Search Results

Nitric Oxide (NO) can significantly influence the autoignition reactivity and this can affect knock limits in conventional stoichiometric SI engines. Previous studies also revealed that the role of NO changes with fuel type. Fuels with high RON (Research Octane Number) and high Octane Sensitivity (S = RON - MON (Motor Octane Number)) exhibited monotonically retarding knock-limited combustion phasing (KL-CA50) with increasing NO. In contrast, for a high-RON, low-S fuel, the addition of NO initially resulted in a strongly retarded KL-CA50 but beyond the certain amount of NO, KL-CA50 advanced again. The current study focuses on same high-RON, low-S Alkylate fuel to better understand the mechanisms responsible for the reversal in the effect of NO on KL-CA50 beyond a certain amount of NO.

Lawrence Livermore National Laboratory (LLNL) has conducted a series of scaled wind tunnel tests to investigate the aerodynamic benefits of heavy vehicle platooning and the availability of cooling air for trailing vehicles on two- and three-vehicle platoons. To measure the aerodynamic drag, scale models are mounted onto a LLNL designed splitter plate by means of a low-friction linear bearing and a load cell located within each model trailer. In addition to drag, pressure measurements are made with a pitot probe positioned at the center of each model radiator grill. Particle Image Velocimetry (PIV) and Infrared Thermography (IRT) measurements are used to map the three-dimensional velocity field and flow structures around the vehicles.

Simulation of chemical kinetic processes in combustion engine environments has become ubiquitous towards the understanding of combustion phenomenology, the evaluation of controlling parameters, and the design of configurations and/or control strategies. Such calculations are not free from error however, and the interpretation of simulation results must be considered within the context of uncertainties in the chemical kinetic model. Uncertainties arise due to structural issues (e.g., included/missing reaction pathways), as well as inaccurate descriptions of kinetic rate parameters and thermochemistry. In fundamental apparatuses like rapid compression machines and shock tubes, computed constant-volume ignition delay times for simple, single-component fuels can have variations on the order of factors of 2-4.

In this paper, a framework for estimating experimental measurement uncertainties for a Homogenous Charge Compression Ignition (HCCI)/Low-Temperature Gasoline Combustion (LTGC) engine testing facility is presented. Detailed uncertainty quantification is first carried out for the measurement of the in-cylinder pressure, whose variations during the cycle provide most of the information for performance evaluation. Standard uncertainties of other measured quantities, such as the engine geometry and speed, the air and fuel flow rate and the intake/exhaust dry molar fractions are also estimated. Propagating those uncertainties using a Monte Carlo simulation and Bayesian inference methods then allows for estimation of uncertainties of the mass-average temperature and composition at IVC and throughout the cycle; and also of the engine performances such as gross Integrated Mean Effective Pressure, Heat Release and Ringing Intensity.

The combustion behavior of conventional gasoline has been numerically investigated by means of detailed chemical-kinetic modeling simulations, with particular emphasis on analyzing the chemistry of the intermediate temperature heat release (ITHR). Previous experimental work on highly boosted (up to 325 kPa absolute) HCCI combustion of gasoline (SAE 2020-01-1086) showed a steady increase in the charge temperature up to the point of hot ignition, even for conditions where the ignition point was retarded well after top dead center (TDC). Thus, sufficient energy was being released by early pre-ignition reactions resulting in temperature rise during the early part of the expansion stroke This behavior is associated with a slow pre-ignition heat release (ITHR), which is critical to keep the engine from misfiring at the very late combustion phasings required to prevent knock at high-load boosted conditions.

Detailed chemical kinetics, although preferred due to increased accuracy, can significantly slow down CFD combustion simulations. Chemistry solutions are typically the most computationally costly step in engine simulations. The calculation time can be significantly accelerated using a multi-zone combustion model. The multi-zone model is integrated into the CONVERGE CFD code. At each time-step, the CFD cells are grouped into zones based on the cell temperature and equivalence ratio. The chemistry solver is invoked only on each zone. The zonal temperature and mass fractions are remapped onto the CFD cells, such that the temperature and composition non-uniformities are preserved. Two remapping techniques published in the literature are compared for their relative performance. The accuracy and speed-up of the multi-zone model is improved by using variable bin sizes at different temperature and equivalence ratios.

Isopentanol is an advanced biofuel that can be produced by micro-organisms through genetically engineered metabolic pathways. Compared to the more frequently studied ethanol, isopentanol's molecular structure has a longer carbon chain and includes a methyl branch. Its volumetric energy density is over 30% higher than ethanol, and it is less hygroscopic. Some fundamental combustion properties of isopentanol in an HCCI engine have been characterized in a recent study by Yang and Dec (SAE 2010-01-2164). They found that for typical HCCI operating conditions, isopentanol lacks two-stage ignition properties, yet it has a higher HCCI reactivity than gasoline. The amount of intermediate temperature heat release (ITHR) is an important fuel property, and having sufficient ITHR is critical for HCCI operation without knock at high loads using intake-pressure boosting. Isopentanol shows considerable ITHR, and the amount of ITHR increases with boost, similar to gasoline.

Three integration strategies are developed and tested for the stiff, ordinary differential equation (ODE) integrators used to solve the fully coupled multizone chemical kinetics model. Two of the strategies tested are found to provide more than an order of magnitude of improvement over the original, basic level of usage for the stiff ODE solver. One of the faster strategies uses a decoupled, or segregated, multizone model to generate an approximate Jacobian. This approach yields a 35-fold reduction in the computational cost for a 20 zone model. Using the same approximate Jacobian as a preconditioner for an iterative Krylov-type linear system solver, the second improved strategy achieves a 75-fold reduction in the computational cost for a 20 zone model. The faster strategies achieve their cost savings with no significant loss of accuracy.

Now more than ever, the increasing strictness of environmental regulation and the stronger need of higher efficiency standards are pushing for the development of cleaner and energy-efficient powertrains. HCCI engines are suitable candidates to achieve these objectives. Understanding the autoignition process and how it is affected by operating conditions is central to the development of these engines. In addition to experiments, detailed kinetic modeling represents a very effective tool for gaining deeper insight into the fundamentals of HCCI autoignition and combustion. Indeed, modeling activities are today widely used in engine design, allowing a significant reduction in prototype development costs and providing a valuable support to the improvement of control strategies.

Detailed exhaust speciation measurements were made on an HCCI engine fueled with iso-octane over a range of fueling rates, and over a range of fuel-stratification levels. Fully premixed fueling was used for the fueling sweep. This sweep extended from a fuel/air equivalence ratio (ϕ) of 0.28, which is sufficiently high to achieve a combustion efficiency of 96%, down to a below-idle fueling rate of ϕ = 0.08, with a combustion efficiency of only 55%. The stratification sweep was conducted at an idle fueling rate, using an 8-hole GDI injector to vary stratification from well-mixed conditions for an early start of injection (SOI) (40°CA) to highly stratified conditions for an SOI well up the compression stroke (325°CA, 35°bTDC-compression). The engine speed was 1200 rpm. At each operating condition, exhaust samples were collected and analyzed by GC-FID for the C1 and C2 hydrocarbon (HC) species and by GC-MS for all other species except formaldehyde and acetaldehyde.

One way to increase the load range in an HCCI engine is to increase boost pressure. In this modeling study, we investigate the effect of increased boost pressure on the fuel chemistry in an HCCI engine. Computed results of HCCI combustion are compared to experimental results in a HCCI engine. We examine the influence of boost pressure using a number of different detailed chemical kinetic models - representing both pure compounds (methylcyclohexane, cyclohexane, iso-octane and n-heptane) and multi-component models (primary reference fuel model and gasoline surrogate fuel model). We examine how the model predictions are altered by increased fueling, as well as reaction rate variation, and the inclusion of residuals in our calculations. In this study, we probe the low temperature chemistry (LTC) region and examine the chemistry responsible for the low-temperature heat release (LTHR) for wide ranges of intake boost pressure.

This paper investigates flow and combustion in a full-cycle simulation of a four-stroke, three-valve HCCI engine by visualizing the flow with pathlines. Pathlines trace massless particles in a transient flow field. In addition to visualization, pathlines are used here to trace the history, or evolution, of flow fields and species. In this study evolution is followed from the intake port through combustion. Pathline analysis follows packets of intake charge in time and space from induction through combustion. The local scalar fields traversed by the individual packets in terms of velocity magnitude, turbulence, species concentration and temperatures are extracted from the simulation results. The results show how the intake event establishes local chemical and thermal environments in-cylinder and how the species respond (chemically react) to the local field.

Multi-zone CFD simulations with detailed kinetics were used to model iso-octane HCCI experiments performed on a single-cylinder research engine. The modeling goals were to validate the method (multi-zone combustion modeling) and the reaction mechanism (LLNL 857 species iso-octane) by comparing model results to detailed exhaust speciation data, which was obtained with gas chromatography. The model is compared to experiments run at 1200 RPM and 1.35 bar boost pressure over an equivalence ratio range from 0.08 to 0.28. Fuel was introduced far upstream to ensure fuel and air homogeneity prior to entering the 13.8:1 compression ratio, shallow-bowl combustion chamber of this 4-stroke engine. The CFD grid incorporated a very detailed representation of the crevices, including the top-land ring crevice and head-gasket crevice. The ring crevice is resolved all the way into the ring pocket volume. The detailed grid was required to capture regions where emission species are formed and retained.

The ignition delay times of toluene-oxygen-argon mixtures with fuel equivalence ratios from 0.5 to 1.5 and concentrations of toluene from 0.1 to 2.0% were measured behind reflected shock waves for temperatures 1270 to 1755 K and at a pressure of 2.4 ± 0.7 atm. A detailed chemical kinetic model has been developed on the basis of a kinetic mechanism proposed by Pitz et al. [1] to reproduce our experimental results as well as some literature data obtained in other shock tubes at pressures from 1.1 to 50 atm. It is found that the present chemical kinetic model could give better agreement on the pressure dependence of the ignition delay times than the previously proposed kinetic models.

To facilitate the growing interest in hydrogen combustion for internal combustion engines, computer models are being developed to simulate gaseous fuel injection, air entrainment and the ensuing combustion. This paper introduces a new method for modeling the injection and air entrainment processes for gaseous fuels. Modeling combustion is not covered in this paper. The injection model uses a gaseous sphere injection methodology, similar to liquid droplet injection techniques used for liquid fuel injection. In this paper, the model concept is introduced and model results are compared with correctly- and under-expanded experimental data.

We have developed an artificial neural network (ANN) based combustion model and have integrated it into a fluid mechanics code (KIVA3V) to produce a new analysis tool (titled KIVA3V-ANN) that can yield accurate HCCI predictions at very low computational cost. The neural network predicts ignition delay as a function of operating parameters (temperature, pressure, equivalence ratio and residual gas fraction). KIVA3V-ANN keeps track of the time history of the ignition delay during the engine cycle to evaluate the ignition integral and predict ignition for each computational cell. After a cell ignites, chemistry becomes active, and a two-step chemical kinetic mechanism predicts composition and heat generation in the ignited cells. KIVA3V-ANN has been validated by comparison with isooctane HCCI experiments in two different engines.

Homogeneous Charge Compression Ignition (HCCI) engines are currently of great interest as a future alternative to Diesel and Spark Ignition engines because of HCCI's potential to achieve high efficiency with very low NOx emissions. However, significant technical barriers remain to practical implementation of HCCI engines: difficult-to-control combustion, low power density, rapid pressure rise, and high hydrocarbon and carbon monoxide emissions. To overcome some of these barriers, operational strategies that involve relaxing the constraint of truly “homogeneous” HCCI combustion have been studied. The phrase “Premixed Charge Compression Ignition” or “PCCI” combustion can be used to describe this class of combustion processes, in which combustion occurs similarly to HCCI engines as a non-mixing controlled, chemical kinetics dominated, auto-ignition process, but the fuel, air, and residual gas mixture need not be homogeneous.

Gasoline consists of many different classes of hydrocarbons, such as paraffins, olefins, aromatics, and cycloalkanes. In this study, a surrogate gasoline reaction mechanism is developed, and it has one representative fuel constituent from each of these classes. These selected constituents are iso-octane, n-heptane, 1-pentene, toluene, and methyl-cyclohexane. The mechanism was developed in a step-wise fashion, adding submechanisms to treat each fuel component. Reactions important for low temperature oxidation (<1000K) and cross-reactions among different fuels are incorporated into the mechanism. The mechanism consists of 1328 species and 5835 reactions. A single-zone engine model is used to evaluate how well the mechanism captures autoignition behavior for conditions corresponding to homogeneous charge compression ignition (HCCI) engine operation.

This paper illustrates the applicability of a sequential fluid mechanics, multi-zone chemical kinetics model to analyze HCCI experimental data for two combustion chamber geometries with different levels of turbulence: a low turbulence disc geometry (flat top piston), and a high turbulence square geometry (piston with a square bowl). The model uses a fluid mechanics code to determine temperature histories in the engine as a function of crank angle. These temperature histories are then fed into a chemical kinetic solver, which determines combustion characteristics for a relatively small number of zones (40). The model makes the assumption that there is no direct linking between turbulence and combustion. The multi-zone model yields good results for both the disc and the square geometries. The model makes good predictions of pressure traces and heat release rates.

We have developed a model of the diesel fuel injection process for application to analysis of low temperature non-sooting combustion. The model uses a simplified mixing correlation and detailed chemical kinetics to analyze a parcel of fuel as it moves along the fuel jet, from injection to evaporation and ignition. The model predicts chemical composition and soot precursors, and is applied at conditions that result in low temperature non-sooting combustion. Production of soot precursors is the first step toward production of soot, and modeling precursor production is expected to give insight into the overall evolution of soot inside the engine. The results of the analysis show that the model has been successful in describing many of the observed characteristics of low temperature combustion.