Search Results

Two turbulent combustion modeling approaches, which were large eddy simulations in conjunction with detailed kinetics (LES-CHEMKIN) and Reynolds Averaged Navier Stokes with detailed kinetics (RANS-CHEMKIN), were used to model two partially premixed engine conditions. The results were compared with average pressure and heat release data, as well as images of in-cylinder ignition chemiluminescence and OH radical distributions. Both LES-CHEMKIN and RANS-CHEMKIN match well with experimental average data. However, LES-CHEMKIN has advantages over RANS-CHEMKIN in predicting the details of location of ignition sites, temperature as well as OH radical distributions. Therefore, LES offers more realistic representations of the combustion process. As a further improvement aiming at saving computational cost and accounting for turbulence-chemistry interactions, a flamelet time scale (FTS) combustion model is coupled with CHEMKIN to predict the entire combustion process. In this new approach (i.e.

Fuel spray atomization and breakup processes within a direct-injection spark-ignition (DISI) engine and outside the engine were modeled using a modified KIVA-3V code with improved spray models. The structures of the predicted sprays were qualitatively compared with planar images. The considered sprays were created by a prototype pressure-swirl injector and the planar images were obtained by laser sheet imaging in an optical DISI engine. In the out-of-engine case, the spray was injected into atmospheric air, and was modeled in a two dimensional bomb. In the engine case, the injection started from 270° ATDC, and full 3-D computations in the same engine were performed. In both cases, two liquid injection pressure conditions were applied, that is, 3.40 MPa and 6.12 MPa. The model gives good prediction of the tip penetration, and external spray shape, but the internal structure prediction has relatively lower accuracy, especially near the spray axis.

This paper describes numerical simulations that compare the performance of two combustion CFD models against experimental data, and evaluates the effects of combustion and spray model constants on the predicted combustion and emissions under various operating conditions. The combustion models include a Characteristic Time Combustion (CTC) model and CHEMKIN with reduced chemistry models integrated in the KIVA-3Vr2 CFD code. The diesel spray process was modeled using an updated version of the KH-RT spray model that features a gas jet submodel to help reduce numerical grid dependencies, and the effects of both the spray and combustion model constants on combustion and emissions were evaluated. In addition, the performance of two soot models was compared, namely a two-step soot model, and a more detailed model that considers soot formation from PAH precursors.

In a recent experimental study the in-cylinder spatial distribution of mixture equivalence ratio was quantified under non-combusting conditions by planar laser-induced fluorescence (PLIF) of a fuel tracer (toluene). The measurements were made in a single-cylinder, direct-injection, light-duty diesel engine at conditions matched to an early-injection low-temperature combustion mode. A fuel amount corresponding to a low load (3.0 bar indicated mean effective pressure) operating condition was introduced with a single injection at -23.6° ATDC. The data were acquired during the mixture preparation period from near the start of injection (-22.5° ATDC) until the crank angle where the start of high-temperature heat release normally occurs (-5° ATDC). In the present study the measured in-cylinder images are compared with a fully resolved three-dimensional CFD model, namely KIVA3V-RANS simulations.

While Low Temperature Combustion (LTC) strategies such as Reactivity Controlled Compression Ignition (RCCI) exhibit high thermal efficiency and produce low NOx and soot emissions, low load operation is still a significant challenge due to high unburnt hydrocarbon (UHC) and carbon monoxide (CO) emissions, which occur as a result of poor combustion efficiencies at these operating points. Furthermore, the exhaust gas temperatures are insufficient to light-off the Diesel Oxidation Catalyst (DOC), thereby resulting in poor UHC and CO conversion efficiencies by the aftertreatment system. To achieve exhaust gas temperature values sufficient for DOC light-off, combustion can be appropriately phased by changing the ratio of gasoline to diesel in the cylinder, or by burning additional fuel injected during the expansion stroke through post-injection.

Three different approaches for modeling diesel engine combustion are compared against cylinder pressure, NOx emissions, high-speed soot luminosity imaging, and 2-color thermometry data from a heavy-duty DI diesel engine. A characteristic time combustion (KIVA-CTC) model, a representative interactive flamelet (KIVA-RIF) model, and direct integration using detailed chemistry (KIVA-CHEMKIN) were integrated into the same version of the KIVA-3v computer code. In this way, the computer code provides a common platform for comparing various combustion models. Five different engine operating strategies that are representative of several different combustion regimes were explored in the experiments and model simulations. Two of the strategies produce high-temperature combustion with different ignition delays, while the other three use dilution to achieve low-temperature combustion (LTC), with early, late, or multiple injections.

Multidimensional computations were made of spark-ignited premixed-charge combustion in a pancake-combustion-chamber engine with a centrally located spark plug and in two pent-roof-chamber engines, one with a central spark plug and the other with dual lateral spark plugs. A global combustion submodel was used that accounts for laminar kinetics and turbulent mixing effects. The predictions were compared with available measurements in the pancake-chamber engine over a range of loads, speeds, and equivalence ratios. In all cases the computed and measured cylinder pressures agreed well in trends and magnitudes (within 8%) for the entire duration of combustion. Fair agreements were also obtained between predicted and measured values of wall heat flux and emission index of nitric oxide. In the pent-roof-chamber engines the predicted maximum cylinder pressures also agreed well with measurements (within 12%) in cases with MBT (Minimum spark advance for Best Torque) or advanced spark timing.

The use of gasoline in a compression ignition engine has been a research focus lately due to the ability of gasoline to provide more premixing, resulting in controlled emissions of the nitrogen oxides [NOx] and particulate matter. The present study assesses the reactivity of 93 RON [87AKI] gasoline in a GM 1.9L 4-cylinder diesel engine, to extend the low load limit. A single injection strategy was used in available experiments where the injection timing was varied from −42 to −9 deg ATDC, with a step-size of 3 deg. The minimum fueling level was defined in the experiments such that the coefficient of variance [COV] of indicated mean effective pressure [IMEP] was less than 3%. The study revealed that injection at −27 deg ATDC allowed a minimum load of 2 bar BMEP. Also, advancement in the start of injection [SOI] timing in the experiments caused an earlier CA50, which became retarded with further advancement in SOI timing.

Many studies have demonstrated ability of low temperature combustion to yield low NOx and soot while maintaining diesel-like thermal efficiencies. Methods of achieving low temperature combustion are numerous and range from using high cetane number fuels, like diesel, with large amounts of exhaust gas recirculation, to completely premixing a high octane number fuel, like gasoline, and approaching an HCCI-like condition. Both of the aforementioned techniques have relatively short combustion duration that results in very a rapid rate of heat release, and hence very rapid rates of pressure rise. This has been one of the major challenges for premixed, low temperature combustion at mid and high load. Reactivity Controlled Compression Ignition (RCCI) has been introduced recently, which is a dual fuel partially premixed combustion concept.

The potential of low temperature combustion to yield low NOx and soot while maintaining diesel-like thermal efficiencies has been demonstrated through countless studies. Methods of achieving low temperature combustion are just as numerous and they range from using high cetane number fuels, like diesel, with large amounts of exhaust gas recirculation, to completely premixing a high octane number fuel, like gasoline, and approaching an HCCI-like condition. The potential of operating a heavy-duty compression ignition engine fueled with conventional gasoline in a partially premixed combustion mode to have high thermal efficiency and low emissions has been demonstrated in this study. The objective of this work was to optimize the engine using computational tools. The KIVA3V-CHEMKIN code, a multi-dimensional engine CFD model was coupled to a Nondominated Sorting Genetic Algorithm (NSGA II), which is a multi-objective genetic algorithm.

A modification of the computational fluid dynamics code KIVA-II is presented that allows computations to be made in complex engine geometries. An example application is given in which three versions of KIVA-II are run simultaneously. Each version considers a separate block of the computational domain, and the blocks exchange boundary condition information with each other at their common interfaces. The use of separate blocks permits the connectedness of the overall computational domain to change with time. The scavenging flow in the cylinder, transfer pipes (ports), and exhaust pipe of a ported two-stroke engine with a moving piston was modeled in this way. Results are presented for three engine designs that differ only in the angle of their boost ports. The calculated flow fields and the resulting fuel distributions are shown to be markedly different with the different geometries.

The present work proposes a methodology for diesel engine development using scaling laws and computational optimization with multi-dimensional CFD tools. A previously optimized 450cc HSDI diesel engine was down-scaled to 400cc size using recently developed scaling laws. The scaling laws were validated by comparing the performance of these two engines, including pressure, HRR, peak and averaged temperature, and pollutant emissions. A novel optimization methodology, which is able to simultaneously optimize multiple operating conditions, was proposed. The method is based on multi-objective genetic algorithms, and was coupled with the KIVA3V Release 2 code to further optimize the down-scaled diesel engine. An adaptive multi-grid chemistry model was used in the KIVA3V code to reduce the computational cost of the optimization. The computations were conducted using high-throughput computing with the CONDOR system.

A new search technique, called Non-Gradient Step-Controlled algorithm (NGSC), is presented. The NGSC was applied independently from pre-selected starting points and as a supplement to a Genetic Algorithm (GA) to optimize a HSDI diesel engine using split injection strategies. It is shown that the NGSC handles well the challenges of a complex response surface and factor high-dimensionality, which demonstrates its capability as an efficient and accurate tool to seek “local” convergence on complex surfaces. By directly tracking the change of a merit function, the NGSC places no requirement on response surface continuity / differentiability, and hence is more robust than gradient-dependent search techniques. The directional search mechanism takes factor interactions into consideration, and search step size control is adopted to facilitate search efficiency.

In the present study a reduced chemical reaction mechanism for biodiesel surrogate fuel was developed and validated for multi-dimensional engine combustion simulations. An existing detailed methyl butanoate mechanism that contained 264 species and 1219 reactions was chosen to represent the oxygenated portion of the fuel. The reduction process included flux analysis, ignition sensitivity analysis, and optimization of reaction rate constants under constant volume conditions. The current reduced mechanism consists of 41 species and 150 reactions and gives predictions in excellent agreement with those of the comprehensive mechanism. In order to validate the mechanism under biodiesel-fueled engine conditions, it was combined with another skeletal mechanism for n-heptane oxidation. This combined reaction mechanism can be used to adjust the energy content of the fuel, and account for diesel/biodiesel blend engine simulations.

A reduced chemical reaction mechanism is developed and validated in the present study for multi-dimensional diesel HCCI engine combustion simulations. The motivation for the development of the reduced mechanism is to enhance the computational efficiency of engine stimulations. The new reduced mechanism was generated starting from an existing n-heptane mechanism (40 species and 165 reactions). The procedure of generating the reduced mechanism included: using SENKIN to produce the ignition delay data and solution files, using XSENKPLOT to analyze the base mechanism and to identify important reactions and species, eliminating unimportant species and reactions, formulating the new reduced mechanism, using the new mechanism to generate ignition delay data, and finally adjusting kinetic constants in the new mechanism to improve ignition delay and engine combustion predictions to account for diesel fuel cetane number and composition effects.

A, three-dimensional CFD code, based on the KIVA code, is used to explore alternatives to conventional DI diesel engine designs for reducing NOx and soot emissions without sacrificing engine performance. The effects of combustion chamber design and fuel spray orientation are investigated using a new proposed GAMMA engine concept, and two new multiple injector combustion system (MICS) designs which utilize multiple injectors to increase gas motion and enhance fuel/air mixing in the combustion chamber. From these computational studies, it is found that both soot and nitrous oxide emissions can be significantly reduced without the need for more conventional emission control strategies such as EGR or ultra high injection pressure. The results suggest that CFD models can be a useful tool not only for understanding combustion and emissions production, but also for investigating new design concepts.

In previous publications, Singh et al. [1, 2] have shown that direct integration of CFD with a detailed chemistry auto-ignition model (KIVA-CHEMKIN) performs reasonably well for predicting combustion, emissions, and flame structure for stratified diesel engine operation. In this publication, it is shown that the same model fails to predict combustion for partially premixed dual-fuel engines. In general, models that account for chemistry alone, greatly under-predict cylinder pressure. This is shown to be due to the inability of such models to simulate a propagating flame, which is the major source of heat release in partially premixed dual-fuel engines, under certain operating conditions. To extend the range of the existing model, a level-set-based, hybrid, auto-ignition/flame-propagation (KIVA-CHEMKIN-G) model is proposed, validated and applied for both stratified diesel engine and partially premixed dual-fuel engine operation.

A universal engine combustion model based on the level-set approach was developed in this study. It was first used to model combustion in Spark Ignition (SI) and Direct Injection Spark Ignition (DISI) engines when combined with the Discrete Particle Spark Ignition model, in which the ignition kernel is represented by particles. Once the flame kernel grows to a size that the turbulent flame is fully developed, the G-equation model is used to track the subsequent propagation of the turbulent flame. When combined with a characteristic time combustion model, the triple flame structure that is found in DISI engine combustion was successfully modeled. The model was also applied to simulate diesel combustion where the diffusion combustion regime is dominant. In this case, the ignition was modeled using the Shell auto-ignition model. Satisfactory agreement with features of the conceptual diesel combustion model of Dec [1997] was found.

A new ignition and combustion model has been developed and tested for use in premixed spark-ignition engines. The ignition model is referred to as the Discrete Particle Ignition Kernel (DPIK) model, and it uses Lagrangian markers to track the flame-front growth. The model includes the effects of electrode heat transfer on the early flame kernel growth process, and it is used in conjunction with a characteristic-time-scale combustion model once the ignition kernel has grown to a size where the effects of turbulence on the flame must be considered. A new term which accounts for the effect of air-fuel ratio, was added to the combustion model for modeling combustion in very lean and very rich mixtures. The flame kernel size predicted by the DPIK model was compared with measurements of Maly and Vogel. Furthermore, predictions of the electrode heat transfer were compared with data of Kravchik and Heywood. In both comparisons the model predictions were in good agreement with the experiments.

The development of a new Nitric Oxide (NOx) reaction mechanism has been conducted by adding species, including hydrogen cyanide (HCN) and the CH radical to a reduced chemistry diesel combustion model. The additional chemical reactions were added to the ERC's reduced 12-step NOx mechanism, which consists of N, NO, N2O, and NO2. The new NOx mechanism was implemented into the KIVA/ERC-CHEMKIN code and was found to be able to predict the experimentally observed trend that the amount of engine-out NOx decreases as engine load is increased, which is not reproduced by the current reduced NOx mechanism. HCN and CH were found to be species that bridge CxHy products and N radicals via the reaction CH+N2→HCN+N under high equivalence ratio conditions, and Zeldovich NO formation is suppressed by the formation of HCN, a species in the Fenimore NO formation pathway. The additional species and reactions were also found to influence the prediction of engine-out soot emissions.