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Surface film formation is an important phenomenon during spray impingement in a combustion chamber. The film that forms on the chamber walls and piston bowl produces soot post-combustion. While some droplets stick to the wall surface, others splash and interact with the gas present inside the combustion chamber. Accurate prediction of both the film thickness and splashed mass is crucial for surface film model development since it leads to a precise estimation of the amount of soot and other exhaust gases formed. This information could guide future studies aimed at a comprehensive understanding of the combustion process and might enable development of engines with reduced emissions. Dynamic structure Large Eddy Simulation (LES) turbulence model implemented for in-cylinder sprays [1] has shown to predict the flow structure of a spray more accurately than the Reynolds-averaged Navier-Stokes turbulence model.

In most large-eddy simulation (LES) applications to two-phase engine flows, the liquid-air interactions need to be accounted for as source terms in the respective governing equations. Accurate calculation of these source terms requires the relative velocity “seen” by liquid droplets as they move across the flow, which generally needs to be estimated using a turbulent dispersion model. Turbulent dispersion modeling in LES is very scarce in the literature. In most studies on engine spray flows, sub-grid scale (SGS) models for the turbulent dispersion still follow the same stochastic approach originally proposed for Reynolds-averaged Navier-Stokes (RANS). In this study, an SGS dispersion model is formulated in which the instantaneous gas velocity is decomposed into a deterministic part and a stochastic part. The deterministic part is reconstructed using the approximate deconvolution method (ADM), in which the large-scale flow can be readily calculated.

To meet stringent emissions regulations, filtration devices are often used in engine exhaust systems to reduce particulate mass (PM) and particulate number (PN). Diesel particulate filters (DPFs) are a well-established means of reducing PM from diesel engines to meet emissions regulations. New emissions regulations will most likely require a similar technology on gasoline engines with direct injection, gasoline particulate filters (GPFs). Due to differences in the exhaust and particulate characteristics, the design and operation of GPFs and DPFs differ. In a DPF filtration is dominated by the buildup of a soot cake. Whereas in a GPF, much of the soot is trapped inside the porous substrate, or filter wall, where deep-bed filtration is dominant. Thus, an accurate model describing the porous filtration properties of GPF substrates is desired. The pore filtration model (PFM) was developed to more accurately model the deep-bed filtration process that occurs in a GPF.

A swept-volume method of calculating the volume swept by the flame during each time step is developed and used to improve the calculation of fuel reaction rates. The improved reaction rates have been applied to the ignition model and coupled with the level set G-equation combustion model. In the ignition model, a single initial kernel is formed after which the kernel is convected by the gas flow and its growth rate is determined by the flame speed and thermal expansion due to the energy transfer from the electrical circuit. The predicted ignition kernel size was compared with the available experimental data and good agreements were achieved. Once the ignition kernel reaches a size when the fully turbulent flame is developed, the G-equation model is switched on to track the mean turbulent flame front propagation.

Modeling ignition kernel development in spark ignition engines is crucial to capturing the sources of cyclic variability, both with RANS and LES simulations. Appropriate kernel modeling must ensure that energy transfer from the electrodes to the gas phase has the correct timing, rate and locations, until the flame surface is large enough to be represented on the mesh by the G-Equation level-set method. However, in most kernel models, geometric details driving kernel growth are missing: either because it is described as Lagrangian particles, or because its development is simplified, i.e., down to multiple spherical flames. This paper covers the geometric aspects of kernel development, which makes up the core of a Triangulated Lagrangian Ignition Kernel model. One (or multiple, if it restrikes) spark channel is initialized as a one-dimensional Lagrangian particle thread.

In this paper, large eddy simulation (LES) coupled with two uncertainty quantification (UQ) methods, namely latin-hypercube sampling (LHS) and polynomial chaos expansion (PCE), have been used to quantify the effects of model parameters and spray boundary conditions on diesel and gasoline spray simulations. Evaporating, non-reacting spray data was used to compare penetration, mixture fraction and spray probability contour. Two different sets of four uncertain variables were used for diesel and gasoline sprays, respectively. UQ results showed good agreement between experiments and predictions. UQ statistics indicated that discharge coefficient has stronger impact on gasoline than diesel sprays, and spray cone angle is important for vapor penetration of both types of sprays. Additionally, examination of the gasoline spray characteristics showed that plume-to-plume interaction and nozzle dribble are important phenomena that need to be considered in high-fidelity gasoline spray simulations.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

Three time integration schemes and four finite volume interpolation schemes for the convection term in momentum equation were tested under turbulent planar gas jet and Sandia non-reacting vaporizing Spray-H cases. The three time integration schemes are the first-order Euler implicit scheme, the second-order backward scheme, and the second-order Crank-Nicolson scheme. The four spatial interpolation schemes are cubic central, linear central, upwind, and vanLeer schemes. Velocity magnitude contour, centerline and radial mean velocity and Reynolds stress profiles for the planar turbulent gas jet case, and fuel vapor contour and liquid and vapor penetrations for the Diesel spray case predicted by the different numerical schemes were compared. The sensitivity of the numerical schemes to mesh resolution was also investigated. The non-viscosity based dynamic structure subgrid model was used. The numerical tool used in this study was OpenFOAM.

This paper is part of a larger body of experimental and computational work devoted to studying the role of close-coupled post injections on soot reduction in a heavy-duty optical engine. It is a continuation of an earlier computational paper. The goals of the current work are to develop new CFD analysis tools and methods and apply them to gain a more in depth understanding of the different in-cylinder environments into which fuel from main- and post-injections are injected and to study how the in-cylinder flow, thermal and chemical fields are transformed between start of injection timings. The engine represented in this computational study is a single-cylinder, direct-injection, heavy-duty, low-swirl engine with optical components. It is based on the Cummins N14, has a cylindrical shaped piston bowl and an eight-hole injector that are both centered on the cylinder axis. The fuel used was n-heptane and the engine operating condition was light load at 1200 RPM.

Due to the new challenge of meeting number-based regulations for particulate matter (PM), a numerical and experimental study has been conducted to better understand particulate formation in engines fuelled with compressed natural gas. The study has been conducted on a Heavy-Duty, Euro VI, 4-cylinder, spark ignited engine, with multipoint sequential phased injection and stoichiometric combustion. For the experimental measurements two different instruments were used: a condensation particle counter (CPC) and a fast-response particle size spectrometer (DMS) the latter able also to provide a particle size distribution of the measured particles in the range from 5 to 1000 nm. Experimental measurements in both stationary and transient conditions were carried out. The data using the World Harmonized Transient Cycle (WHTC) were useful to detect which operating conditions lead to high numbers of particles. Then a further transient test was used for a more detailed and deeper analysis.

Reactivity Controlled Compression Ignition (RCCI) has been shown to be an attractive concept to achieve clean and high efficiency combustion. RCCI can be realized by applying two fuels with different reactivities, e.g., diesel and gasoline. This motivates the idea of using a single low reactivity fuel and direct injection (DI) of the same fuel blended with a small amount of cetane improver to achieve RCCI combustion. In the current study, numerical investigation was conducted to simulate RCCI and HCCI combustion and emissions with various fuels, including gasoline/diesel, iso-butanol/diesel and iso-butanol/iso-butanol+di-tert-butyl peroxide (DTBP) cetane improver. A reduced Primary Reference Fuel (PRF)-iso-butanol-DTBP mechanism was formulated and coupled with the KIVA computational fluid dynamic (CFD) code to predict the combustion and emissions of these fuels under different operating conditions in a heavy duty diesel engine.

A novel 2-zone combustion chamber concept (patent pending) was developed using multi-dimensional modeling. At minimum volume, an axial projection in the piston divides the volume into distinct zones joined by a communication channel. The projection provides a means to control the mixture formation and combustion phasing within each zone. The novel combustion system was applied to reactivity controlled compression ignition (RCCI) combustion in both light-duty and heavy-duty diesel engines. Results from the study of an 8.8 bar BMEP, 2600 RPM operating condition are presented for the light-duty engine. The results from the heavy-duty engine are at an 18.1 bar BMEP, 1200 RPM operating condition. The effect of several major design features were investigated including the volume split between the inner and outer combustion chamber volumes, the clearance (squish) height, and the top ring land (crevice) volume.

Control of the timing and magnitude of heat release is one of the biggest challenges for premixed compression ignition, especially when attempting to operate at high load. Single-fuel strategies such as partially premixed combustion (PPC) use direct injection of gasoline to stratify equivalence ratio and retard heat release, thereby reducing pressure rise rate and enabling high load operation. However, retarding the heat release also reduces the maximum work extraction, effectively creating a tradeoff between efficiency and noise. Dual-fuel strategies such as reactivity controlled compression ignition (RCCI) use premixed gasoline and direct injection of diesel to stratify both equivalence ratio and fuel reactivity, which allows for greater control over the timing and duration of heat release. This enables combustion phasing closer to top dead center (TDC), which is thermodynamically favorable.

Due to the upcoming regulations for particulate matter (PM) emissions from GDI engines, a computational fluid dynamic (CFD) modeling study to predict soot emissions (both mass and solid particle number) from gasoline direct injection (GDI) engines was undertaken to provide insights on how and why soot emissions are formed from GDI engines. In this way, better methods may be developed to control or reduce PM emissions from GDI engines. In this paper, the influence of engine operating parameters was examined for a side-mounted fuel injector configuration in a direct-injection spark-ignition (DISI) engine. The present models are able to reasonably predict the influences of the variables of interest compared to available experimental data or literature. For a late injection strategy, effects of the fuel composition, and spray cone angle were investigated with a single-hole injector.

In this work computational and experimental approaches are combined to characterize in-cylinder flow structures and local flow field properties during operation of the Sandia 1.9L light-duty optical Diesel engine. A full computational model of the single-cylinder research engine was used that considers the complete intake and exhaust runners and plenums, as well as the adjustable throttling devices used in the experiments to obtain different swirl ratios. The in-cylinder flow predictions were validated against an extensive set of planar PIV measurements at different vertical locations in the combustion chamber for different swirl ratio configurations. Principal Component Analysis was used to characterize precession, tilting and eccentricity, and regional averages of the in-cylinder turbulence properties in the squish region and the piston bowl.

The application of close-coupled post injections in diesel engines has been proven to be an effective in-cylinder strategy for soot reduction, without much fuel efficiency penalty. But due to the complexity of in-cylinder combustion, the soot reduction mechanism of post-injections is difficult to explain. Accordingly, a simulation study using a three dimensional computational fluid dynamics (CFD) model, coupled with the SpeedChem chemistry solver and a semi-detailed soot model, was carried out to investigate post-injection in a constant volume combustion chamber, which is more simple and controllable with respect to the boundary conditions than an engine. A 2-D axisymmetric mesh of radius 2 cm and height 5 cm was used to model the spray. Post-injection durations and initial oxygen concentrations were swept to study the efficacy of post-injection under different combustion conditions.

The SCR Filter simultaneously reduces NOx and Particle Matter (PM) in the exhaust and is considered an effective way to meet emission regulations. By combining the function of a Diesel Particulate Filtration (DPF) and a Selective Catalytic Reduction (SCR), the SCR Filter reduces the complexity and cost of aftertreatment systems in diesel vehicles. Moreover, it provides an effective reaction surface and potentially reduces backpressure by combining two devices into one. However, unlike traditional flow through type SCR, the deNOx reactions in the SCR Filter can be affected by the particulate filtration and regeneration process. Additionally, soot oxidation can be affected by the deNOx process. A 1-D kinetic model for integrated DPF and NH3-SCR system over Cu-zeolite catalysts was developed and validated with experimental data in previous work[1].

The present experimental engine efficiency study explores the effects of intake pressure and temperature, and premixed and global equivalence ratios on gross thermal efficiency (GTE) using the reactivity controlled compression ignition (RCCI) combustion strategy. Experiments were conducted in a heavy-duty single-cylinder engine at constant net load (IMEPn) of 8.45 bar, 1300 rev/min engine speed, with 0% EGR, and a 50% mass fraction burned combustion phasing (CA50) of 0.5°CA ATDC. The engine was port fueled with E85 for the low reactivity fuel and direct injected with 3.5% 2-ethylhexyl nitrate (EHN) doped into 91 anti-knock index (AKI) gasoline for the high-reactivity fuel. The resulting reactivity of the enhanced fuel corresponds to an AKI of approximately 56 and a cetane number of approximately 28. The engine was operated with a wide range of intake pressures and temperatures, and the ratio of low- to high-reactivity fuel was adjusted to maintain a fixed speed-phasing-load condition.

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as local, globally lean, low-temperature combustion strategies are setting the path towards a more efficient and environmentally sustainable use of energy resources in transportation. In this paper, we assessed the computational efficiency of a recently developed sparse analytical Jacobian chemistry solver, namely ‘SpeedCHEM’, that features both direct and Krylov-subspace solution methods for maximum efficiency for both small and large mechanism sizes. The code was coupled with a high-dimensional clustering algorithm for grouping homogeneous reactors into clusters with similar states and reactivities, to speed-up the chemical kinetics solution in multi-dimensional combustion simulations.