Simulating Flame Lift-Off Characteristics of Diesel and Biodiesel Fuels Using Detailed Chemical-Kinetic Mechanisms and LES Turbulence Model

2011 ◽  
Author(s):  
Sibendu Som ◽  
Douglas E. Longman ◽  
Zhaoyu Luo ◽  
Max Plomer ◽  
Tianfeng Lu ◽  
...  
Keyword(s):  
Turbulence Model ◽  
Turbulence Models ◽  
Chemical Kinetic ◽  
Upstream Region ◽  
Spray Combustion ◽  
Turbulent Diffusion Flame ◽  
Lifted Flame ◽  
Kinetic Mechanisms ◽  
Lift Off ◽  
Biodiesel Fuels

Combustion in direct-injection diesel engines occurs in a lifted, turbulent diffusion flame mode. Numerous studies indicate that the combustion and emissions in such engines are strongly influenced by the lifted flame characteristics, which are in turn determined by fuel and air mixing in the upstream region of the lifted flame, and consequently by the liquid breakup and spray development processes. From a numerical standpoint, these spray combustion processes depend heavily on the choice of underlying spray, combustion, and turbulence models. The present numerical study investigates the influence of different chemical kinetic mechanisms for diesel and biodiesel fuels, as well as Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation (LES) turbulence models on predicting flame lift-off lengths (LOLs) and ignition delays. Specifically, two chemical kinetic mechanisms for n-heptane (NHPT) and three for biodiesel surrogates are investigated. In addition, the RNG k-ε (RANS) model is compared to the Smagorinsky based LES turbulence model. Using adaptive grid resolution, minimum grid sizes of 250 μm and 125 μm were obtained for the RANS and LES cases respectively. Validations of these models were performed against experimental data from Sandia National Laboratories in a constant volume combustion chamber. Ignition delay and flame lift-off validations were performed at different ambient temperature conditions. The LES model predicts lower ignition delays and qualitatively better flame structures compared to the RNG k-ε model. The use of realistic chemistry and a ternary surrogate mixture, which consists of methyl decanoate, methyl 9-decenoate, and NHPT, results in better predicted LOLs and ignition delays. For diesel fuel though, only marginal improvements are observed by using larger size mechanisms. However, these improved predictions come at a significant increase in computational cost.

Simulating Flame Lift-Off Characteristics of Diesel and Biodiesel Fuels Using Detailed Chemical-Kinetic Mechanisms and Large Eddy Simulation Turbulence Model

2012 ◽  
Vol 134 (3) ◽  
Author(s):  
Sibendu Som ◽  
Douglas E. Longman ◽  
Zhaoyu Luo ◽  
Max Plomer ◽  
Tianfeng Lu ◽  
...  
Keyword(s):  
Large Eddy Simulation ◽  
Turbulence Model ◽  
Turbulence Models ◽  
Chemical Kinetic ◽  
Spray Combustion ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Kinetic Mechanisms ◽  
Lift Off ◽  
Biodiesel Fuels

Combustion in direct-injection diesel engines occurs in a lifted, turbulent diffusion flame mode. Numerous studies indicate that the combustion and emissions in such engines are strongly influenced by the lifted flame characteristics, which are in turn determined by fuel and air mixing in the upstream region of the lifted flame, and consequently by the liquid breakup and spray development processes. From a numerical standpoint, these spray combustion processes depend heavily on the choice of underlying spray, combustion, and turbulence models. The present numerical study investigates the influence of different chemical kinetic mechanisms for diesel and biodiesel fuels, as well as Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES) turbulence models on predicting flame lift-off lengths (LOLs) and ignition delays. Specifically, two chemical kinetic mechanisms for n-heptane (NHPT) and three for biodiesel surrogates are investigated. In addition, the renormalization group (RNG) k-ε (RANS) model is compared to the Smagorinsky based LES turbulence model. Using adaptive grid resolution, minimum grid sizes of 250 μm and 125 μm were obtained for the RANS and LES cases, respectively. Validations of these models were performed against experimental data from Sandia National Laboratories in a constant volume combustion chamber. Ignition delay and flame lift-off validations were performed at different ambient temperature conditions. The LES model predicts lower ignition delays and qualitatively better flame structures compared to the RNG k-ε model. The use of realistic chemistry and a ternary surrogate mixture, which consists of methyl decanoate, methyl nine-decenoate, and NHPT, results in better predicted LOLs and ignition delays. For diesel fuel though, only marginal improvements are observed by using larger size mechanisms. However, these improved predictions come at a significant increase in computational cost.

Modeling spray combustion using multi-component surrogate fuels

2021 ◽  
pp. 095765092110025
Author(s):  
Tao Yang ◽  
Ran Yi ◽  
Qiaoling Wang ◽  
Chien-Pin Chen
Keyword(s):  
Chemical Properties ◽  
Kinetic Mechanism ◽  
Chemical Kinetic ◽  
Spray Combustion ◽  
Surrogate Fuels ◽  
Diesel Fuels ◽  
Constant Volume Chamber ◽  
Kinetic Mechanisms ◽  
Lift Off ◽  
Evaporation Models

Kerosene and diesel fuels involved in spray combustion operations are complex fuels composed of a wide and diverse variety of hydrocarbon components. For practical numerical modeling of the evaporation and combustion phenomena in a combustor, well-designed surrogates fuels that can mimic the real fuel thermal and chemical properties can be utilized. In this study, predictions and validations of the influence of fuel on the liquid and vapor penetration characteristics within a constant-volume chamber were first performed utilizing a benchmark m-xylene/ n-dodecane, Jet-A, and diesel surrogate fuels. Then, simulations of reacting spray of a bi-component m-xylene/ n-dodecane fule, and a four-component Jet-A surrogate fuel ( n-dodecane (C12H26), iso-cetane (C16H34), trans-decalin (C10H18) and toluene (C7H8)) were studied aided by skeleton chemical kinetic mechanisms available from the literature. The results of ignition delay time, lift-off length, radicals, and the mass fraction histories of fuel species were comprehensively used to assess the performance of relevant thermophysical and chemical sub-models. Two different chemical mechanisms were compared in detail to investigate the effect of the chemical kinetics model on the flame structures and spray characteristics. It has been found that the spray ignition of multi-component fuels is remarkably influenced by the chosen chemical kinetic mechanism and less affected by the droplet evaporation models.

Investigation of Biodiesel Combustion and Emissions Using Reduced Chemical Kinetics

2018 ◽  
Vol 140 (6) ◽  
Author(s):  
Aron P. Dobos ◽  
Allan T. Kirkpatrick
Keyword(s):  
Chemical Kinetic ◽  
Operational Parameters ◽  
Computationally Efficient ◽  
Compression Ignition Engine ◽  
Spray Structure ◽  
Kinetic Mechanisms ◽  
Lift Off ◽  
Dimensional Simulation ◽  
Complex Relationships ◽  
Biodiesel Fuels

This paper studies the differences in spray structure and emissions trends between diesel and biodiesel fuels in a compression ignition engine. A computationally efficient and predictive quasi-dimensional simulation model is combined with fuel-specific physical properties and chemical kinetic mechanisms to predict spray mixing, combustion, and emissions behavior. The results underscore the complex relationships between NOx emissions, operational parameters, and fuel chemistry and provide further evidence of a link between stoichiometry near the flame lift-off length and formation of NOx.

scholarly journals Simulation of a GOx-GCH4 Rocket Combustor and the Effect of the GEKO Turbulence Model Coefficients

Aerospace ◽  
2021 ◽  
Vol 8 (11) ◽  
pp. 341
Author(s):  
Evgeny Strokach ◽  
Victor Zhukov ◽  
Igor Borovik ◽  
Andrej Sternin ◽  
Oscar J. Haidn
Keyword(s):  
Experimental Data ◽  
Heat Flux ◽  
Turbulence Model ◽  
Chemical Kinetic ◽  
Wall Heat Flux ◽  
Combustion Model ◽  
Combustion Chambers ◽  
Separation Parameter ◽  
Kinetic Mechanisms ◽  
Stable Performance

In this study, a single injector methane-oxygen rocket combustor is numerically studied. The simulations included in this study are based on the hardware and experimental data from the Technical University of Munich. The focus is on the recently developed generalized k–ω turbulence model (GEKO) and the effect of its adjustable coefficients on the pressure and on wall heat flux profiles, which are compared with the experimental data. It was found that the coefficients of ‘jet’, ‘near-wall’, and ‘mixing’ have a major impact, whereas the opposite can be deduced about the ‘separation’ parameter Csep, which highly influences the pressure and wall heat flux distributions due to the changes in the eddy-viscosity field. The simulation results are compared with the standard k–ε model, displaying a qualitatively and quantitatively similar behavior to the GEKO model at a Csep equal to unity. The default GEKO model shows a stable performance for three oxidizer-to-fuel ratios, enhancing the reliability of its use. The simulations are conducted using two chemical kinetic mechanisms: Zhukov and Kong and the more detailed RAMEC. The influence of the combustion model is of the same order as the influence of the turbulence model. In general, the numerical results present a good or satisfactory agreement with the experiment, and both GEKO at Csep = 1 or the standard k–ε model can be recommended for usage in the CFD simulations of rocket combustion chambers, as well as the Zhukov–Kong mechanism in conjunction with the flamelet approach.

CFD Simulation of Gasoline Compression Ignition

2014 ◽  
Author(s):  
Janardhan Kodavasal ◽  
Christopher Kolodziej ◽  
Stephen Ciatti ◽  
Sibendu Som
Keyword(s):  
Turbulence Model ◽  
Cfd Simulation ◽  
Turbulence Models ◽  
Kinetic Mechanism ◽  
Chemical Kinetic ◽  
Combustion Model ◽  
Low Temperature Combustion ◽  
Compression Ignition ◽  
Simulation Results ◽  
The Impact

Gasoline compression ignition (GCI) is a low temperature combustion (LTC) concept that has been gaining increasing interest over the recent years owing to its potential to achieve diesel-like thermal efficiencies with significantly reduced engine-out nitrogen oxides (NOx) and soot emissions compared to diesel engines. In this work, closed-cycle computational fluid dynamics (CFD) simulations are performed of this combustion mode using a sector mesh in an effort to understand effects of model settings on simulation results. One goal of this work is to provide recommendations for grid resolution, combustion model, chemical kinetic mechanism, and turbulence model to accurately capture experimental combustion characteristics. Grid resolutions ranging from 0.7 mm to 0.1 mm minimum cell sizes were evaluated in conjunction with both Reynolds averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) based turbulence models. Solution of chemical kinetics using the multi-zone approach is evaluated against the detailed approach of solving chemistry in every cell. The relatively small primary reference fuel (PRF) mechanism (48 species) used in this study is also evaluated against a larger 312-species gasoline mechanism. Based on these studies the following model settings are chosen keeping in mind both accuracy and computation costs — 0.175 mm minimum cell size grid, RANS turbulence model, 48-species PRF mechanism, and multi-zone chemistry solution with bin limits of 5 K in temperature and 0.05 in equivalence ratio. With these settings, the performance of the CFD model is evaluated against experimental results corresponding to a low load start of injection (SOI) timing sweep. The model is then exercised to investigate the effect of SOI on combustion phasing with constant intake valve closing (IVC) conditions and fueling over a range of SOI timings to isolate the impact of SOI on charge preparation and ignition. Simulation results indicate that there is an optimum SOI timing, in this case −30°aTDC (after top dead center), which results in the most stable combustion. Advancing injection with respect to this point leads to significant fuel mass burning in the colder squish region, leading to retarded phasing and ultimately misfire for SOI timings earlier than −42°aTDC. On the other hand, retarding injection beyond this optimum timing results in reduced residence time available for gasoline ignition kinetics, and also leads to retarded phasing, with misfire at SOI timings later than −15°aTDC.

Turbulent Spray Combustion Modeling Using Various Kinetic Solvers and Turbulence Models

2018 ◽  
Vol 140 (12) ◽  
Author(s):  
J. A. Piehl ◽  
O. Samimi Abianeh ◽  
A. Goyal ◽  
L. Bravo
Keyword(s):  
Turbulence Models ◽  
Dynamic Structure ◽  
Kinetic Mechanism ◽  
Measured Data ◽  
Spray Combustion ◽  
Gas Temperature ◽  
Fine Mesh ◽  
Turbulent Spray Combustion ◽  
Turbulent Spray ◽  
Lift Off

Turbulent spray combustion of n-dodecane was modeled at relevant engine conditions using two combustion models (direct integration of chemistry (DIC) and flamelet generated manifolds (FGM)) and multifidelity turbulence models (dynamic structure large eddy simulation (LES) and renormalization group (RNG) Reynolds-averaged Naiver–Stokes (RANS)). The main objective of this work is to study the effect of various combustion and turbulence models on spray behavior and quantify these effects. To reach these objectives, a recently developed kinetic mechanism and well-established spray models were utilized for the three-dimensional turbulent spray simulation at various combustion chamber initial gas temperature and pressure conditions. Fine mesh with a size of 31 μm was utilized to resolve small eddies in the periphery of the spray. In addition, a new methodology for mesh generation was proposed and investigated to simulate the measured data fluctuation in the CFD domain. The pressure-based ignition delay, flame lift-off length (LOL), species concentrations, spray, and jet penetrations were modeled and compared with measured data. Differences were observed between various combustion and turbulence models in predicting the spray characteristics. However, these differences are within the uncertainties, error, and variations of the measured data.

Computational Fluid Dynamics Simulation of Gasoline Compression Ignition

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Janardhan Kodavasal ◽  
Christopher P. Kolodziej ◽  
Stephen A. Ciatti ◽  
Sibendu Som
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Turbulence Model ◽  
Turbulence Models ◽  
Chemical Kinetic ◽  
Dynamics Simulation ◽  
Combustion Model ◽  
Compression Ignition ◽  
Simulation Results ◽  
The Impact

Gasoline compression ignition (GCI) is a low temperature combustion (LTC) concept that has been gaining increasing interest over the recent years owing to its potential to achieve diesel-like thermal efficiencies with significantly reduced engine-out nitrogen oxides (NOx) and soot emissions compared to diesel engines. In this work, closed-cycle computational fluid dynamics (CFD) simulations are performed of this combustion mode using a sector mesh in an effort to understand effects of model settings on simulation results. One goal of this work is to provide recommendations for grid resolution, combustion model, chemical kinetic mechanism, and turbulence model to accurately capture experimental combustion characteristics. Grid resolutions ranging from 0.7 mm to 0.1 mm minimum cell sizes were evaluated in conjunction with both Reynolds averaged Navier–Stokes (RANS) and large eddy simulation (LES) based turbulence models. Solution of chemical kinetics using the multizone approach is evaluated against the detailed approach of solving chemistry in every cell. The relatively small primary reference fuel (PRF) mechanism (48 species) used in this study is also evaluated against a larger 312-species gasoline mechanism. Based on these studies, the following model settings are chosen keeping in mind both accuracy and computation costs—0.175 mm minimum cell size grid, RANS turbulence model, 48-species PRF mechanism, and multizone chemistry solution with bin limits of 5 K in temperature and 0.05 in equivalence ratio. With these settings, the performance of the CFD model is evaluated against experimental results corresponding to a low load start of injection (SOI) timing sweep. The model is then exercised to investigate the effect of SOI on combustion phasing with constant intake valve closing (IVC) conditions and fueling over a range of SOI timings to isolate the impact of SOI on charge preparation and ignition. Simulation results indicate that there is an optimum SOI timing, in this case −30 deg aTDC (after top dead center), which results in the most stable combustion. Advancing injection with respect to this point leads to significant fuel mass burning in the colder squish region, leading to retarded phasing and ultimately misfire for SOI timings earlier than −42 deg aTDC. On the other hand, retarding injection beyond this optimum timing results in reduced residence time available for gasoline ignition kinetics, and also leads to retarded phasing, with misfire at SOI timings later than −15 deg aTDC.

scholarly journals Analysis of Flow Characteristics and Effects of Turbulence Models for the Butterfly Valve

2021 ◽  
Vol 11 (14) ◽  
pp. 6319
Author(s):  
Sung-Woong Choi ◽  
Hyoung-Seock Seo ◽  
Han-Sang Kim
Keyword(s):  
Turbulence Model ◽  
Dissipation Rate ◽  
Flow Characteristics ◽  
Turbulence Models ◽  
Flow Properties ◽  
Nominal Diameter ◽  
Large Pressure ◽  
Sst Model ◽  
Turbulence Effect ◽  
Valve Opening

In the present study, the flow characteristics of butterfly valves with different sizes DN 80 (nominal diameter: 76.2 mm), DN 262 (nominal diameter: 254 mm), DN 400 (nominal diameter: 406 mm) were numerically investigated under different valve opening percentages. Representative two-equation turbulence models of two-equation k-epsilon model of Launder and Sharma, two-equation k-omega model of Wilcox, and two-equation k-omega SST model of Menter were selected. Flow characteristics of butterfly valves were examined to determine turbulence model effects. It was determined that increasing turbulence effect could cause many discrepancies between turbulence models, especially in areas with large pressure drop and velocity increase. In addition, sensitivity analysis of flow properties was conducted to determine the effect of constants used in each turbulence model. It was observed that the most sensitive flow properties were turbulence dissipation rate (Epsilon) for the k-epsilon turbulence model and turbulence specific dissipation rate (Omega) for the k-omega turbulence model.

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