REVISED k-ε TURBULENCE MODEL IN ELECTROMAGNETIC CONTINUOUS CASTING OF MELT

The research is motivated by the ongoing the electromagnetic continuous casting of molten metal. The revised k-ε model considering the effect of magnetic field application was derived. The specific model equations for the electromagnetic braking were used to calculate the velocity distribution in the continuous casting mold of steel. The results show that the revised k-ε model considering the effect of magnetic field application tends to suppress the production of turbulence and difference between the conventional and revised k-e model is small.

Numerical prediction of inner turbulent flow in conical diffuser by using a new five-point scheme and DLR k-ε turbulence model

The internal turbulent flow in conical diffuser is a very complicated adverse pressure gradient flow.DLR k-ε turbulence model was adopted to study it.The every terms of the Laplace operator in DLR k-ε turbulence model and pressure Poisson equation were discretized by upwind difference scheme.A new full implicit difference scheme of 5-point was constructed by using finite volume method and finite difference method.A large sparse matrix with five diagonals was formed and was stored by three arrays of one dimension in a compressed mode.General iterative methods do not work wel1 with large sparse matrix.With algebraic multigrid method(AMG),linear algebraic system of equations was solved and the precision was set at 10-6.The computation results were compared with the experimental results.The results show that the computation results have a good agreement with the experiment data.The precision of computational results and numerical simulation efficiency are greatly improved.

A sub-grid scale model for Burgers turbulence based on the artificial neural network method

The present study proposes a sub-grid scale model for the one-dimensional Burgers turbulence based on the neuralnetwork and deep learning method.The filtered data of the direct numerical simulation is used to establish thetraining data set,the validation data set,and the test data set.The artificial neural network(ANN)methodand Back Propagation method are employed to train parameters in the ANN.The developed ANN is applied toconstruct the sub-grid scale model for the large eddy simulation of the Burgers turbulence in the one-dimensionalspace.The proposed model well predicts the time correlation and the space correlation of the Burgers turbulence.

TWO MODIFICATORY K-ε TURBULENCE MODELS FOR TURBULENT SWIRLING FLOWS

Since the standard K-ε model used to predict the strongly swirling flowleads to a large deviation from experimental results, it is necessary to introduce modification tothe standard K-ε model. Based on the algebraic Reynolds stress model and Bradshaw's turbulentlength scale modification conception, we present two modified K-ε models. To investigate thebehaviour of the modified turbulence models, they are used to predict two representative turbulentswirling flows. The computational results, after compared with the experimental data, show that themodified K-ε models substantially improve the prediction of the standard K-ε model for theturbulent swirling flows.

A k-ε Turbulence Model Considering Compressibility in Three-Dimensional Transonic Turbulent Flow Calculation

Based on the standard k-ε turbulence model, a new compressible k-ε model considering the pressure expansion influence due to the compressibility of fluid is developed and applied to the simulation of 3D transonic turbulent flows in a nozzle and a cascade. The Reynolds avenged N-S equations in generalized curvilinear coordinates are solved with implementation of the new model. The high resolution TVD scheme is used to discretize the convective terms. The numerical results show that the compressible k-ε model behaves well in the simulation of transonic internal turbulent flows.

Artificial neural network-based one-equation model for simulation of laminar-turbulent transitional flow

A mapping function between the Reynolds-averaged Navier-Stokes mean flow variables and transition intermittency factor is constructed by fully connected artificial neural network(ANN),which replaces the governing equation of the intermittency factor in transition-predictive Spalart-Allmaras(SA)-γmodel.By taking SA-γmodel as the benchmark,the present ANN model is trained at two airfoils with various angles of attack,Mach numbers and Reynolds numbers,and tested with unseen airfoils in different flow states.The a posteriori tests manifest that the mean pressure coefficient,skin friction coefficient,size of laminar separation bubble,mean streamwise velocity,Reynolds shear stress and lift/drag/moment coefficient from the present two-way coupling ANN model almost coincide with those from the benchmark SA-γmodel.Furthermore,the ANN model proves to exhibit a higher calculation efficiency and better convergence quality than traditional SA-γmodel.

Stochastic Analysis and Modeling of Velocity Observations in Turbulent Flows

Highly turbulent water flows,often encountered near human constructions like bridge piers,spillways,and weirs,display intricate dynamics characterized by the formation of eddies and vortices.These formations,varying in sizes and lifespans,significantly influence the distribution of fluid velocities within the flow.Subsequently,the rapid velocity fluctuations in highly turbulent flows lead to elevated shear and normal stress levels.For this reason,to meticulously study these dynamics,more often than not,physical modeling is employed for studying the impact of turbulent flows on the stability and longevity of nearby structures.Despite the effectiveness of physical modeling,various monitoring challenges arise,including flow disruption,the necessity for concurrent gauging at multiple locations,and the duration of measurements.Addressing these challenges,image velocimetry emerges as an ideal method in fluid mechanics,particularly for studying turbulent flows.To account for measurement duration,a probabilistic approach utilizing a probability density function(PDF)is suggested to mitigate uncertainty in estimated average and maximum values.However,it becomes evident that deriving the PDF is not straightforward for all turbulence-induced stresses.In response,this study proposes a novel approach by combining image velocimetry with a stochastic model to provide a generic yet accurate description of flow dynamics in such applications.This integration enables an approach based on the probability of failure,facilitating a more comprehensive analysis of turbulent flows.Such an approach is essential for estimating both short-and long-term stresses on hydraulic constructions under assessment.

Artificial neural network-based subgrid-scale models for LES of compressible turbulent channel flow

Fully connected neural networks(FCNNs)have been developed for the closure of subgrid-scale(SGS)stress and SGS heat flux in large-eddy simulations of compressible turbulent channel flow.The FCNNbased SGS model trained using data with Mach number Ma=3.0 and Reynolds number Re=3000 was applied to situations with different Mach numbers and Reynolds numbers.The input variables of the neural network model were the filtered velocity gradients and temperature gradients at a single spatial grid point.The a priori test showed that the FCNN model had a correlation coefficient larger than 0.91 and a relative error smaller than 0.43,with much better reconstructions of SGS unclosed terms than the dynamic Smagorinsky model(DSM).In a posteriori test,the behavior of the FCNN model was marginally better than that of the DSM in predicting the mean velocity profiles,mean temperature profiles,turbulent intensities,total Reynolds stress,total Reynolds heat flux,and mean SGS flux of kinetic energy,and outperformed the Smagorinsky model.

Numerical simulation of gas–liquid flow in the bubble column using Wray–Agarwal turbulence model coupled with population balance model

In this paper,an improved computational fluid dynamic(CFD)model for gas-liquid flow in bubble column was developed using the one-equation Wary-Agarwal(WA)turbulence model coupled with the population balance model(PBM).Through 18 orthogonal test cases,the optimal combination of interfacial force models,including drag force,lift force,turbulent dispersion force.The modified wall lubrication force model was proposed to improve the predictive ability for hydrodynamic behavior near the wall of the bubble column.The values simulated by optimized CFD model were in agreement with experimental data,and the errors were within±20%.In addition,the axial velocity,turbulent kinetic energy,bubble size distribution,and the dynamic characteristic of bubble plume were analyzed at different superficial gas velocities.This research work could provide a theoretical basis for the extension of the CFD-PBM coupled model to other multiphase reactors..

Simulation Analysis of New Energy Vehicle Engine Cooling System Based on K-E Turbulent Flow Mathematical Model

New energy vehicles have better clean and environmental protection characteristics than traditional fuel vehicles.The new energy engine cooling technology is critical in the design of new energy vehicles.This paper used oneand three-way joint simulation methods to simulate the refrigeration system of new energy vehicles.Firstly,a k-εturbulent flow model for the cooling pump flow field is established based on the principle of computational fluid dynamics.Then,the CFD commercial fluid analysis software FLUENT is used to simulate the flow field of the cooling pump under different inlet flow conditions.This paper proposes an optimization scheme for new energy vehicle engines’“boiling”phenomenon under high temperatures and long-time climbing conditions.The simulation results show that changing the radiator’s structure and adjusting the thermostat’s parameters can solve the problem of a“boiling pot.”The optimized new energy vehicle engine can maintain a better operating temperature range.The algorithm model can reference each cryogenic system component hardware selection and control strategy in the new energy vehicle’s engine.

Calculation of tip vortex cavitation flows around three-dimensional hydrofoils and propellers using a nonlinear k-ε turbulence model

Simulations of tip vortex wetted flows and cavitating flows are carried out by using a RANS model. Two types of turbule- nce models, with and without the Boussinesq turbulent-viscosity hypothesis, are adopted in comparing with experimental results regarding the vorticity, the strain rate and the Reynolds shear stress distributions in the vortex region. The numerical results imply that the spatial phase shift between the mean strain rate and the Reynolds stresses can be accurately modeled by the nonlinear κ-ε turbulence model, the tip vortex cavitation region can only be predicted using the nonlinear κ-ε turbulence model. The mecha- nism of the over-dissipation due to the turbulence model is analyzed in terms of the turbulence production, which is one of the dominant source terms in the transport equations of energy.

Numerical application of k-ε turbulence model to the flow over a backward-facing step

A model that uses the operator splitting technique based on Eulerian-Lagrangian method and embeds the k-ε turbulence mode is developed. The model is used to simulate a two dimensional flow over a backward-facing step with triangular mesh discrete flow field. The convection operator is solved with the characteristic method and the diffusion operator and pressure-Poisson equation are solved by finite element method. The results from the example showed that numerical results are well agreed with the experimental data,and that the method can be adapted to simulate complex turbulent flow with strong non-linear convection. The treatment of boundary conditions is also studied in the paper.

APPLICATION OF A MODIFIED QUICK SCHEME TO DEPTH-AVERAGED k-ε TURBULENCE MODEL BASED ON UNSTRUCTURED GRIDS

The modified QUICK scheme on unstructured grid was used to improve the advection flux approximation, and the depth-averaged κ-ε turbulence model with the scheme based on FVM by SIMPLE series algorithm was established and applied to spur-dike flow computation. In this model, the over-relaxed approach was adopted to estimate the diffusion flux in view of its advantages in reducing errors and sustaining numerical stability usually encountered in non-orthogonal meshes. Two spur-dike cases with different defection angles （90°and 135°） were analyzed to validate the model. Computed results show that the predicted velocities and recirculation lengths are in good agreement with the observed data. Moreover, the computations on structured and unstructured grids were compared in terms of the approximately equivalent grid numbers. It can be concluded that the precision with unstructured grids is higher than that with structured grids in spite that the CPU time required is slightly more with unstructured grids Thus, it is significant to apply the method to numerical simulation of practical hydraulic engineering.

THREE-DIMENSIONAL SIMULATION OF MEANDERING RIVER BASED ON 3-D RNG k-ε TURBULENCE MODEL

A 3-D numerical model for calculating flow in non-curvilinear coordinates was established in this article. The flow was simulated by solving the full Reynolds-averaged Navier-Stokes equations with the RNG κ-ε turbulence model. In the horizontal x-y-plane, a boundary-fitted curvilinear co-ordinate system was adopted, while in the vertical direction, a σ co-ordinate transformation was used to represent the free surface and bed topography. The water level was determined by solving the 2-D Poisson equation derived from 2-D depth averaged momentum equations. The finite-volume method was used to discretize the equations and the SIMPLEC algorithm was applied to acquire the coupling of velocity and pressure. This model was applied to simulate the meandering channels and natural rivers, and the water levels and the velocities for all sections were given. By contrasting and analyzing, the agreement with measurements is generally good. The feasibility studies of simulating flow of the natural fiver have been conducted to demonstrate its applicability to hydraulic engineering research.

Development of the modified k-ε turbulence model of power-law fluid for engineering applications

In the present study, a high Reynolds number version of a turbulence model was proposed by using drag reduction to analyze the turbulent flows of power-law fluid for engineering applications. In order to determine the model constants in the constitutive equation, numerical simulation was conducted under the same conditions that were applied to obtain the experiment re- suits and previous turbulence models. For validation of the modified turbulence model, numerical simulations were performed for power-law fluids of different viscosities. The results of the modified k-ε turbulence model showed better agreement with the experimental results than those of the standard k-ε turbulence model. In addition, computation time and computer resource of the modified k-ε turbulence model were reduced by about one third as compared to the low Reynolds number model for power-law fluids.

Numerical Evaluation of Two k-εTurbulence Model for Predicting Flow and Solidification in Continuous Casting Slab

A steady three-dimensional fluid flow and solidification model was built based on CFD software by high-Reynolds-number and Lam-Bremhorst low-Reynolds-number k-ε model.During the simulation,the fixed-grid enthalpy-porosity technique was used to represent the solidification,and Darcy law was adopted to simulate the flow in mushy region.The prediction for steel flow and solidification was evaluated by the comparison of two turbulence models.It is found that both Lam-Bremhorst low-Reynolds-number and high-Reynolds-number k-ε models predict the same trend of the steel flow and temperature distribution.However,due to the effect of turbulent flow on heat transfer,the low-Reynolds-number turbulence model predicts longer penetration depth of molten steel in sub-mold region,less shell growth and higher shell surface temperature at the narrow face compared with standard k-ε model.

SIMULATION OF 3-D FLOW AROUND A VAN-BODY TRUCK WITH RNG K-ε TURBULENCE MODEL

It is proved that the calculation precision of the outside flow field of the van-body truck using PNG k-Ε turbulence model is higher than that using standard k-Ε turbulence model by means of experiments. The calculation results of the outside flow field of a certain domestic van-body truck are given. And by analyzing and comparing the different tail flow plots, the tail flow structural characteristics and the relationship between the position and the intensity of the tail vortex and the aerodynamic drag is obtained, which can direct the design of the outside aerodynamic shape of the van-body truck.

A K-εTWO-EQUATION TURBULENCE MODEL FOR THE SOLID-LIQUID TWO-PHASE FLOWS

A two-equation turbulence model has been dereloped for predicting two-phase flow the two equations describe the conserration of turbulence kinetic energy and dissipation rate of that energy for the incompressible carrier fluid in a two-phase flow The continuity, the momentum, K and εequations are modeled. In this model,the solid-liquid slip veloeites, the particle-particte interactions and the interactions between two phases are considered,The sandy water pipe turbulent flows are sueeessfuly predicted by this turbulince model.

A new compressibility modification k-ε turbulence model with shock unsteadiness effect

A new compressibility modification k-ε model,including shock unsteadiness effect and the previous compressibility modification of pressure dilatation and dilatational dissipation rate,was developed with a simple formulation for numerical simulation in supersonic complex turbulent flows.The shock unsteadiness effect was modeled by inhibiting turbulent kinetic energy production in the governing equations of turbulent kinetic energy and the turbulent kinetic energy dissipation rate.Sarkar's correction models were employed accounting for the dilatational compressibility effects in the new model.Two types of flows,the free supersonic mixing layers and complex supersonic flow with transverse injection were simulated with different flow conditions.Comparisons with experimental data of the free supersonic mixing layers showed that the new compressibility modification k-ε model significantly inhibited the excessive growth of turbulent kinetic energy and improved predictions.On the supersonic mixing layer flows,prediction results with the new model were in close agreement with experimental data,accurately predicting the decreasing trend of the mixing layer spreading rate with the increase of the convective Mach number.Due to the complicated flow field with flow separation,shock unsteadiness modification inhibited excessive growth of the turbulent kinetic energy in shock regions and wider shock regions are predicted,thereby significantly improving results of the flow with a strong separation forecast.The flow separation was stronger,which was the primary modification effect of the new model.Predictions accord with experimental results even in strong separation flows.

An assessment of k-εturbulence models for gas distribution analysis

This paper presents the gas distribution analysis by injecting air fountain into the containment and simulations with the HYDRAGON code. Turbulence models of standard k-ε(SKE), re-normalization group k-ε(RNG) and a realizable k-ε(RLZ) are used to assess the effects on the gas distribution analysis during a severe accident in a nuclear power plant. By comparing with experimental data,the simulation results of the RNG and SKE turbulence models agree well with the experimental data on the prediction of dimensionless density distributions. The results illustrate that the turbulence model choice had a small effect on the simulation results, particularly the region near to the air fountain source.