Large Eddy Simulation of SGS Turbulent Kinetic Energy and SGS Turbulent Dissipation in a Backward-Facing Step Turbulent Flow

2004 ◽  
Vol 21 (9) ◽  
pp. 1773-1776 ◽  
Author(s):  
Wang Bing ◽  
Zhang Hui-Qiang ◽  
Wang Xi-Lin
Keyword(s):  
Kinetic Energy ◽  
Large Eddy Simulation ◽  
Turbulent Flow ◽  
Turbulent Kinetic Energy ◽  
Backward Facing Step ◽  
Turbulent Dissipation ◽  
Eddy Simulation ◽  
Large Eddy

Large Eddy Simulation of Francis Turbine Flow Fields under Small Opening Condition

2013 ◽  
Vol 444-445 ◽  
pp. 281-285 ◽  
Author(s):  
Tao Guo ◽  
Jun Zhou ◽  
Xiao Nan Liu
Keyword(s):  
Kinetic Energy ◽  
Large Eddy Simulation ◽  
Turbulent Kinetic Energy ◽  
Guide Vane ◽  
Francis Turbine ◽  
Scale Model ◽  
Unstable Flow ◽  
Small Opening ◽  
Eddy Simulation ◽  
Large Eddy

The vibration intensity is strong in Francis turbine occurred under the small opening conditions, such as Lijia Gorges and Three Gorges project. In paper we use large eddy simulation (LES) method base on Vreman SubGrid-Scale model to study the generation and evolution process of turbulence flow, capturing the details of the flow structures and the dissipation of the turbulent kinetic energy. The SIMPIEC algorithm is applied to solve the coupled equation of velocity and pressure. The result shows that the small guide vane opening conditions deviate the optimal conditions most. So some unstable flow characters been induced. Such as the turbulent kinetic energy of fluid in guide vanes zone, the blade passage and the draft tube are very strong. The unstable flow phenomenon including the swirl, flow separation, interruption and vortex strip. It can be deduced that the vibration of unit is induced by these flow characteristic.

Large-eddy simulation of the Richtmyer–Meshkov instability

2015 ◽  
Vol 93 (10) ◽  
pp. 1124-1130 ◽  
Author(s):  
T. Wang ◽  
P. Li ◽  
J.S. Bai ◽  
G. Tao ◽  
B. Wang ◽  
...  
Keyword(s):  
Kinetic Energy ◽  
Flow Field ◽  
Large Eddy Simulation ◽  
Turbulent Kinetic Energy ◽  
Interface Instability ◽  
Simulation Code ◽  
Interface Evolution ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Turbulence Mixing

The subgrid-scale (SGS) terms of turbulence transport are modelled by the stretched-vortex SGS stress model, and a large-eddy simulation code multi-viscous fluid and turbulence (MVFT) is developed to investigate the MVFT problems. Then one AWE shock tube experiment of interface instability is simulated numerically by MVFT code, which reproduces the development process of the interface. The obtained numerical images of interface evolution and wave structures in flow field are consistent with the experimental results. The evolution of perturbed interface and propagation of shock waves in flow field and their interactions are analyzed in detail. The statistics features of turbulence mixing in the form of finer quantities, such as the turbulent kinetic energy, enstrophy, density variance, and turbulent mass flux are investigated, which also proves that the SGS model has a key role in large-eddy simulation. The turbulent kinetic energy and enstrophy decay with time as a power law.

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.

Large Eddy Simulation of a Turbulent Non-Reacting Spray Jet

2015 ◽  
Author(s):  
B. Hu ◽  
S. Banerjee ◽  
K. Liu ◽  
D. Rajamohan ◽  
J. M. Deur ◽  
...  
Keyword(s):  
Kinetic Energy ◽  
Large Eddy Simulation ◽  
Turbulent Kinetic Energy ◽  
Cell Size ◽  
Adaptive Mesh Refinement ◽  
Large Scale ◽  
Flow Behavior ◽  
Similarity Index ◽  
Eddy Simulation ◽  
Large Eddy

We performed Large Eddy Simulation (LES) of a turbulent non-reacting n-Heptane spray jet, referred to as Spray H in the Engine Combustion Network (ECN), and executed a data analysis focused on key LES metrics such as fraction of resolved turbulent kinetic energy and similarity index. In the simulation, we used the dynamic structure model for the sub-grid stress, and the Lagrangian-based spray-parcel models coupled with the blob-injection model. The finest mesh-cell size used was characterized by an Adaptive Mesh Refinement (AMR) cell size of 0.0625 mm. To obtain ensemble statistics, we performed 28 numerical realizations of the simulation. Demonstrated by the comparison with experimental data in a previous study [7], this LES has accurately predicted global quantities, such as liquid and vapor penetrations. The analysis in this work shows that 14 realizations of LES are sufficient to provide a reasonable representation of the average flow behavior that is benchmarked against the 28-realization ensemble. With the current mesh, numerical schemes, and sub-grid scale turbulence model, more than 95% of the turbulent kinetic energy is directly resolved in the flow regions of interest. The large-scale flow structures inferred from a statistical analysis reveal a region of disorganized flow around the peripheral region of the spray jet, which appears to be linked to the entrainment process.

scholarly journals Turbulent Kinetic Energy Production in the Vane of a Low-Pressure Linear Turbine Cascade with Incoming Wakes

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
V. Michelassi ◽  
J. G. Wissink
Keyword(s):  
Boundary Layer ◽  
Kinetic Energy ◽  
Large Eddy Simulation ◽  
Turbulent Kinetic Energy ◽  
Suction Side ◽  
Low Pressure ◽  
Eddy Simulation ◽  
Transition Mechanism ◽  
Principal Axes ◽  
Large Eddy

Incompressible large eddy simulation and direct numerical simulation of a low-pressure turbine atRe=5.18×104and1.48×105with discrete incoming wakes are analyzed to identify the turbulent kinetic energy generation mechanism outside of the blade boundary layer. The results highlight the growth of turbulent kinetic energy at the bow apex of the wake and correlate it to the stress-strain tensors relative orientation. The production rate is analytically split according to the principal axes, and then terms are computed by using the simulation results. The analysis of the turbulent kinetic energy is followed both along the discrete incoming wakes and in the stationary frame of reference. Both direct numerical and large eddy simulation concur in identifying the same production mechanism that is driven by both a growth of strain rate in the wake, first, followed by the growth of turbulent shear stress after. The peak of turbulent kinetic energy diffuses and can eventually reach the suction side boundary layer for the largest Reynolds number investigated here with higher incidence angle. As a consequence, the local turbulence intensity outside the boundary layer can grow significantly above the free-stream level with a potential impact on the suction side boundary layer transition mechanism.

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