in Diesel Nozzle Orifice

2012 ◽  
Vol 246-247 ◽  
pp. 127-130
Author(s):  
Bing Li ◽  
Xue Song Hu ◽  
Xiao Feng Cao ◽  
Gui Qi Jia ◽  
Fang Xi Xie ◽  
...  
Keyword(s):  
Flow Characteristics ◽  
Internal Flow ◽  
Key Factors ◽  
Complex Flow ◽  
Two Phase ◽  
Nozzle Orifice ◽  
Fuel Flow ◽  
Flow Features ◽  
Diesel Nozzle ◽  
Nozzle Hole

The fuel flow characteristics in diesel nozzle orifice are key factors to the atomization of fuel near the nozzle orifice. In the paper, two-phase flow model is used to simulate the complex flow features in nozzle orifice, and to study the influences of the relative position of nozzles orifice axis and nozzle axis, and inclination angle of nozzle hole on the internal flow feature.

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