A two-scale Langevin PDF model for Richtmyer–Meshkov turbulence with a small Atwood number

2020 ◽  
Vol 403 ◽  
pp. 132276
Author(s):  
Olivier Soulard ◽  
Florian Guillois ◽  
Jérôme Griffond ◽  
Vladimir Sabelnikov ◽  
Serge Simoëns
Keyword(s):  
Pdf Model ◽  
Atwood Number

On Numerical Simulation of Fuel Mixed With Steam or Air to Investigate Soot and Other Emissions

2015 ◽  
Author(s):  
Ajit Patki ◽  
Xianchang Li ◽  
Daniel Chen ◽  
Helen Lou ◽  
Vijaya Damodara
Keyword(s):  
Combustion Efficiency ◽  
Combustion Mechanism ◽  
Fuel Type ◽  
Ansys Fluent ◽  
Pm 2.5 ◽  
Combustion Gases ◽  
Numerical Studies ◽  
Baseline Case ◽  
Substantial Risk ◽  
Pdf Model

Soot emissions (PM 2.5) as well as CO and NOx from industrial flares and other industrial processes or sources pose a substantial risk to human being health and the environment, and now are subject to new and tougher EPA regulations. Flaring is used widely used in many industries to dispose unwanted combustion gases by burning them as a flame. However, flaring produces significant amount of particulate matter in the form of soot, along with other harmful gas emissions. Although many experimental and numerical studies have previously been done on flames burning in a controlled condition, relatively few studies have been conducted with fuel-steam mixture. In practice, air and steam are commonly used to assist the flaring processes — control the smoke and the combustion efficiency. This study aims to investigate soot, CO and NOx emissions of turbulent diffusion methane and propane flame mixed with air or superheated steam. To study such effect numerically, the computational fluid dynamics software ANSYS Fluent 14.5 is used with non-premixed probability density function (PDF) model. The laminar flamelet is generated with automated grid refinement. For the soot generation, the Moss-Brookes soot model with Lee sub-model is considered. The combustion mechanism is developed by the authors’ research group from the combined GRI and USC mechanisms. Two types of fuel, methane and propane, are used. The amount of super-heated steam varied from four percent to twenty percent (4%, 8 %, 12%, 16%, and 20%), and the behavior of the flame is analyzed. For the baseline case, the jet has a diameter of 50.8 mm or 2 inches, and the jet velocity is kept to 1.0 m/s. A co-flow air is supplied at a velocity of 0.2 m/s. The temperature distribution of methane and propane are compared with different contents of steam or air assists. The NOx, Soot and CO yields (kg/kg) varying with steam or air percentages are also presented. The results indicate that the soot yield is dependent on fuel type strongly and the percentage of steam or air affects the soot yield differently as the fuel type varies.

scholarly journals The design, instrumentation, and validation of a multiphase shock tube facility

2017 ◽  
Author(s):  
◽  
Constantine Gregory Avgoustopoulos
Keyword(s):  
Shock Tube ◽  
Quantitative Data ◽  
Velocity Difference ◽  
Gas Cylinder ◽  
First Case ◽  
Experimental Apparatus ◽  
Large Particles ◽  
Particle Imaging ◽  
Atwood Number ◽  
Number Of Particles

This paper investigates the experimental work in Shock Driven Multiphase Instabilities (SDMI). SDMIs occur when an interface consisting of a particle seeded gas is instantaneously accelerated and begins mixing. SDMIs have similar flow morphologies to the Richtmyer-Meshkov Instability (RMI), however, the driving force inducing this flow is very different. SDMIs occur when there is a relative velocity difference between surrounding gas and the moving particles. This results to a shear at the edges and ultimately leads to rollups that are similar to a RMI. To investigate this phenomena, a shock tube facility was designed, calibrated, and tested to perform experiments. The experimental data was qualitatively compared to simulations performed, as well as to literature of similar experiments. Quantitative data was analyzed using Particle Imaging Velocimetry (PIV) to understand the flow of the instability. The flow morphologies observed in experiments have similar behavior to those performed in simulations. Additionally, the qualitative observations of experiments performed in this lab are also in agreement with experimental literature. Two different effective Atwood numbers are investigated in this study. The first case looks at a gas cylinder interface with an effective Atwood number of -0.01 and a gas Atwood number of -0.02, shocked with a Mach 1.66 shock wave. The observations show a dominating instability resulting in the gas Atwood number. What ends up happening is the smaller particles are pulled into the vortex and the large particles separate and trail behind. The second case looks at the same gas cylinder perturbation but with an effective Atwood number of 0.03 and a gas Atwood number of 0, shocked at Mach 1.66. The higher Atwood number was achieved by modifying the experimental apparatus slightly to deliver a greater number of particles to the shock tube. The experiments observed show that there is agreement with literature and simulations. Certain unusual filaments begin forming at late times, 4.0ms after shock. This was thought to only appear in a pure RMI. In the case of a SDMI, these filaments are a result of colliding particles.

scholarly journals Detection of Mobile Objects by Mixture PDF Model for Mobile Robots

2012 ◽  
Vol 25 (11) ◽  
pp. 308-315 ◽  
Author(s):  
Masahiro Tanaka ◽  
Masahiro Wada ◽  
Tomohiro Umetani ◽  
Minoru Ito
Keyword(s):  
Mobile Robots ◽  
Mobile Objects ◽  
Pdf Model

scholarly journals An SMLD Joint PDF Model for Turbulent Non-Premixed Combustion Using the Flamelet Progress-Variable Approach

2015 ◽  
Vol 95 (1) ◽  
pp. 97-119 ◽  
Author(s):  
Alessandro Coclite ◽  
Giuseppe Pascazio ◽  
Pietro De Palma ◽  
Luigi Cutrone ◽  
Matthias Ihme
Keyword(s):  
Premixed Combustion ◽  
Progress Variable ◽  
Variable Approach ◽  
Pdf Model

Statistical characteristics of turbulent mixing in spherical and cylindrical converging Richtmyer–Meshkov instabilities

2021 ◽  
Vol 928 ◽  
Author(s):  
Xinliang Li ◽  
Yaowei Fu ◽  
Changping Yu ◽  
Li Li
Keyword(s):  
Turbulent Mixing ◽  
Initial Perturbation ◽  
Great Influence ◽  
Mixing Layers ◽  
Statistical Characteristics ◽  
Computational Domain ◽  
Heavy Fluid ◽  
Node Number ◽  
Geometric Effect ◽  
Atwood Number

In this paper, the Richtmyer–Meshkov instabilities in spherical and cylindrical converging geometries with a Mach number of approximately 1.5 are investigated by using the high resolution implicit large eddy simulation method, and the influence of the geometric effect on the turbulent mixing is investigated. The heavy fluid is sulphur hexafluoride (SF6), and the light fluid is nitrogen (N2). The shock wave converges from the heavy fluid into the light fluid. The Atwood number is 0.678. The total structured and uniform Cartesian grid node number in the main computational domain is 20483. In addition, to avoid the influence of boundary reflection, a sufficiently long sponge layer with 50 non-uniform coarse grids is added for each non-periodic boundary. Present numerical simulations have high and nonlinear initial perturbation levels, which rapidly lead to turbulent mixing in the mixing layers. Firstly, some physical-variable mean profiles, including mass fraction, Taylor Reynolds number, turbulent kinetic energy, enstrophy and helicity, are provided. Second, the mixing characteristics in the spherical and cylindrical turbulent mixing layers are investigated, such as molecular mixing fraction, efficiency Atwood number, turbulent mass-flux velocity and density self-correlation. Then, Reynolds stress and anisotropy are also investigated. Finally, the radial velocity, velocity divergence and enstrophy in the spherical and cylindrical turbulent mixing layers are studied using the method of conditional statistical analysis. Present numerical results show that the geometric effect has a great influence on the converging Richtmyer–Meshkov instability mixing layers.

scholarly journals Richtmyer–Meshkov instability on a low Atwood number interface after reshock

Shock Waves ◽  
2012 ◽  
Vol 22 (4) ◽  
pp. 317-325 ◽  
Author(s):  
C. Weber ◽  
N. Haehn ◽  
J. Oakley ◽  
M. Anderson ◽  
R. Bonazza
Keyword(s):  
Atwood Number

Continuous thermodynamics for droplet vaporization: Comparison between Gamma-PDF model and QMoM

2009 ◽  
Vol 337 (6-7) ◽  
pp. 449-457 ◽  
Author(s):  
Claire Laurent ◽  
Gérard Lavergne ◽  
Philippe Villedieu
Keyword(s):  
Droplet Vaporization ◽  
Pdf Model

Flashback Limit and Mechanism of Methane and Syngas Fuel

2006 ◽  
Author(s):  
Gang Xu ◽  
Ying Tian ◽  
Quanbin Song ◽  
Aibin Fang ◽  
Yufeng Cui ◽  
...  
Keyword(s):  
Premixed Combustion ◽  
Product System ◽  
Gas Turbine Combustor ◽  
Optimal Range ◽  
Lean Premixed Combustion ◽  
Flame Holder ◽  
Ring Shape ◽  
Lean Premixed ◽  
Dimensionless Function ◽  
Pdf Model

Flashback is one of the major problems in lean premixed combustion of gas turbine combustor. Due to the effulgent future of co-product system and IGCC, lean premixed combustion, one of the approaches to ultra low NOx for rich hydrogen syngas fuel need farther research on anti-flashback and low pressure drop combustor. Mechanism and characteristics of methane and syngas flashback for 2 types of flame holders, i.e. ring shape and rod shape have been researched through experiment as well as numerical simulation. The partial premix model has been selected to simulate premixed combustion flashback process since it combined the advantage of PDF model and TFC model. Experiments demonstrate that, the flashback velocity of different fuel compositions or flame holder size generally can be correlated to the same dimensionless function by using Peclet number model if the structures of flame holders are the same. Peclet function curves were used to compare the anti-flashback performance of the 2 types of flame holders mentioned above with swirl holder. Boundary coaxial jet can change flashback through the wall into flashback in the core flow and significantly improve the anti-flashback performance of the ring-type flame holder on condition that the velocity of the boundary coaxial jet is in an optimal range. As the result, ring shape holder shows the best while swirl holder the worst on anti-flashback performance.

Dynamics of buoyancy-driven flows at moderately high Atwood numbers

2016 ◽  
Vol 795 ◽  
pp. 313-355 ◽  
Author(s):  
Bhanesh Akula ◽  
Devesh Ranjan
Keyword(s):  
Volume Fraction ◽  
Mixing Layer ◽  
Mie Scattering ◽  
Splitter Plate ◽  
Total Probability ◽  
Reynolds Stresses ◽  
Turbulence Statistics ◽  
Velocity Statistics ◽  
Anisotropy Tensor ◽  
Atwood Number

Simultaneous density and velocity turbulence statistics for Rayleigh–Taylor-driven flows at a moderately high Atwood number ($A_{t}$) of $0.73\pm 0.02$ are obtained using a new convective type or statistically steady gas tunnel facility. Air and air–helium mixture are used as working fluids to create a density difference in this facility, with a thin splitter plate separating the two streams flowing parallel to each other at the same velocity ($U=3~\text{m}~\text{s}^{-1}$). At the end of the splitter plate, the two miscible fluids are allowed to mix and the instability develops. Visualization and Mie-scattering techniques are used to obtain structure shape, volume fraction profile and mixing height growth information. Particle image velocimetry (PIV) and hot-wire techniques are used to measure planar and point-wise velocity statistics in the developing mixing layer. Asymmetry is evident in the flow field from the Mie-scattering images, with the spike side showing a more gradual decline in volume fraction than the bubble side. The spike side of the mixing layer grows 50 % faster than the bubble side. PIV is implemented for the first time in these moderately high-Atwood-number experiments ($A_{t}>0.1$) to obtain root-mean-square velocities, anisotropy tensor components and Reynolds stresses across the mixing layer. Overall, the turbulence statistics measured have shown different scaling compared to small-Atwood-number experiments. However, the total probability density functions for the velocities and turbulent mass fluxes exhibit behaviour similar to small-Atwood-number experiments. Conditional statistics reveal different values for turbulence statistics for spikes and bubbles, unlike small-Atwood-number experiments.

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