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In the present paper optimization tools are used to recommend low-emission engine combustion chamber designs, spray targeting and swirl ratio levels for a heavy-duty diesel engine operated at high-load. The study identifies aspects of the combustion and pollution formation that are affected by mixing processes, and offers guidance for better matching of the piston geometry with the spray plume geometry for enhanced mixing. By coupling a GA (genetic algorithm) with the KIVA-CFD code, and also by utilizing an automated grid generation technique, multi-objective optimizations with goals of low emissions and fuel economy were achieved. Three different multi-objective genetic algorithms including a Micro-Genetic Algorithm (μGA), a Nondominated Sorting Genetic Algorithm II (NSGA II) and an Adaptive Range Multi-Objective Genetic Algorithm (ARMOGA) were compared for conducting the optimization under the same conditions.

In the present work the three-dimensional KIVA CFD code was used to simulate the combustion process in a HSDI diesel engine. State-of-the-art models, including the KH-RT spray breakup model, the RNG k-ε turbulence model, and a n-heptane reduced chemistry including reduced GRI NOx mechanism were used. The performances of two combustion models, KIVA-CHEMKIN and GAMUT (KIVA-CHEMKIN-G), coupled with 2-step and multi-step phenomenological soot models were compared. The numerical results were compared with available experimental data obtained from an optically accessible HSDI engine and good agreement was obtained. To assess the effects of the in-cylinder flow field on combustion and emissions, off-centered swirl flows were also considered. In these studies, the swirl center was initialized at different positions in the chamber for different cases to simulate the effects of different intake flow arrangements.

A computational study using multi-dimensional CFD modeling was performed to investigate the effects of physical properties on diesel engine combustion characteristics with bio-diesel fuels. Properties of typical bio-diesel fuels that were either calculated or measured are used in the study and the simulation results are compared with those of conventional diesel fuels. The sensitivity of the computational results to individual physical properties is also investigated, and the results provide information about the desirable characteristics of the blended fuels. The properties considered in the study include liquid density, vapor pressure, surface tension, liquid viscosity, liquid thermal conductivity, liquid specific heat, latent heat, vapor specific heat, vapor diffusion coefficient, vapor viscosity and vapor thermal conductivity. The results show significant effects of the fuel physical properties on ignition delay and burning rates at various engine operating conditions.

In-cylinder flow and combustion processes simulated with the standard k-ε turbulence model and with an alternative model-employing a non-linear, quadratic equation for the turbulent stresses-are contrasted for both motored and fired engine operation at two loads. For motored operation, the differences observed in the predictions of mean flow development are small and do not emerge until expansion. Larger differences are found in the spatial distribution and magnitude of turbulent kinetic energy. The non-linear model generally predicts lower energy levels and larger turbulent time scales. With fuel injection and combustion, significant differences in flow structure and in the spatial distribution of soot are predicted by the two models. The models also predict considerably different combustion efficiencies and NOx emissions.

Low-temperature combustion (LTC) strategies for diesel engines are of increasing interest because of their potential to significantly reduce particulate matter (PM) and nitrogen oxide (NOx) emissions. LTC with late fuel injection further offers the benefit of combustion phasing control because ignition is closely coupled to the fuel injection event. But with a short ignition-delay, fuel jet mixing processes must be rapid to achieve adequate premixing before ignition. In the current study, mixing and pollutant formation of late-injection LTC are studied in a single-cylinder, direct-injection, optically accessible heavy-duty diesel engine using three laser-based imaging diagnostics. Simultaneous planar laser-induced fluorescence of the hydroxyl radical (OH) and combined formaldehyde (H2CO) and polycyclic aromatic hydrocarbons (PAH) are compared with vapor-fuel concentration measurements from a non-combusting condition.

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.

A transport equation residual model incorporating refined G-equation and detailed chemical kinetics combustion models has been developed and implemented in the ERC KIVA-3V release2 code for Gasoline Direct Injection (GDI) engine simulations for better predictions of flame propagation. In the transport equation residual model a fictitious species concept is introduced to account for the residual gases in the cylinder, which have a great effect on the laminar flame speed. The residual gases include CO2, H2O and N2 remaining from the previous engine cycle or introduced using EGR. This pseudo species is described by a transport equation. The transport equation residual model differentiates between CO2 and H2O from the previous engine cycle or EGR and that which is from the combustion products of the current engine cycle.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline (termed GDICI for Gasoline Direct-Injection Compression Ignition) in the low temperature combustion (LTC) regime is presented. As an aid to plan engine experiments at full load (16 bar IMEP, 2500 rev/min), exploration of operating conditions was first performed numerically employing a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion. Operation ranges of a light-duty diesel engine operating with GDICI combustion with constraints of combustion efficiency, noise level (pressure rise rate) and emissions were identified as functions of injection timings, exhaust gas recirculation rate and the fuel split ratio of double-pulse injections.

Several diffusion combustion scaling models were experimentally tested in two geometrically similar single-cylinder diesel engines with a bore diameter ratio of 1.7. Assuming that the engines have the same in-cylinder thermodynamic conditions and equivalence ratio, the combustion models primarily change the fuel injection pressure and engine speed in order to attain similar performance and emissions. The models tested include an extended scaling model, which scales diffusion flame lift-off length and jet spray penetration; a simple scaling model, which only scales spray penetration at equal mean piston speed; and a same speed scaling model, which holds crankshaft rotational velocity constant while also scaling spray penetration. Successfully scaling diffusion combustion proved difficult to accomplish because of apparent differences that remained in the fuel-air mixing and heat transfer processes.

Single-cylinder engine experiments were used to investigate a fuel reactivity controlled compression ignition (RCCI) concept in both light- and heavy-duty engines and comparisons were made between the two engine classes. It was found that with only small changes in the injection parameters, the combustion characteristics of the heavy-duty engine could be adequately reproduced in the light-duty engine. Comparisons of the emissions and performance showed that both engines can simultaneously achieve NOx below 0.05 g/kW-hr, soot below 0.01 g/kW-hr, ringing intensity below 4 MW/m2, and gross indicated efficiencies above 50 per cent. However, it was found that the peak gross indicated efficiency of the baseline light-duty engine was approximately 7 per cent lower than the heavy-duty engine. The energy balances of the two engines were compared and it was found that the largest factor contributing to the lower efficiency of the light-duty engine was increased heat transfer losses.

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.

Reactivity Controlled Compression Ignition combustion (RCCI) has been demonstrated at mid to high loads [1, 2, 3, 4, 5, 6] as a method to operate an internal combustion engine that produces low NOx and low PM emissions with high thermal efficiency. The current study investigates RCCI engine operation at loads of 2 and 4.5 bar gross IMEP at engine speeds between 800 and 1700 rev/min. This load range was selected to cover the range from the previous work of 6 bar gIMEP down to an off-idle load at 2 bar. The fueling strategy for the low load investigation consisted of in-cylinder fuel blending using port-fuel-injection of gasoline and early cycle, direct-injection of either diesel fuel or gasoline doped with 3.5% by volume 2-EHN (2-ethylhexyl nitrate). At these loads, engine operating conditions such as inlet air temperature, port fuel percentage, and engine speed were varied to investigate their effect on combustion.

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.

A multi-component fuel model is used to represent gasoline in computational fluid dynamics (CFD) simulations of a dual-fuel engine that combines premixed gasoline injection with diesel direct injection. The simulations employ detailed-kinetics mechanisms for both the gasoline and diesel surrogate fuels, through use of an advanced and efficient chemistry solver. The objective of this work is to elucidate kinetics effects of dual-fuel usage in Reactivity Controlled Compression Ignition (RCCI) combustion. The model is applied to simulate recent experiments on highly efficient RCCI engines. These engine experiments used a dual-fuel RCCI strategy with port-fuel-injection of gasoline and early-cycle, multiple injections of diesel fuel with a conventional diesel injector. The experiments showed that the US 2010 heavy-duty NO and soot emissions regulations were easily met without aftertreatment, while achieving greater than 50% net indicated thermal efficiency.

Biodiesel-fueled engine simulations were performed using the KIVA3v-Release 2 code coupled with Chemkin-II for detailed chemistry. The model incorporates a reduced mechanism that was created from a methyl decanoate/methyl-9-decenoate mechanism developed at the Lawrence Livermore National Laboratory. A combination of Directed Relation Graph, chemical lumping, and limited reaction rate tuning was used to reduce the detailed mechanism from 3299 species and 10806 reactions to 77 species and 209 reactions. The mechanism was validated against its detailed counterpart and predicted accurate ignition delay times over a range of relevant operating conditions. The mechanism was then combined with the ERC PRF mechanism to include n-heptane as an additional fuel component. The biodiesel mechanism was applied in KIVA using a discrete multi-component model with accurate physical properties for the five common components of real biodiesel fuel.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline injected using a triple-pulse strategy in the low temperature combustion (LTC) regime is presented. This work aims to extend the operation ranges for a light-duty diesel engine, operating on gasoline, that have been identified in previous work via extended controllability of the injection process. The single-cylinder engine (SCE) was operated at full load (16 bar IMEP, 2500 rev/min) and computational simulations of the in-cylinder processes were performed using a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion chosen to match ignition characteristics of the gasoline fuel used for the SCE experiments.

Many recent studies have shown that the Reactivity Controlled Compression Ignition (RCCI) combustion strategy can achieve high efficiency with low emissions. However, it has also been revealed that RCCI combustion is difficult at high loads due to its premixed nature. To operate at moderate to high loads with gasoline/diesel dual fuel, high amounts of EGR or an ultra low compression ratio have shown to be required. Considering that both of these approaches inherently lower thermodynamic efficiency, in this study natural gas was utilized as a replacement for gasoline as the low-reactivity fuel. Due to the lower reactivity (i.e., higher octane number) of natural gas compared to gasoline, it was hypothesized to be a better fuel for RCCI combustion, in which a large reactivity gradient between the two fuels is beneficial in controlling the maximum pressure rise rate.

Manufacturers of heavy-duty diesel engines are facing increasingly stringent, emission standards. These standards have motivated new research efforts towards improving the performance of diesel engines. The objective of the present program is to develop a comprehensive analytical model of the diesel combustion process that can be used to explore the influence of design changes. This will enable industry to predict the effect of these changes on engine performance and emissions. A major benefit of the successful implementation of such models is that engine development time and costs would be reduced through their use. The computer model is based on the three-dimensional KIVA-II code, with state-of-the-art submodels for spray atomization, drop breakup / coalescence, multi-component fuel vaporization, spray/wall interaction, ignition and combustion, wall heat transfer, unburned HC and NOx formation, and soot and radiation.

Engine experiments and multi-dimensional modeling were used to explore the effects of isobutanol as both the high and low reactivity fuels in Reactivity Controlled Compression Ignition (RCCI) Combustion. Three fuel combinations were examined; EEE/diesel, isobutanol/diesel, and isobutanol/isobutanol+DTBP (di-tert butyl peroxide). In order to assess the relative performance of the fuel combinations of interest under RCCI operation, the engine was operated under conditions representative of typical low temperature combustion (LTC). A net load of 6 bar indicated mean effective pressure (IMEP) was chosen because it provides a wide operable range of equivalence ratios and combustion phasings without excessively high peak pressure rise rates (PPRR). The engine was operated under various intake pressures with global equivalence ratios from 0.28-0.36, and various combustion phasings (defined by 50% mass fraction burned-CA50) from about 1.5 to about 10 deg after top dead center (ATDC).

Real transportation fuels, such as gasoline and diesel, are mixtures of thousands of different hydrocarbons. For multidimensional engine applications, numerical simulations of combustion of real fuels with all of the hydrocarbon species included exceeds present computational capabilities. Consequently, surrogate fuel models are normally utilized. A good surrogate fuel model should approximate the essential physical and chemical properties of the real fuel. In this work, we present a novel methodology for the formulation of surrogate fuel models based on local optimization and sensitivity analysis technologies. Within the proposed approach, several important fuel properties are considered. Under the physical properties, we focus on volatility, density, lower heating value (LHV), and viscosity, while the chemical properties relate to the chemical composition, hydrogen to carbon (H/C) ratio, and ignition behavior. An error tolerance is assigned to each property for convergence checking.