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Carbon-neutral (CN) fuels will be part of the solution to reducing global warming effects of the transportation sector, along with electrification. CN fuels such as hydrogen, ammonia, biofuels, and e-fuels can play a primary role in some segments (aviation, shipping, heavy-duty road vehicles) and a secondary role in others (light-duty road vehicles). The composition and properties of these fuels vary substantially from existing fossil fuels. Fuel effects on performance and emissions are complex, especially when these fuels are blended with fossil fuels. Predictively modeling the combustion of these fuels in engine and combustor CFD simulations requires accurate representation of the fuel blends. We discuss a methodology for matching the targeted fuel properties of specific CN fuels, using a blend of surrogate fuel components, to form a fuel model that can accurately capture fuel effects in an engine simulation.

Accurate modeling of the characteristics of diesel-engine combustion leads to more efficient design. Accurate modeling in turn depends on correctly capturing spray dynamics, turbulence, and fuel chemistry. This work presents a computational fluid dynamics (CFD) investigation of a well characterized small-bore direct injection diesel engine at Sandia National Laboratories’ Combustion Research Facility. The engine has been studied for two piston-bowls geometries and various injection timings. Simulation of these conditions test the predictive capabilities of our approach to diesel engine modeling using Ansys Forte. An experimental database covering a wide range of operating conditions is provided by the Engine Combustion Network for this engine, which is used to validate our modeling approach. Automatic and solution-adaptive meshing is used, and the recommended settings are discussed.

Accurately predicting the evolution of soot mass and soot particle numbers under engine conditions is critical to advanced engine design. A detailed soot-chemistry model that can capture soot under gasoline and diesel conditions without tuning is necessary for such predictions. Building confidence in the predictive usage of the chemistry in engine simulations requires validating the soot kinetics over a wide range of operating conditions and fuels, using data from different experimental techniques, and using sources from laboratory flames to engines. This validation study focuses on a soot-chemistry model that considers multiple nucleation, growth, and oxidation reaction pathways. It involves 14 gas-phase precursors and considers the effect of different soot-particle surface sites.

Flash boiling occurs in sprays when the ambient gas pressure is lower than the saturation pressure of the injected fuel. In the present work, a numerical study was conducted to investigate solid-cone spray behaviors under various flash-boiling conditions. A new spray cone angle correlation that is a function of injection parameters was developed and used for spray initialization at the nozzle exit to capture plume interactions and the global spray shape. The spray-breakup regime control was adjusted to enable catastrophic droplet breakup, characterized by Rayleigh-Taylor (RT) breakup, near the nozzle exit. The model was validated against experimental spray data from five different injectors, including both multi-hole and single-hole injectors, with injection pressure varying from 100 to 200 bar.

Aromatics constitute a significant portion of refinery fuels. Characterizing the impact of various aromatic components on combustion and emissions facilitates formulation of surrogate fuels for engine simulations. The impact of blending aromatics in fuel surrogates is usually nonlinear for ignition characteristics responsible for knocking in spark engines and for combustion phasing in diesel engines. In this work, we have characterized the behavior of nine aromatics components under engine-relevant conditions. A self-consistent and validated detailed kinetics mechanism has been developed for gasoline and diesel surrogates that contains toluene, ethylbenzene, n-propylbenzene, n-butylbenzene, isomers of xylene, 1,2,4-trimethylbenzene, and 1-methylnaphthalene. Numerical experiments using 0-D and 1-D models have been performed to study the relative behavior of these aromatics for different reacting conditions.

This study focuses on Lagrangian spray models that are commonly used in engine CFD simulations. In modeling sprays, droplet collision is one of the physical phenomena that must be accounted for. There are two main parts of droplet collision models for sprays - detecting colliding pairs of droplets and predicting the outcomes of these collisions. For the first part, we focus on the efficiency of the algorithm. We present an implementation of the arbitrary adaptive collision mesh model of Hou and Schmidt [1], and examine its efficiency in dealing with large simulations. Through theoretical analysis and numerical tests, we show that the computational cost of this model scales pseudo-linearly with respect to the number of parcels in the sprays. Regarding the second part, we examine the variations in existing phenomenological models used for predicting binary droplet collision outcomes. A quantitative accuracy metric is used to evaluate the models with respect to the experimental data set.

Advanced research in Spark-ignition (SI) engines has been focused on dilute-combustion concepts. For example, exhaust-gas recirculation is used to lower both fuel consumption and pollutant emissions while maintaining or enhancing engine performance, durability and reliability. These advancements achieve higher engine efficiency but may deteriorate combustion stability. One symptom of instability is a large cycle-to-cycle variation (CCV) in the in-cylinder flow and combustion metrics. Large-eddy simulation (LES) is a computational fluid dynamics (CFD) method that may be used to quantify CCV through numerical prediction of the turbulent flow and combustion processes in the engine over many engine cycles. In this study, we focus on evaluating the capability of LES to predict the in-cylinder flows and gas exchange processes in a motored SI engine installed with a transparent combustion chamber (TCC), comparing with recently published data.

Emissions from Diesel engines have been a major concern for many years, particularly with regards to the impact of NOx and particulate matter on human health. Exhaust gas re-circulation (EGR) is a widely used method in diesel engines for controlling NOx production. While EGR rates can be varied to ensure engine performance and reduce NOx emissions, EGR also influences the ignition delay, reduces the peak combustion temperature and increases particulate emissions. Moreover, the injection timing directly affects NOx and particulate emissions under the broad and highly variable operating conditions. An effective CFD-based design tool for diesel engines must therefore include robust and accurate predictive capabilities for combustion and pollutant formation, to address the complex design tradeoffs. The objective of the present study is to evaluate CFD modeling of diesel engine combustion and emissions for various combinations of EGR rates and injection timings.

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.

A methodology has been implemented to calculate local turbulent flame speeds for spark ignition engines accurately and on-the-fly in 3-D CFD modeling. The approach dynamically captures fuel effects, based on detailed chemistry calculations of laminar flame speeds. Accurately modeling flame propagation is critical to predicting heat release rates and emissions. Fuels used in spark ignition engines are increasingly complex, which necessitates the use of multi-component fuels or fuel surrogates for predictive simulation. Flame speeds of the individual components in these multi-component fuels may vary substantially, making it difficult to define flame speed values, especially for stratified mixtures. In addition to fuel effects, a wide range of local conditions of temperature, pressure, equivalence ratio and EGR are expected in spark ignition engines.

One of the best tools to explore complicated in-cylinder physics is computational fluid dynamics (CFD). In order to assess the accuracy and reliability of the CFD simulations, it is critical to perform validation studies over different engine operating conditions. Simulation-based design of SI engines requires predictive capabilities, where results do not need to be tuned for each operating condition. This requires the models adopted to simulate their respective engine physics to be reliable under a broad range of conditions. A detailed set of experimental data was obtained to validate the CFD predictions of SI engine combustion.

Gasoline Direct Injection (GDI) is a key technology in the automotive industry for improving fuel economy and performance of gasoline internal combustion engines. GDI engine performance and emission characteristics are mainly determined by the complex interaction of in-cylinder flow, mixture formation and subsequent combustion processes. In a GDI engine, mixture formation depends on spray characteristics. Spray evolution and mixture formation is critical to GDI engine operation. In this work, a multi-component surrogate fuel blend was used to represent the chemical and physical properties of the gasoline employed in the experimental engine tests. Multi-component spray models were also validated in this study against experimental spray injection measurements in a chamber. The spray-chamber data include spray-penetration lengths, transient spray velocities and droplet Sauter mean diameter (SMD) at different axial and radial distances from the spray tip, obtained using a PDPA system.

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.

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.

An important goal for CFD simulation in engine design is to be able to predict the combustion behavior as operating conditions are varied and as hardware is modified. Such predictive capability allows virtual prototyping and optimization of design parameters. For low-temperature combustion conditions, such as with high rates of exhaust-gas recirculation, reliable and accurate predictions have been elusive. Soot has been particularly difficult to predict, due to the dependence of soot formation on the fuel composition and the kinetics detail of the fuel combustion. Soot evolution in diesel engines is impacted by fuel and chemistry effects, as well as by spray dynamics and turbulence. In this work, we present a systematic approach to accurately simulate combustion and emissions in a high-performance BMW diesel engine. This approach has been tested and validated against experimental data for a wide range of operating conditions.