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A numerical investigation on a series of Diesel spray experiments in constant-volume vessels is proposed. Non reacting conditions were used to assess the spray models and to determine the grid size required to correctly predict the fuel-air mixture formation process. To this end, not only computed liquid and vapor penetrations were compared with experimental data, but also a detailed comparison between computed and experimental mixture fraction distributions was performed at different distances from the injector. Grid dependency was reduced by introducing an Adaptive Local Mesh Refinement technique (ALMR) with an arbitrary level of refinement. Once the capabilities of the current implemented spray models have been assessed, reacting conditions at different ambient densities and temperatures were considered. A Perfectly Stirred Reactor (PSR) combustion model, based on a direct integration of complex chemistry mechanisms over a homogenous cell, was adopted.

Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

Ammonia/urea-SCR is a mature technology, applied worldwide for the control of NOx emissions in combustion exhausts from thermal power plants, cogeneration units, incinerators and stationary diesel engines and more recently also from mobile sources. However a greater DeNOx activity at low temperatures is desired in order to meet more and more restrictive legislations. In this paper we report transient and steady state data collected over commercial Fe-ZSM-5 and V₂O₅-WO₃/TiO₂ catalysts showing high NOx reduction efficiencies in the 200 - 350°C T-range when NO and ammonia react with nitrates, e.g., in the form of an aqueous solution of ammonium nitrate. Under such conditions a new reaction occurs, the so-called "Enhanced SCR" reaction, 2 NH₃ + 2 NO + NH₄NO₃ → 3 N₂ + 5 H₂O.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Fuel lean combustion and exhaust gas dilution are known to increase the thermal efficiency and reduce NOx emissions. In this study, experiments are performed to understand the effect of equivalence ratio on flame kernel formation and flame propagation around the spark plug for different low turbulent velocities. A series of experiments are carried out for propane-air mixtures to simulate engine-like conditions. For these experiments, equivalence ratios of 0.7 and 0.9 are tested with 20 percent mass-based exhaust gas recirculation (EGR). Turbulence is generated by a shrouded fan design in the vicinity of J-spark plug. A closed loop feedback control system is used for the fan to generate a consistent flow field. The flow profile is characterized by using Particle Image Velocimetry (PIV) technique. High-speed Schlieren visualization is used for the spark formation and flame propagation.

The modeling of fuel sprays under well-characterized conditions relevant for heavy-duty Diesel engine applications, allows for detailed analyses of individual phenomena aimed at improving emission formation and fuel consumption. However, the complexity of a reacting fuel spray under heavy-duty conditions currently prohibits direct simulation. Using a systematic approach, we extrapolate available spray models to the desired conditions without inclusion of chemical reactions. For validation, experimental techniques are utilized to characterize inert sprays of n-dodecane in a high-pressure, high-temperature (900 K) constant volume vessel with full optical access. The liquid fuel spray is studied using high-speed diffused back-illumination for conditions with different densities (22.8 and 40 kg/m3) and injection pressures (150, 80 and 160 MPa), using a 0.205-mm orifice diameter nozzle.

Past experimental studies conducted by the current authors on a 13 liter 16.7:1 compression ratio heavy-duty diesel engine have shown that diesel-Compressed Natural Gas (CNG) Reactivity Controlled Compression Ignition (RCCI) combustion targeting low NOx emissions becomes progressively difficult to control as the engine load is increased. This is mainly due to difficulty in controlling reactivity levels at higher loads. For the current study, CFD investigations were conducted in CONVERGE using the SAGE combustion solver with the application of the Rahimi mechanism. Studies were conducted at a load of 5 bar BMEP to validate the simulation results against RCCI experimental data. In the low load study, it was found that the Rahimi mechanism was not able to predict the RCCI combustion behavior for diesel injection timings advanced beyond 30 degCA bTDC. This poor prediction was found at multiple engine speed and load points.

Selective Catalytic Reduction (SCR) systems are nowadays widely applied for the reduction of NOx emitted from Diesel engines. The typical process is based on the injection of aqueous urea in the exhaust gases before the SCR catalyst, which determines the production of the ammonia needed for the catalytic reduction of NOx. However, this technology is affected by two main limitations: a) the evaporation of the urea water solution (UWS) requires a sufficiently high temperature of the exhaust gases and b) the formation of solid deposits during the UWS evaporation is a frequent phenomenon which compromise the correct operation of the system. In this context, to overcome these issues, a technology based on the injection of gaseous ammonia has been recently proposed: in this case, ammonia is stored at the solid state in a cartridge containing a Strontium Chloride salt and it is desorbed by means of electrical heating.

Autonomous ground vehicles can use a variety of techniques to navigate the environment and deduce their motion and location from sensory inputs. Visual Odometry can provide a means for an autonomous vehicle to gain orientation and position information from camera images recording frames as the vehicle moves. This is especially useful when global positioning system (GPS) information is unavailable, or wheel encoder measurements are unreliable. Feature-based visual odometry algorithms extract corner points from image frames, thus detecting patterns of feature point movement over time. From this information, it is possible to estimate the camera, i.e., the vehicle’s motion. Visual odometry has its own set of challenges, such as detecting an insufficient number of points, poor camera setup, and fast passing objects interrupting the scene. This paper investigates the effects of various disturbances on visual odometry.

Transient and steady-state kinetic data are herein presented to analyze the inhibiting effect of ammonia on the NH₃-SCR of NO at low temperatures over a Fe-zeolite commercial catalyst for vehicles. It is shown that in SCR converter models a rate expression accounting for NH₃ inhibition of the Standard SCR reaction is needed in order to predict the specific dynamics observed both in lab-scale and in engine test bench runs upon switching on and off the ammonia feed. Two redox, dual site kinetic models are developed which ascribe such inhibition to the spill-over of ammonia from its adsorption sites, associated with the zeolite, to the redox sites, associated with the Fe promoter. Better agreement both with lab-scale intrinsic kinetic runs and with engine test-bench data, particularly during transients associated with dosing of ammonia to the SCR catalyst, is obtained assuming slow migration of NH₃ between the two sites.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

The flow field resulting from injecting a gas jet into a crossflow confined in a narrow square duct has been studied under steady regime using schlieren imaging and laser Doppler velocimetry (LDV). This transparent duct is intended to simulate the intake port of an internal combustion engine fueled by gaseous mixture, and the jet is issued from a round nozzle. The schlieren images show that the relative small size of the duct would confine the development of the transverse jet, and the interaction among jet and sidewalls strongly influences the mixing process between jet and crossflow. The mean velocity and turbulence fields have been studied in detail through LDV measurements, at both center plane and several cross sections. The well-known flow feature formed by a counter rotating vortex pair (CVP) has been observed, which starts to appear at the jet exit section and persists far downstream contributing to enhancing mixing process.

This paper is focused on the development and application of a CFD methodology that can be applied to predict the fuel-air mixing process in stratified charge, sparkignition engines. The Eulerian-Lagrangian approach was used to model the spray evolution together with a liquid film model that properly takes into account its effects on the fuel-air mixing process into account. However, numerical simulation of stratified combustion in SI engines is a very challenging task for CFD modeling, due to the complex interaction of different physical phenomena involving turbulent, reacting and multiphase flows evolving inside a moving geometry. Hence, for a proper assessment of the different sub-models involved a detailed set of experimental optical data is required. To this end, a large experimental database was built by the authors.

The Kalman and Vold-Kalman order tracking filters have been implemented in commercial software since the early 90's. There are several mathematical formulations of filters that have been implemented by different software vendors. However, there have not been any papers that have been published which sufficiently explain the math behind these filters and discuss the actual implementations of the filters in software. In addition, upon generating the equations represented by these filters, solving the equations for datasets in excess of several hundred thousand datapoints is not trivial and has not been discussed in the literature. The papers which have attempted to cover these topics are generally vague and overly mathematically eloquent but not easily understandable by a practicing engineer.

In the last years automotive industry has shown a growing interest in exploring the field of vehicle dynamic control, improving handling performances and safety of the vehicle, and actuating devices able to optimize the driving torque distribution to the wheels. These techniques are defined as torque vectoring. The potentiality of these systems relies on the strong coupling between longitudinal and lateral vehicle dynamics established by tires and powertrain. Due to this fact the detailed (and correct) simulation of the dynamic behaviour of the driveline has a strong importance in the development of these control systems, which aim is to optimize the contact forces distribution. The aim of this work is to build an integrated vehicle and powertrain model in order to provide a proper instrument to be used in the development of such systems, able to reproduce the dynamic interaction between vehicle and driveline and its effects on the handling performances.

With concerns continuing to grow with respect to global warming from greenhouse gases, further regulations are being examined, developed and are expected for the emission of CO2 as an automobile exhaust. Renewable alternate fuels offer the potential to significantly reduce the CO2 impact of transportation. Hydrogen as a spark - ignition (SI) engine fuel provides this potential for significant CO2 reduction when generated from renewable resources. In addition, hydrogen has advantageous combustion properties including a wide flammable mixture range which facilitates lean burning and high dilution, fast combustion energy release and zero CO2 emissions. However, the high burning rates and fast energy release can lead to excessive in-cylinder pressures and temperatures resulting in combustion knock and high NOx emissions at stoichiometric operation.

As noise concerns for snowmobiles become of greater interest for governing bodies, standards such as SAE J192 are implemented for regulation. Specific to this pass-by noise standard, and unlike many other pass-by tests, multiple non-standardized test surfaces are allowed to be used. Manufacturers must understand how the machines behave during these tests to know how to best improve the measured noise levels. Data is presented that identifies the contributions of different sources for different snowmobiles on various test surface conditions. Adaptive resampling for Doppler removal, frequency response functions and order tracking methods are implemented in order to best understand what components affect the overall measurement during the pass-by noise test.

The discrete droplet model is widely used to describe two-phase flows such as high-velocity dense sprays. The interaction between the liquid and the gas phase is modeled via appropriate source terms in the gas phase equations. This approach can lead to a strong dependence of the liquid-gas coupling on the spatial resolution of the gas phase. The liquid-gas coupling requires the computation of source terms using the gas phase properties, and, subsequently, these sources are then distributed onto the gas phase mesh. In this study, a Lagrange polynomial interpolation method has been developed to evaluate the source terms and also to distribute these source terms onto the gas mesh. The focus of this investigation has been on the momentum exchange between the two phases. The Lagrange polynomial interpolation and source term distribution methods are evaluated for non-evaporating sprays using KIVA3 as a modeling platform.

A one-dimensional model simulating the oxidation of CO, HC, and NO was developed to predict the gaseous emissions downstream of a diesel oxidation catalyst (DOC). The model is based on the conservation of mass, species, and energy inside the DOC and draws on past research literature. Steady-state experiments covering a wide range of operating conditions (exhaust temperatures, flow rates and gaseous emissions) were performed, and the data were used to calibrate and validate the model. NO conversion efficiencies of 50% or higher were obtained at temperatures between 300°C and 350°C. CO conversion efficiencies of 85% or higher and HC conversion efficiencies of 75% or higher were found at every steady state condition above 200°C. The model agrees well with the experimental results at temperatures from 200°C to 500°C, and volumetric flow rates from 8 to 42 actual m3/min.