Sibendu Som

Development and validation of an n-dodecane skeletal mechanism for spray combustion applications

n-Dodecane is a promising surrogate fuel for diesel engine study because its physicochemical properties are similar to those of the practical diesel fuels. In the present study, a skeletal mechanism for n-dodecane with 105 species and 420 reactions was developed for spray combustion simulations. The reduction starts from the most recent detailed mechanism for n-alkanes consisting of 2755 species and 11,173 reactions developed by the Lawrence Livermore National Laboratory. An algorithm combining direct relation graph with expert knowledge (DRGX) and sensitivity analysis was employed for the present skeletal reduction. The skeletal mechanism was first extensively validated in 0-D and 1-D combustion systems, including auto-ignition, jet stirred reactor (JSR), laminar premixed flame and counter flow diffusion flame. Then it was coupled with well-established spray models and further validated in 3-D turbulent spray combustion simulations under engine-like conditions. These simulations were compared with the recent experiments with n-dodecane as a surrogate for diesel fuels. It can be seen that combustion characteristics such as ignition delay and flame lift-off length were well captured by the skeletal mechanism, particularly under conditions with high ambient temperatures. Simulations also captured the transient flame development phenomenon fairly well. The results further show that ignition delay may not be the only factor controlling the stabilisation of the present flames since a good match in ignition delay does not necessarily result in improved flame lift-off length prediction.

Grid-Convergent Spray Models for Internal Combustion Engine CFD Simulations

A state-of-the-art spray modeling methodology is presented. Key features of the methodology, such as Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, are described. The ability of this approach to use cell sizes much smaller than the nozzle diameter is demonstrated. Grid convergence of key parameters is verified for non-evaporating, evaporating, and reacting spray cases using cell sizes down to 1/32 mm. Grid settings are recommended that optimize the accuracy/runtime tradeoff for RANS-based spray simulations.Copyright

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

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 Reynoldsaveraged 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-e (RANS) model is compared to the Smagorinsky based LES turbulence model. Using adaptive grid resolution, minimum grid sizes of 250lm and 125lm 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-e 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. [DOI: 10.1115/1.4007216]

Computational Fluid Dynamics Simulation of Gasoline Compression Ignition

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.

A reduced mechanism for biodiesel surrogates with low temperature chemistry for compression ignition engine applications

Biodiesel is a promising alternative fuel for compression ignition (CI) engines. It is a renewable energy source that can be used in these engines without significant alteration in design. The detailed chemical kinetics of biodiesel is however highly complex. In the present study, a skeletal mechanism with 123 species and 394 reactions for a tri-component biodiesel surrogate, which consists of methyl decanoate, methyl 9-decanoate and n-heptane was developed for simulations of 3-D turbulent spray combustion under engine-like conditions. The reduction was based on an improved directed relation graph (DRG) method that is particularly suitable for mechanisms with many isomers, followed by isomer lumping and DRG-aided sensitivity analysis (DRGASA). The reduction was performed for pressures from 1 to 100 atm and equivalence ratios from 0.5 to 2 for both extinction and ignition applications. The initial temperatures for ignition were from 700 to 1800 K. The wide parameter range ensures the applicability of the skeletal mechanism under engine-like conditions. As such the skeletal mechanism is applicable for ignition at both low and high temperatures. Compared with the detailed mechanism that consists of 3299 species and 10806 reactions, the skeletal mechanism features a significant reduction in size while still retaining good accuracy and comprehensiveness. The validations of ignition delay time, flame lift-off length and important species profiles were also performed in 3-D engine simulations and compared with the experimental data from Sandia National Laboratories under CI engine conditions.

Grid-Convergent Spray Models for Internal Combustion Engine Computational Fluid Dynamics Simulations

A state-of-the-art spray modeling methodology is presented. Key features of the methodology, such as adaptive mesh refinement (AMR), advanced liquid–gas momentum coupling, and improved distribution of the liquid phase, are described. The ability of this approach to use cell sizes much smaller than the nozzle diameter is demonstrated. Grid convergence of key parameters is verified for nonevaporating, evaporating, and reacting spray cases using cell sizes down to 1/32 mm. Grid settings are recommended that optimize the accuracy/runtime tradeoff for RANS-based spray simulations.

A Progress Review on Soot Experiments and Modeling in the Engine Combustion Network (ECN)

The following individuals and funding agencies are acknowledged for their support. The authors from DTU acknowledge the Technical University of Denmark, Danish Strategic Research Council, and MAN Diesel & Turbo University of Wisconsin: Financial support provided by the Princeton Combustion Energy Frontier Research Center. ETH Zurich: Financial support from the Swiss Federal Office of Energy (grant no. SI/500818-01) and the Swiss Competence Center for Energy and Mobility (CCEM project “In-cylinder emission reduction”) is gratefully acknowledged. Argonne National Labs: Work was funded by U.S. DOE Office of Vehicle Technologies, Office of Energy Efficiency and Renewable Energy under Contract No. DE-AC02-06CH11357. We also gratefully acknowledge the computing resources provided on Fusion, a computing cluster operated by the Laboratory Computing Resource Center at Argonne National Laboratory. Sandia National Labs, Combustion Research Facility: Work was supported by the U.S. Department of Energy, Office of Vehicle Technologies. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under contract DEAC04-94AL85000. Chris Carlen and Dave Cicone are gratefully acknowledged for technical assistance. The authors from ANL and SNL also wish to thank Gurpreet Singh and Leo Breton, program managers at U.S. DOE, for their support.

Comparison of Mixture and Multifluid Models for In-Nozzle Cavitation Prediction

Fuel injectors often feature cavitation because of large pressure gradients, which in some regions lead to extremely low pressures. The main objective of this work is to compare the prediction capabilities of two multiphase flow approaches for modeling cavitation in small nozzles, like those used in high-pressure diesel or gasoline fuel injectors. Numerical results are assessed against quantitative high resolution experimental data collected at Argonne National Laboratory using synchrotron X-ray radiography of a model nozzle. One numerical approach uses a homogeneous mixture model with the volume of fluid (VOF) method, in which phase change is modeled via the homogeneous relaxation model (HRM). The second approach is based on the multifluid nonhomogeneous model and uses the Rayleigh bubble-dynamics model to account for cavitation. Both models include three components, i.e., liquid, vapor, and air, and the flow is compressible. Quantitatively, the amount of void predicted by the multifluid model is in good agreement with measurements, while the mixture model overpredicts the values. Qualitatively, void regions look similar and compare well with the experimental measurements. Grid converged results have been achieved for the prediction of mass flow rate while grid-convergence for void fraction is still an open point. Simulation results indicate that most of the vapor is produced at the nozzle entrance. In addition, downstream along the centerline, void due to expansion of noncondensable gases has been identified. The paper also includes a discussion about the effect of turbulent pressure fluctuations on cavitation inception.

Modeling of internal and near-nozzle flow for a GDI fuel injector

A numerical study of two-phase flow inside the nozzle holes and the issuing spray jets for a multi-hole direct injection gasoline injector has been presented in this work. The injector geometry is representative of the Spray G nozzle, an eight-hole counterbore injector, from the Engine Combustion Network (ECN). Simulations have been carried out for a fixed needle lift. Effects of turbulence, compressibility and non-condensable gases have been considered in this work. Standard k–e turbulence model has been used to model the turbulence. Homogeneous Relaxation Model (HRM) coupled with Volume of Fluid (VOF) approach has been utilized to capture the phase change phenomena inside and outside the injector nozzle. Three different boundary conditions for the outlet domain have been imposed to examine non-flashing and evaporative, non-flashing and non-evaporative and flashing conditions. Noticeable hole-to-hole variations have been observed in terms of mass flow rates for all the holes under all the operating conditions considered in this study. Inside the nozzle holes mild cavitation-like and in the near-nozzle region flash boiling phenomena have been predicted when liquid fuel is subjected to superheated ambiance. Under favorable conditions considerable flashing has been observed in the near-nozzle regions. An enormous volume is occupied by the gasoline vapor, formed by the flash boiling of superheated liquid fuel. Large outlet domain connecting the exits of the holes and the pressure outlet boundary appeared to be necessary leading to substantial computational cost. Volume-averaging instead of mass-averaging is observed to be more effective, especially for finer mesh resolutions.Copyright

Quantum Tunneling Affects Engine Performance

We study the role of individual reaction rates on engine performance, with an emphasis on the contribution of quantum tunneling. It is demonstrated that the effect of quantum tunneling corrections for the reaction HO2 + HO2 = H2O2 + O2 can have a noticeable impact on the performance of a high-fidelity model of a compression-ignition (e.g., diesel) engine, and that an accurate prediction of ignition delay time for the engine model requires an accurate estimation of the tunneling correction for this reaction. The three-dimensional model includes detailed descriptions of the chemistry of a surrogate for a biodiesel fuel, as well as all the features of the engine, such as the liquid fuel spray and turbulence. This study is part of a larger investigation of how the features of the dynamics and potential energy surfaces of key reactions, as well as their reaction rate uncertainties, affect engine performance, and results in these directions are also presented here.