Turbulence Model Constants Research Articles

Fluid Flow and Effect of Turbulence Model on Large-Sized Triple-Offset Butterfly Valve

The performance a valve has been frequently estimated with numerical methods owing to limitations such as cost and place. In this study, for the triple-offset butterfly valves, the different sizes in various disc-opening cases was numerically conducted using different turbulence models of the two-equation turbulence models of k–ε, k-ω, and Reynolds stress model. The numerical calculations were validated against experimentally obtained valve flow test results. The numerical effect with the different turbulence models were analyzed with respect to the disc-opening cases. From the numerical analysis, the Reynolds stress model exhibits the most pronounced turbulence effects among the various turbulence models showing higher value of Reynolds normal stress near the valve disc region. The sensitivity of the turbulence model constants was examined using the 300 mm valve to observe the sensitivity of the turbulence model parameters in the two-equation turbulence models.

Calibration of Turbulent Model Constants Based on Experimental Data Assimilation: Numerical Prediction of Subsonic Jet Flow Characteristics

Experimental measurements and numerical simulations are two primary methods for studying turbulence. However, these methods often struggle to balance the accuracy and breadth of results. In order to accurately predict the flow characteristics of subsonic jet exhaust and provide a research foundation for the runway crossing operation after the takeoff point, this study utilizes the ensemble Kalman filter algorithm to recalibrate the SA turbulence model constants by integrating NASA’s experimental particle image velocimetry (PIV) data with a sample library generated using Latin hypercube sampling to obtain corresponding flow field calculations. The modified model constants effectively improve the prediction of jet flow characteristics, reducing the spatially averaged relative error along the horizontal axis behind the nozzle from 13.04% to 4.6%. This study focuses on enhancing the accuracy of numerical predictions for subsonic jet flows via the adjustment of turbulence model constants. The recalibrated model constants are then validated to improve the prediction of jet flows under various conditions. The findings have important implications for acquiring high-fidelity data on rear engine jet flows after takeoff, enabling precise determination of safety separation distances, and enhancing the operational efficiency of airports.

Bayesian Parameter Estimation of the k-ω Shear Stress Transport Model for Accurate Simulations of Impinging-Jet Heat Transfer

Given the lack of fusion-relevant component test facilities, current estimates of the thermo-fluid performance of plasma-facing components are based for the most part on numerical simulations. A major source of uncertainty in these simulations is the semiempirical turbulence (closure) models for the Reynolds stresses appearing in the governing Reynolds-averaged Navier-Stokes equations, which involve a set of constants that depend upon the flow. The objective of this study is to evaluate Bayesian parameter estimation of turbulence closure constants in ANSYS Fluent to model heat transfer in impinging jets. The Bayesian statistical calibration produces a probability distribution for these constants from experimental data; the maximum a posteriori estimates are then taken to be the calibrated constants, or parameters. The turbulence model constants are calibrated using an experimental study of a submerged jet of air impinging on a flat heated surface at Reynolds numbers Re = O(104) and impingement distance in jet diameters H/d = 2. Numerical predictions using the calibrated model parameters are then compared with those generated using the default constants. Predictions obtained with model parameters calibrated on datasets of two different sizes are compared to evaluate the effect of the number of calibration samples. Finally, the extrapolative ability of the calibrated model is examined by predictions at a Re beyond the calibration values.

Numerical prediction of heat transfer performance of plate heat exchanger based on experimental data assimilation to calibrate turbulence model constants

• Apply Data Assimilation to the study of heat transfer characteristics. • Use the ensemble Kalman filter to calibrate turbulence model constants. • Realize the perfect integration of experimental and numerical research. • The application of Data Assimilation in engineering is expanded. The heat transfer effect of plate heat exchangers is different due to its various plate structures. To accurately predict the heat transfer characteristics of a plate heat exchanger, this paper makes an important attempt to apply data assimilation technology, namely the data-driven model constant optimization method, to the study of the flow and heat transfer characteristics of a plate heat exchanger. Based on the experimental data, the ensemble Kalman filter algorithm is used to calibrate turbulence model constants and predict the heat transfer performance of a plate heat exchanger. The results show that the data assimilation technology maximizes the value of experimental data, realizes the perfect integration of experimental research and numerical simulation research, and gives full play to the advantages of experimental research and numerical simulation research of plate heat exchangers. At the same time, the reliability of predicting heat transfer characteristics of a plate heat exchanger is improved, the application of data assimilation in engineering is expanded, and the application potential of data assimilation in future turbulence research is highlighted.

Numerical Prediction of Heat Transfer Performance of Plate Heat Exchanger Based on Experimental Data Assimilation to Calibrate Turbulence Model Constants

Numerical Prediction of Heat Transfer Performance of Plate Heat Exchanger Based on Experimental Data Assimilation to Calibrate Turbulence Model Constants

AN INVESTIGATION TURBULENCE MODEL OF STANDARD k- TO GET OPTIMUM PARAMETERS OF TURBULENCE CONSTANTS (cµ, c1, AND c2) OF COMPRESSIBLE FLUID DYNAMICS IN A CONFINED JET

This research aims to find the optimal standard k-e turbulence model constants (cµ, c1e, and c2e) for better predicting compressible fluid dynamics in an air jet ejector. The turbulence field in a jet flow plays an important role in influencing the performance of the momentum transfer process at a shear layer in nozzle application for momentum source and mixing process. In this research, some activities have been done before analyzing and optimizing the turbulence model constants, including preliminary turbulence modeling study for compressible flow in the air-jet ejector, verification, and validation with primary experimental data as well as by other secondary data. The preliminary studies in turbulence modeling presented that the turbulence modeling of a 3mm air jet-ejector resulted in a similar trend of the relation between entrainment ratio and motive fluid pressure. The results showed that the sensitive parameters in the standard k-emodel dissipation and diffusion terms, cµ, c1e, and c2e, strongly affected the optimum value of turbulence kinetic energy (k) and dissipation rate (e), compared to the reference model. Better k and e could be obtained by changing the c2e into positively proportional, but the cµ and c1e must be changed with opposite proportionality. It was found that the optimum standard k-e model constants in the case of air-jet ejector with 3 mm nozzle diameter for cµ, c1e, and c2e are 0.05, 1.48, and 1.88, respectively, with the error values for k being -8.88% and e being -17.44%.

The Effect of Ramp Location in a Strut Based Scramjet Combustor under non reacting flow field

The scramjet engine is considered to be the high-speed propulsive system for hypersonic air-breathing vehicles. Researchers focus on various geometries of strut injectors to enhance the mixing and combustion efficiencies of the scramjet combustor. This paper reveals the non-reacting flow characteristics of various ramp locations in a scramjet combustor with strut injection. The ramps are symmetrically placed at three different locations upstream of the strut within the combustor. Air enters into the combustor inlet with Mach number 2, and the fuel is injected at the sonic velocity from the strut. The 2D supersonic flow characteristics are numerically investigated using ANSYS 18.0 software. The steady-state flow simulations are performed in this study. The flow field is modelled using RANS equations, and the k-ω SST turbulence model and default constants are chosen to investigate the flow characteristics within the combustor. The flow characteristics of the ramp based DLR scramjet combustors are compared with the baseline DLR scramjet model. The computational results are validated with the experimental data. The shock wave interaction from the ramps enhances the distribution of hydrogen in the lateral direction of the flow than the baseline strut configuration. The ramps create recirculation regions that could enhance fuel-air mixing. The ramp induced strut based DLR scramjet engine provides increased total pressure loss of the baseline DLR scramjet.

New consideration of lateral boundary treatment for meso- and micro-scale nested PBL simulations over complex terrain

A detailed planetary boundary layer (PBL) flow over complex terrain can be simulated by nesting mesoscale numerical weather prediction (NWP) models and microscale computational fluid dynamics (CFD). When fully prescribed lateral boundaries are encountered, the over-specified treatment of CFD or limited-area models may result in ill-posedness and numerical instabilities. Such behaviors are due to inconsistent governing equations, turbulent viscosity models, and underlying surfaces between meso- and micro-scale formulations. In this study, by applying the relaxation treatment in marginal zones of CFD, its wind components are forced toward the externally specified NWP values. The relaxation schemes, deduced from simple advective transport equations, are optimized using genetic algorithms. Their numerical abilities in absorbing wave reflections on shallow-water systems are more efficient than the published approach. Then, key questions concerning the selection of relaxation strength, turbulence model constants, and prognostic variables specified on NWP–CFD nested boundaries are systemically investigated in the neutrally stratified Askervein Hill case. The relaxation scheme from simpler systems also performs effectively in CFD and decreases the adaption distance of wind velocities near over-specified outlet boundaries. A full set approach to obtain well-posed PBL solutions from the microscale domains sustained with inflow boundaries from NWP is proposed and validated.

Appropriate boundary conditions for computational wind engineering: Still an issue after 25 years

The problems associated with creating a Horizontally Homogeneous Atmospheric Boundary Layer (HHABL) model in Computational Wind Engineering (CWE) are discussed. In order to achieve this it is important that ALL the conservation equations are in equilibrium. Previous papers have often focussed more on the turbulence property conservation equations, whereas the most common mistake is in not balancing the streamwise momentum equation. This paper primarily focuses on the required balance between the shear stress and the pressure gradient in a HHABL and the consequential impact on the turbulence profiles. The complex nature of the balance of forces and accelerations in the real atmosphere is discussed and it is shown that the surface layer can be modelled as a planar flow, partially driven by the pressure gradient and partially by the shear stress. It is also noted that in the surface layer, where diffusion of Turbulence Kinetic Energy (TKE) is relatively weak, the TKE profile is strongly related to the shear stress profile. The errors associated with basing inlet conditions on a subset of the conservation equations is investigated by analysing one set of profiles which are derived from the TKE conservation equation in isolation. The use of experimental data as inlet conditions is discussed, particularly in relation to the higher levels of TKE in the atmosphere compared to that suggested by the standard turbulence model constants.

Analysis and Modifications of Turbulence Models for Wind Turbine Wake Simulations in Atmospheric Boundary Layers

Computational fluid dynamics (CFD) simulations of wind turbine wakes are strongly influenced by the choice of the turbulence model used to close the Reynolds-averaged Navier-Stokes (RANS) equations. A wrong choice can lead to incorrect predictions of the velocity field characterizing the wind turbine wake and, consequently, to an incorrect power estimation for wind turbines operating downstream. This study aims to investigate the influence of different turbulence models, namely the k–ε, k–ω, SSTk–ω, and Reynolds stress models (RSM), on the results of CFD wind turbine simulations. Their influence was evaluated by comparing the CFD results with the publicly available experimental measurements of the velocity field and turbulence quantities from the Sexbierum and Nibe wind farms. Consistent turbulence model constants were proposed for atmospheric boundary layer (ABL) and wake flows according to previous literature and appropriate experimental observations, and modifications of the derived turbulence model constants were also investigated in order to improve agreement with experimental data. The results showed that the simulations using the k–ε and k–ω turbulence models consistently overestimated the velocity and turbulence quantities in the wind turbine wakes, whereas the simulations using the shear-stress transport (SST) k–ω and RSMs could accurately match the experimental data. Results also showed that the predictions from the k–ε and k–ω turbulence models could be improved by using the modified set of turbulence coefficients.

타원혼합 이차모멘트 모델을 사용한 난류 자연대류 해석

In this paper a computation of turbulent natural convection in enclosures with the elliptic-blending based differential and algebraic flux models is presented. The primary emphasis of the study is placed on an investigation of accuracy of the treatment of turbulent heat fluxes with the elliptic-blending second-moment closure for the turbulent natural convection flows. The turbulent heat fluxes in this study are treated by the elliptic-blending based algebraic and differential flux models. The previous turbulence model constants are adjusted to produce accurate solutions. The proposed models are applied to the prediction of turbulent natural convections in a 1:5 rectangular cavity and in a square cavity with conducting top and bottom walls, which are commonly used for validation of the turbulence models. The relative performance between the algebraic and differential flux model is examined through comparing with experimental data. It is shown that both the elliptic-blending based models predict well the mean velocity and temperature, thereby the wall shear stress and Nusselt number. It is also shown that the elliptic-blending based algebraic flux model produces solutions which are as accurate as those by the differential flux model.

Comparison of Experimental and RANS-Based Numerical Studies of the Decay of Grid-Generated Turbulence

This paper presents both experimental and numerical studies of the statistical properties of turbulent flows at moderate Reynolds number (Reλ = 100) in the context of grid-generated turbulence. In spite of the popularity of passive grids as turbulence generators, their design relies essentially on empirical laws. Here, we propose to test the ability of simple numerical simulations to capture the large scale properties (root-mean-square (rms) velocity, turbulence decay, pressure drop, etc.) of the turbulence downstream a passive grid. With this purpose, experimental measurements are compared with the three-dimensional (3D) Reynolds-Averaged Navier–Stokes (RANS) equations based turbulence model simulations. To better modeling of energy cascade of turbulence, different turbulence models, mesh resolutions, and turbulence model constants, which are determined in accordance with the experimentally measured corresponding values, are used. Both qualitative and quantitative comparisons are made with the experimental data to further assess the accuracy and capability of present numerical techniques for their use in different aerodynamic applications at moderate Re number.

CFD Modeling of the Atmospheric Boundary Layer in Short Test Section Wind Tunnel

The aim of this paper is to provide a contribution to algorithms for the numerical simulation of the atmospheric boundary layer (ABL) in short test section wind tunnel, with the lowest pressure loss possible, for large Re, similar to the high values observed in nature. Different turbulent models have been examined for their relative suitability for the atmospheric boundary layer airflow with and without the implementation of buoyancy effects with modified turbulence model constants for the atmosphere. Validation of turbulent models through comparison with wind tunnel experiments is essential for practical applications. It has been observed that the k-e model is most suitable tool for generation of an ABL in short-chamber wind tunnel. A comparison has been made with the available experimental data, from literature, and the predicted CFD values are very close to the corresponding experimental measurements. The simulation results show the importance of turbulence model constant (Cµ), the non-uniform velocity and turbulence intensity profiles. Also, the significance of y+ for consistent assessment is confirmed. However, it has been found that the buoyancy force makes significant change in boundary layer thickness without a major impact on computation time.

The characteristics of pressure recovery in an adjustable ejector multi-evaporator refrigeration system

In this paper, Computational Fluid Dynamics (CFD) technique is used to investigate the adaption of adjustable ejector for variable cooling loads and the characteristics of ejector pressure recovery in a multi-evaporator refrigeration system (EMERS) using R134a as the refrigerant. The performance of pressure recovery reflects the performance of the compression energy saving. The developed CFD model is first validated by actual experimental data of an EMERS (ejector-based multi-evaporator refrigeration system). Turbulence model constants are carefully selected in order to minimize the model prediction error. The calibrated model is then solved to find the adaption property of the adjustable ejector and the effects of varying cooling loads on and the pressure recovery ratio. The results indicate that the adjustable ejector using spindle to adjust the throat area of primary nozzle is an efficient solution to control the primary operating pressure in constant for system stability. Pressure recovery ratio is sensitive to the varying of cooling loads and the relationship between them is then presented.

Pressure recovery ratio in a variable cooling loads ejector-based multi-evaporator refrigeration system

In this paper, the Computational Fluid Dynamics (CFD) technique is used to investigate the influences of varying cooling loads on the ejector pressure recovery performance in an ejector-based multi-evaporator refrigeration system (EMERS) using R134a as the refrigerant. The performance of pressure recovery in the EMERS reflects the performance of the compression energy saving. The developed CFD model is first validated by actual experimental data from the EMERS. Turbulence model constants are carefully selected in order to minimize the model prediction error. Over 200 different cases are studied using the model to find the effects of varying cooling loads on pressure recovery ratio. The results indicate that pressure recovery ratio is very sensitive to the varying primary and secondary flow cooling loads. The maximum pressure recovery ratio can reach 60% as the cooling loads vary. It was found that in order to keep the system stable, the primary and secondary cooling loads should be maintained within ±5% and ±10%, respectively, in which case the pressure recovery ratio will have a maximum ratio of 32.8%.

Appropriate boundary conditions for computational wind engineering models revisited

At the first Computational Wind Engineering conference in 1992 “Appropriate boundary conditions for computational wind engineering models using the k–ε turbulence model” were proposed. In this paper it is shown that these conditions can be directly derived by treating the onset flow as a horizontally homogeneous turbulent surface layer, with the flow being driven by a shear stress at the top boundary. This approach is extended to provide the inlet profiles and boundary conditions appropriate for modelling the flow using the standard k–ε, RNG k–ε, Wilcox k–ω and LRR QI turbulence models. Means for their application within the commercial CFD code CFX 12.0 are given. It is shown that within the flow the various turbulence model constants set the effective value of von Kármán's constant, which does vary slightly between models. The discrepancy between the turbulence level set by the standard turbulence model constants and that observed in the atmosphere is discussed. Problems with excessive turbulence generation near the ground and the over-prediction of stagnation pressures are discussed and possible solutions proposed.

PDF calculations of piloted premixed jet flames

A series of piloted premixed jet flames with strong finite-rate chemistry effects is studied using the joint velocity-turbulence frequency-composition PDF method. The numerical accuracy of the calculations is demonstrated, and the calculations are compared to experimental data. It is found that all calculations show good agreement with the measurements of mean and rms mixture fraction fields, while the reaction progress is overpredicted to varying degrees depending on the jet velocity. In the calculations of the flame with the lowest jet velocity, the species and temperature show reasonable agreement with the measurements, with the exception of a small region near the centerline where products and temperature are overpredicted and fuel and oxidizer are underpredicted. In the calculations of the flame with the highest jet velocity, however, the overprediction of products and temperature and underprediction of fuel and oxidizer is far more severe. An extensive set of sensitivity studies on inlet boundary conditions, turbulence model constants, mixing models and constants, radiation treatment, and chemical mechanisms is conducted to show that any parameter variation offers little improvement from the base case. To shed light on these discrepancies, diagnostic calculations are performed in which the chemical reactions are artificially slowed. These diagnostic calculations serve to validate the experimental data and to quantify the amount by which the base case calculations overpredict reaction progress. Improved calculations of this flame are achieved only through artificially slowing down the chemical reaction by a factor of about 10. The mixing model behavior in this combustion regime is identified as a likely cause for the observed discrepancy in reaction progress.

Evaluation of numerical schemes using different simulation methods for the continuous phase modeling of cyclone separators

The steady and unsteady state simulations of Stairmand cyclone separator were carried out to investigate the performance of different interpolation schemes for discretization of pressure gradient and advection terms. The RSM turbulence model was revisited to explore its simulation capability of PVC phenomenon and fluctuating velocity profiles of cyclone separators. The combination of Presto, SO, standard and BFW schemes for discretization of pressure gradient and FOU, power law, SOU, QUICK and MUSCL schemes for discretization of advection terms were studied. The double precision solver of Fluent 6.3.26 and modified RSM turbulence model constants of Jiao et al. (Chem. Eng. Technol. 30 (2007) 15–20) were also verified for simulation of cyclone separators. The predicted mean and fluctuating velocity profiles and pressure drop inside the cyclone separator with steady and unsteady simulations have been compared to experimental results available in literature. The steady state simulation failed to predict velocity profiles and pressure drop inside cyclone separator accurately, whereas the unsteady state simulation predicted velocity profiles, pressure drop and PVC phenomenon close to experimental values. The prediction of fluctuating velocity profile was better than previously reported work in the core region compared to the off core region. The present study revealed that the SOU scheme for discretization of advection terms of momentum, kinetic energy and its dissipation rate equations and the FOU scheme for Reynolds stresses together with the Presto scheme for discretization of pressure gradient with unsteady simulation are the optimum choice for simulation of cyclone separators.

Detailed measurements of a statistically steady Rayleigh–Taylor mixing layer from small to high Atwood numbers

The self-similar evolution to turbulence of a multi-mode miscible Rayleigh–Taylor (RT) mixing layer has been investigated for Atwood numbers 0.03–0.6, using an air–helium gas channel experiment. Two co-flowing gas streams, one containing air (on top) and the other a helium–air mixture (at the bottom), initially flowed parallel to each other at the same velocity separated by a thin splitter plate. The streams met at the end of the splitter plate, with the downstream formation of a buoyancy unstable interface, and thereafter buoyancy-driven mixing. This buoyancy-driven mixing layer experiment permitted long data collection times, short transients and was statistically steady. Several significant designs and operating characteristics of the gas channel experiment are described that enabled the facility to be successfully run forAt~ 0.6. We report, and discuss, statistically converged measurements using digital image analysis and hot-wire anemometry. In particular, two hot-wire techniques were developed for measuring the various turbulence and mixing statistics in this air–helium RT experiment. Data collected and discussed include: mean density profiles, growth rate parameters, various turbulence and mixing statistics, and spectra of velocity, density and mass flux over a wide range of Atwood numbers (0.03 ≤At≤ 0.6). In particular, the measured data at the small Atwood number (0.03–0.04) were used to evaluate several turbulence-model constants. Measurements of the root mean square (r.m.s.) velocity and density fluctuations at the mixing layer centreline for the largeAtcase showed a strong similarity to lowerAtbehaviours when properly normalized. A novel conditional averaging technique provided new statistics for RT mixing layers by separating the bubble (light fluid) and spike (heavy fluid) dynamics. The conditional sampling highlighted differences in the vertical turbulent mass flux, and vertical velocity fluctuations, for the bubbles and spikes, which were not otherwise observable. Larger values of the vertical turbulent mass flux and vertical velocity fluctuations were found in the downward-falling spikes, consistent with larger growth rates and momentum of spikes compared with the bubbles.

Comparison of FDS predictions by different combustion models with measured data for enclosure fires

The performance of mixture fraction models FDS4 and FDS5 is investigated under different global equivalence ratios (GER). Predictions of heat release rate (HRR), upper-layer temperature, and CO yield are compared with measurements considering their sensitivities to the lower limit of fuel, mixing time scale, and turbulence model constants. When using FDS4, the inclusion of an extinction model can result in significant variations in both total and volumetric HRR prediction. When using FDS5, the mixing model constant has significant effects on volumetric HRR prediction. At low GER (<0.23), the prediction of upper-layer temperature shows dependency on both the lower fuel limit and the mixing model constant, but the predicted temperature is always lower than measured temperature, with deviations in excess of 30%. At higher GER (0.53<GER<0.81), the upper-layer temperature prediction shows significant dependency on the mixing model constant but can be over-predicted, with deviations up to 24%. The variations of CO yield prediction with lower fuel limit or with the mixing model constant show an opposite trend to that of upper-layer temperature. Furthermore, the prediction of CO yield shows a much greater dependency on the Smagorinsky constant and on the turbulent Schmidt number than do those of HRR and upper-layer temperature.