Numerical Predictions and Experiment Results for a 1m Diameter Methane Fire

2005 ◽  
Author(s):  
Amalia R. Black
Keyword(s):  
Experimental Data ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulence Model ◽  
Vertical Velocity ◽  
Grid Size ◽  
Closure Models ◽  
Filter Width ◽  
Numerical Predictions ◽  
Temporal Filter

Comparisons between numerical predictions and experimental data for a methane fire have been performed. Vertical velocity and turbulent kinetic energy measurements along the centerline of the fire were used to validate the models in the SIERRA/Fuego fire code. Two different turbulence treatments, a steady RANS solution with a model for buoyancy generated turbulence, and an unsteady solution with closure models based on a temporal filter width were used. Solution sensitivity to grid size has been examined for both approaches. The results indicate strong sensitivities to the turbulence model.

Heat Transfer Predictions With Extended k–ε Turbulence Model in Radial Cooling Ducts Rotating in Orthogonal Mode

1994 ◽  
Vol 116 (2) ◽  
pp. 369-380 ◽  
Author(s):  
P. Tekriwal
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulence Model ◽  
Rotation Number ◽  
Density Ratio ◽  
Rotating Systems ◽  
Model Predictions ◽  
Number Flow

Standard and extended k–ε turbulence closure models have been employed for three-dimensional heat transfer calculations for radially outward flow in rectangular and square cooling passages rotating in orthogonal mode. The objective of this modeling effort is to validate the numerical model in an attempt to fill the gap between model predictions and the experimental data for heat transfer in rotating systems. While the trend of heat transfer predictions by the standard k–ε turbulence model is satisfactory, the differences between the data and the predictions are approximately 30 percent or so in the case of high rotation number flow. The extended k–ε turbulence model takes an approach where an extra “source” term based on a second time scale of the turbulent kinetic energy production rate is added to the equation for the dissipation rate of turbulent kinetic energy. This yields a more effective calculation of turbulent kinetic energy as compared to the standard k–ε turbulence model in the case of high rotation number and high density ratio flow. As a result, comparison with the experimental data available in the literature shows that an improvement of up to a significant 15 percent (with respect to data) in the heat transfer coefficient predictions is achieved over the standard k–ε model in the case of high rotation number flow. Comparisons between the results of the standard k–ε model and the extended formulation are made at different rotation numbers, different Reynolds numbers, and varying temperature ratio. The results of the extended k–ε turbulence model are either as good or better than those of the standard k–ε model in all these cases of parametric study. Thus, the extended k–ε turbulence model proves to be more general and reduces the discrepancy between the model predictions and the experimental data for heat transfer in rotating systems.

scholarly journals Estimating turbulent kinetic energy and dissipation with internal flow loss coefficients

2018 ◽  
Author(s):  
Ben Trettel
Keyword(s):  
Fluid Dynamics ◽  
Experimental Data ◽  
Computational Fluid Dynamics ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulence Model ◽  
Internal Flow ◽  
Jet Breakup ◽  
Loss Coefficients ◽  
Improved Model

Estimating the turbulent kinetic energy at the nozzle outlet is necessary to model turbulent jet breakup. We identified errors in a model of nozzle turbulence developed by Huh et al. which made the model inaccurate. To develop an improved model, we derived a generalized form of the Bernoulli equation for non-cavitating flows. The equation can be used to estimate turbulent kinetic energy, k, and dissipation, ε, in internal flows given loss coefficients or friction factors and a turbulence model. The equation allows turbulent kinetic energy and dissipation to be estimated without computational fluid dynamics. The estimates can be used as-is where turbulent kinetic energy or dissipation are desired, or as a more accurate boundary condition for computational fluid dynamics. A model for fully developed pipe flow is developed and compared against experimental data. A nozzle turbulence model which could replace Huh et al.'s is also developed, but the model has not been validated due to a lack of experimental data.

Swirling, Particle-Laden Flows Through a Pipe Expansion

1992 ◽  
Vol 114 (4) ◽  
pp. 648-656 ◽  
Author(s):  
M. Sommerfeld ◽  
A. Ando ◽  
D. Wennerberg
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Gas Phase ◽  
Turbulence Model ◽  
Stokes Equations ◽  
Swirling Flow ◽  
Particle Dispersion ◽  
Recirculation Bubble ◽  
Numerical Predictions ◽  
Pipe Expansion

The present study concerns a particle-laden, swirling flow through a pipe expansion. A gas-particle flow enters the test section through a center tube, and a swirling air stream enters through a coaxial annulus. The swirl number based on the total inflow is 0.47. Numerical predictions of the gas flow were performed using a finite-volume approach for solving the time-averaged Navier-Stokes equations. The predicted mean velocity profiles showed good agreement with experimental results when using the standard k-ε turbulence model. The turbulent kinetic energy of the gas phase, however, is considerably underpredicted by this turbulence model, especially in the initial mixing region of the two jets. The particle dispersion characteristics in this complex flow were studied by using the Lagrangian method for particle tracking and considering the particle size distribution. The influence of the particle phase onto the fluid flow was neglected in the present stage, since only low particle loadings were considered. The particle mean velocities were again predicted reasonably well and differences between experiment and simulation were only found in the velocity fluctuations, which is partly the result of the underpredicted turbulent kinetic energy of the gas phase. The most sensitive parameter for validating the quality of numerical simulations for particle dispersion is the development of the particle mean number diameter which showed reasonable agreement with the experiments, except for the core region of the central recirculation bubble. This, however, is attributed again to the predicted low turbulent kinetic energy of the gas phase.

scholarly journals Development of a two zone turbulence model and its application to the cycle-simulation

2014 ◽  
Vol 18 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Momir Sjeric ◽  
Darko Kozarac ◽  
Rudolf Tomic
Keyword(s):  
High Pressure ◽  
Kinetic Energy ◽  
Flow Field ◽  
Turbulent Kinetic Energy ◽  
Turbulence Model ◽  
Combustion Process ◽  
Progress Variable ◽  
Cycle Simulation ◽  
Pressure Cycle ◽  
Turbulent Flow Field

The development of a two zone k-? turbulence model for the cycle-simulation software is presented. The in-cylinder turbulent flow field of internal combustion engines plays the most important role in the combustion process. Turbulence has a strong influence on the combustion process because the convective deformation of the flame front as well as the additional transfer of the momentum, heat and mass can occur. The development and use of numerical simulation models are prompted by the high experimental costs, lack of measurement equipment and increase in computer power. In the cycle-simulation codes, multi zone models are often used for rapid and robust evaluation of key engine parameters. The extension of the single zone turbulence model to the two zone model is presented and described. Turbulence analysis was focused only on the high pressure cycle according to the assumption of the homogeneous and isotropic turbulent flow field. Specific modifications of differential equation derivatives were made in both cases (single and two zone). Validation was performed on two engine geometries for different engine speeds and loads. Results of the cyclesimulation model for the turbulent kinetic energy and the combustion progress variable are compared with the results of 3D-CFD simulations. Very good agreement between the turbulent kinetic energy during the high pressure cycle and the combustion progress variable was obtained. The two zone k-? turbulence model showed a further progress in terms of prediction of the combustion process by using only the turbulent quantities of the unburned zone.

scholarly journals Discussion on improved method of turbulence model for supercritical water flow and heat transfer

2020 ◽  
Vol 24 (5 Part A) ◽  
pp. 2729-2741
Author(s):  
Zhenchuan Wang ◽  
Guoli Qi ◽  
Meijun Li
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulence Model ◽  
Buoyancy Effect ◽  
Improved Method ◽  
Production Term ◽  
Flow And Heat Transfer ◽  
Effect Model

The turbulence model fails in supercritical fluid-flow and heat transfer simulation, owing to the drastic change of thermal properties. The inappropriate buoyancy effect model and the improper turbulent Prandtl number model are several of these factors lead to the original low-Reynolds number turbulence model unable to predict the wall temperature for vertically heated tubes under the deteriorate heat transfer conditions. This paper proposed a simplified improved method to modify the turbulence model, using the generalized gradient diffusion hypothesis approximation model for the production term of the turbulent kinetic energy due to the buoyancy effect, using a turbulence Prandtl number model for the turbulent thermal diffusivity instead of the constant number. A better agreement was accomplished by the improved turbulence model compared with the experimental data. The main reason for the over-predicted wall temperature by the original turbulence model is the misuse of the buoyancy effect model. In the improved model, the production term of the turbulent kinetic energy is much higher than the results calculated by the original turbulence model, especially in the boundary-layer. A more accurate model for the production term of the turbulent kinetic energy is the main direction of further modification for the low Reynolds number turbulence model.

Coherent Velocity Structures in the Mixed Layer: Characteristics, Energetics, and Turbulent Kinetic Energy Budget

2021 ◽  
Author(s):  
Ewa Jarosz ◽  
Hemantha W. Wijesekera ◽  
David W. Wang
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Mixed Layer ◽  
Vertical Velocity ◽  
Mixed Layer Depth ◽  
Vertical Transport ◽  
Rate Of Change ◽  
Production Term ◽  
Forcing Mechanisms ◽  
Surface Buoyancy

AbstractVelocity, hydrographic, and microstructure observations collected under moderate to high winds, large surface waves, and significant ocean-surface heat losses were utilized to examine coherent velocity structures (CVS) and turbulent kinetic energy (TKE) budget in the mixed layer on the outer shelf in the northern Gulf of Mexico in February 2017. The CVS exhibited larger downward velocities in downweling regions and weaker upward velocities in broader upwelling regions, elevated vertical velocity variance, vertical velocity maxima in the upper part of the mixed layer, and phasing of crosswind velocities relative to vertical velocities near the base of the mixed layer. Temporal scales ranged from 10 min to 40 min and estimated lateral scales ranged from 90 m to 430 m, which were 1.5 – 6 times larger than the mixed layer depth. Nondimensional parameters, Langmuir and Hoenikker numbers, indicated that plausible forcing mechanisms were surface-wave driven Langmuir vortex and destabilizing surface buoyancy flux. The rate of change of TKE, shear production, Stokes production, buoyancy production, vertical transport of TKE, and dissipation in the TKE budget were evaluated. The shear and Stokes productions, dissipation, and vertical transport of TKE were the dominant terms. The buoyancy production term was important at the sea surface, but it decreased rapidly in the interior. A large imbalance term was found under the unstable, high wind, and high-sea state conditions. The cause of this imbalance cannot be determined with certainty through analyses of the available observations; however, our speculation is that the pressure transport is significant under these conditions.

Large Eddy Simulation of Cylindrical Jet Breakup and Correlation of Simulation Results With Experimental Data

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
Shashank S. Moghe ◽  
Scott M. Janowiak
Keyword(s):  
Experimental Data ◽  
Kinetic Energy ◽  
Large Eddy Simulation ◽  
Turbulent Kinetic Energy ◽  
Experimental Results ◽  
Eddy Simulation ◽  
Jet Breakup ◽  
Large Eddy ◽  
Oil Jet ◽  
Piston Cooling

Modern engines with increasing power densities have put additional demands on pistons to perform in incrementally challenging thermal environments. Piston cooling is therefore of paramount importance for engine component manufacturers. The objective of this computational fluid dynamics (CFD) study is to identify the effect of a given piston cooling nozzle (PCN) geometry on the cooling oil jet spreading phenomenon. The scope of this study is to develop a numerical setup using the open-source CFD toolkit OpenFoam® for measuring the magnitude of oil jet spreading and comparing it to experimental results. Large eddy simulation (LES) turbulence modeling is used to capture the flow physics that affects the inherently unsteady jet breakup phenomenon. The oil jet spreading width is the primary metric used for comparing the numerical and experimental results. The results of simulation are validated for the correct applicability of LES by evaluating the fraction of resolved turbulent kinetic energy (TKE) at various probe locations and also by performing turbulent kinetic energy spectral analysis. CFD results appear promising since they correspond to the experimental data within a tolerance (of ±10%) deemed satisfactory for the purpose of this study. Further generalization of the setup is underway toward developing a tool that predicts the aforementioned metric—thereby evaluating the effect of PCN geometry on oil jet spreading and hence on the oil catching efficiency (CE) of the piston cooling gallery. This tool would act as an intermediate step in boundary condition formulation for the simulation determining the filling ratio (FR) and subsequently the heat transfer coefficients (HTCs) in the piston cooling gallery.

Statistical Modeling of Stratified Two-Phase Flow

2017 ◽  
Vol 3 (2) ◽  
Author(s):  
M. Benz ◽  
T. Schulenberg
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulence Model ◽  
Input Parameter ◽  
Wave Number ◽  
Energy Potential ◽  
Two Phase ◽  
Turbulent Length Scale ◽  
Inner Region ◽  
Velocity Turbulence

A new numerical model for stratified two-phase flows with wavy interface is derived in this study. Assuming an equilibrium condition between turbulent kinetic energy, potential energy, and surface energy, the turbulent length scale in the inner region of a two-layer turbulence approach can be described by a statistical model to account for the influence of the waves. The average wave number, which is an input parameter to this model, is taken from wave spectra. They can be predicted from a Boltzmann statistic of turbulent kinetic energy. The new turbulence model is compared with the two-phase k–ϵ turbulence model. Time-averaged flow properties calculated by the new approach, such as velocity, turbulence, and void profiles, are shown to be in good agreement with experimental data.

Assessment Measures for LES Applications

2006 ◽  
Author(s):  
I. Celik ◽  
M. Klein ◽  
J. Janicka
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Power Spectra ◽  
Grid Size ◽  
Large Eddy Simulations ◽  
Large Eddy ◽  
Modeling Errors ◽  
The Common ◽  
Assessment Measures ◽  
Molecular Viscosity

Anticipating that Large Eddy Simulations will increasingly become the future engineering tool for research, development and design, it is deemed necessary to formulate some quality assessment measures that can be used to judge the resolution of turbulent scales and the accuracy of predictions. In this context some new and refined measures are proposed above and beyond those already published by the authors in the common literature. These new measures involve (a) fraction of total turbulent kinetic energy, (b) relative grid size with respect to Kolmogorov or Taylor scales, (c) relative effective sub-grid/numerical viscosity with respect to molecular viscosity, and (d) some property related to power spectra of turbulent kinetic energy. In addition, an attempt is made to segregate the contributions from numerical and modeling errors. Proposed measures are applied to various benchmark cases, and validated against fully resolved LES and/or DNS whenever possible. Along the same line of thinking, the authors present a perspective for verification of under-resolved direct numerical simulations.

Sign in / Sign up

Export Citation Format

Share Document