Lateral jet injection into typical combustor flowfields

30th Joint Propulsion Conference and Exhibit, 1994

Flows through three reference nozzles have been calculated to determine the capabilities and limitations of the widely used Navier-Stokes solver, PARCo The nozzles examined have similar dominant flow characteristics as those considered for supersonic transport programs. Flows from an inverted velocity profile (IVP) nozzle, an underexpanded nozzle, and an ejector nozzle were examined. PARe calculations were obtained with its standard algebraic turbulence model, Thomas, and the two-equation turbulence model, Chien k-£. The Thomas model was run with the default coefficient of mixing set both at 0.09 and a larger value of 0.13 to improve the mixing prediction. Calculations using the default value substantially underpredicted the mixing for all three flows. The calculations obtained with the higher mixing coefficient better predicted mixing in the NP and underexpanded nozzle flows but adversely affected PARC's convergence characteristics for the NP nozzle case. The ejector nozzle case did not converge with the Thomas model and the higher mixing coefficient. The Chien k-E results were in better agreement with the experimental data overall than were those of the Thomas run with the default mixing coefficient, but the default boundary conditions for k and E underestimated the levels of mixing near the nozzle exits. Nomenclature A cross-sectional area in ejector nozzle mixing region A + van Driest damping constant = 26 C EI Chien k-E turbulence model constant = 1.35 C E2 Chien k-E turbulence model constant = 1.8 C Il Chien k-E turbulence model constant = 0.09 fw f l , f2 terms in Chien k-E turbulence model H distance from centerline to top or bottom wall of ejector nozzle K Von Karman constant = 0.41 k turbulent kinetic energy p density CJ k Chien k-£ turbulence model constant = 1.0 CJ E Chien k-£ turbulence model constant = 1.3 w vorticity Wc Thomas model maximum vorticity Subscripts: i, j computational coordinates max maximum min minimum p density CJ k Chien k-£ turbulence model constant = 1.0 CJ E Chien k-£ turbulence model constant = 1.3 w vorticity Wc Thomas model maximum vorticity Subscripts: i, j computational coordinates max maximum min minimum OF REPORT OFTHIS PAGE OF ABSTRACT Unclassified Unclassified Unclassified NSN 7540-01 -280-5500 S tandard Form 2 98 (R ev . 2-89) Prescribed by ANSI Std. Z39-18 298-102

Engineering Applications of Computational Fluid Mechanics, 2012

Reynolds-Averaged Navier-Stokes simulations have been performed to investigate the effect of nozzle geometry on the turbulence characteristics of incompressible fluid flow through nozzles at Reynolds number of approximately 50,000. Four nozzles have been considered: a baseline nozzle and three modified nozzles (extended, grooved and ringed). The flow in these nozzles has been simulated using different turbulence closure models, including Spalart-Allmaras, variants of k-ε and k-ω, and the Reynolds Stress Model (RSM). By comparison to experimental data, it is shown that the RSM produces more accurate results for the prediction of turbulent fluctuations. The presence of a ring significantly increases both the turbulence intensity and mean velocity at the exit, and requires a much higher inlet pressure to move the fluid through the nozzle. On the other hand, cutting a groove near the exit or extending the nozzle has little effect on the exit flow characteristics.

Engineering Applications of Computational Fluid Mechanics, 2012

Reynolds-Averaged Navier-Stokes simulations have been performed to investigate the effect of nozzle geometry on the turbulence characteristics of incompressible fluid flow through nozzles at Reynolds number of approximately 50,000. Four nozzles have been considered: a baseline nozzle and three modified nozzles (extended, grooved and ringed). The flow in these nozzles has been simulated using different turbulence closure models, including Spalart-Allmaras, variants of k-ε and k-ω, and the Reynolds Stress Model (RSM). By comparison to experimental data, it is shown that the RSM produces more accurate results for the prediction of turbulent fluctuations. The presence of a ring significantly increases both the turbulence intensity and mean velocity at the exit, and requires a much higher inlet pressure to move the fluid through the nozzle. On the other hand, cutting a groove near the exit or extending the nozzle has little effect on the exit flow characteristics.

Swirling flow discharged from an injector nozzle is important for flame stabilization in the jet engine combustion process. Inclusion of the details of the swirl-generating device, ie, the realistic injector nozzle geometry, in combustor numerical simulation is necessary because the complicated, spatially developing swirl pattern produced by a nozzle is difficult to emulate faithfully using indirect means. An indirect approach of swirl generation for large-eddy simulation was developed by Pierce & Moin (1998).

ilass europe, 2010

URANS and SAS analysis of turbulent flow in a GDI nozzle was carried out. The vortex structures, velocity and pressure distributions predicted based on the two different approaches were compared both for instant and statistical values. FFT analysis was applied to the time series of mass flow rate, the velocity, pressure and turbulence quantities at monitoring points. Only one dominant frequency was predicted by the URANS approach using the SST turbulence model. A clear correlation was found among the frequency of the mass flow rate, pressure and velocity at monitor points. In contrast, SAS predicted multiple frequencies. Though no simple correlation was obtained, the frequency of big event in mass flow time series was found to be linked to the first dominant frequency of the pressure monitors.

length was ten times the inlet diameter so that the duct has a maximum L/D = 10. The lower L/Ds were achieved by cutting the length after testing a particular L/D. PSI model 9010 pressure transducer was used for measuring pressure at the base, the stagnation pressure in the main settling chamber and the pressure in the control chamber. It has 16 channels and pressure range is 0-300 psi. It averages 250 samples per second and displays the reading. The software provided by the manufacturer was used to interface the transducer with the computer. The user-friendly menu driven software acquires data and shows the pressure readings from all the 16 channels simultaneously in a window type display on the computer screen. The software can be used to choose the units of pressure from a list of available units, perform a re-zero/full calibration, etc. The transducer also has a facility to choose the number of samples to be averaged, by means of dipswitch settings. It could be operated in temperatures ranging from -20° to +60° Celsius and 95 per cent humidity.

2010

ABSTRACT The spatial development of steady flow through a constricted rectangular nozzle is characterised. The constriction consists of an obstacle in the shape of a trapezoid wedge, which is inserted perpendicular to the main flow direction. The channel exit is situated downstream the obstacle at 1.5 times the minimum aperture. The constriction degree is fixed to 70% and the aspect ratio is 4 in the unconstricted and 15 in the constricted portion of the channel so that the flow is considered two-dimensional.

International Journal of Engineering & Technology, 2018

A numerical simulation was carried out to compare various turbulence models simulating axisymmetric nozzle flow past suddenly expanded ducts. The simulations were done for L/D = 10. The convergent-divergent nozzle has been modeled and simulated using the turbulence models: The Standard k-ε model, The Standard k-ω model and The SST k-ω model. Numerical simulations were done for Mach numbers 1.87, 2.2, and 2.58 and the nozzles were operated for NPRs in the range from 3 to 11. From the numerical analysis it is apparent that for a given Mach number and effect of NPR will result in maximum gain or loss of pressure. Numerical results are in good agreement with the experimental results.

2017

In modern Computational Fluid Dynamic (CFD) Analysis of Convergent-Divergent (C-D) Nozzles, current research has shown that, it is common practice to use either experimental or analytical results to predict the accuracy of the CFD models by comparison of the results. It is also commonly agreed, amongst the literature reviewed, that the CFD modelling software packages available do not accurately model turbulence for applications such as transonic C-D nozzles. This study aims to develop a theoretical approach for calculation of flow properties along the axis of the C-D nozzle based on the fundamental gas dynamic equations. The theoretical analyses is validated by experimental data. Then, the CFD model is used to simulate the experimental cases which are compared with the data from both theoretical analysis and experimental measurements. Then, the validated CFD model can be used for more complex analyses, representing more elaborate flow phenomena such as internal shockwaves and boundary layers. The geometry used in the analytical study and CFD simulations constructed to model the experimental rig. The [1, 2] analytical study is undertaken using isentropic and adiabatic relationships and the output of the analytical study, the 'shockwave location tool', is created. The results from the analytical study are then used to optimise the redesign an experimental rig to for more favorable placement of pressure taps and gain a much better representation of the shockwaves occurring in the divergent section of the nozzle. The results from the CFD model can then be directly compared other results in order to gauge the accuracy of each method of analysis. The validated model can then be used in order to create several, novel nozzle designs which may offer better performance and ease of manufacture and may present feasible improvements to existing high-speed flow applications.