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Although the application of cylinder pressure sensors to gain insight into the combustion process is not a novel topic itself, the recent availability of inexpensive in-cylinder pressure sensors has again prompted an upcoming interest for the utilization of the cylinder pressure signal within engine control and monitoring. Besides the use of the in-cylinder pressure signal for combustion analysis and control the information can also be used to determine related quantities in the exhaust or intake manifold. Within this work two different methods to estimate the pressure inside the exhaust manifold are proposed and compared. In contrary to first principle based approaches, which may require time extensive parameterization, alternative data driven approaches were pursued. In the first method a Principle Component Analysis (PCA) is applied to extract the cylinder pressure information and combined with a polynomial model approach.

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).

In recent years, the increase of gasoline fuel injection pressure is a way to improve thermal efficiency and lower engine-out emissions in GDI homogenous combustion concept. The challenge of controlling particulate formation as well in mass and number concentrations imposed by emissions regulations can be pursued improving the mixture preparation process and avoiding mixture inhomogeneity with ultra-high injection pressure values up to 100 MPa. The increase of the fuel injection pressure in GDI homogeneous systems meets the demand for increased injector static flow, while simultaneously improves the spray atomization and mixing characteristics with consequent better combustion performance. Few studies quantify the effects of high injection pressure on transient gasoline spray evolution. The aim of this work was to simulate with OpenFOAM the spray morphology of a commercial gasoline injected in a constant volume vessel by a prototypal GDI injector.

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.

Metallic foams or sponges are materials with a cell structure suitable for many industrial applications, such as reformers, heat catalytic converters, etc. The success of these materials is due to the combination of various characteristics such as mechanical strength, low density, high specific surface, good thermal exchange properties, low flow resistance and sound absorption. Different materials and manufacturing processes produce different type of structure and properties for various applications. In this work a genetic algorithm has been developed and applied to support the design of catalytic devices. In particular, two substrates were considered, namely the traditional honeycomb and an alternative open-cell foam type. CFD simulations of pressure losses and literature based correlations for the heat and mass transfer were used to support the genetic algorithm in finding the best compromise between flow resistance and pollutant abatement.

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.

In-cylinder ion sensing is a subject of interest due to its application in spark-ignited (SI) engines for feedback control and diagnostics including: combustion knock detection, rate and phasing of combustion, and mis-fire On Board Diagnostics (OBD). Further advancement and application is likely to continue as the result of the availability of ignition coils with integrated ion sensing circuitry making ion sensing more versatile and cost effective. In SI engines, combustion knock is controlled through closed loop feedback from sensor metrics to maintain knock near the borderline, below engine damage and NVH thresholds. Combustion knock is one of the critical applications for ion sensing in SI engines and improvement in knock detection offers the potential for increased thermal efficiency. This work analyzes and characterizes the ionization signal in reference to the cylinder pressure signal under knocking and non-knocking conditions.

Today, Direct-Injection systems are widely used on Spark-Ignition engines in combination with turbo-charging to reduce the fuel-consumption and the knock risks. In particular, the spread of Gasoline Direct Injection (GDI) systems is mainly related to the use of new generations of multi-hole, high-pressure injectors whose characteristics are quite different with respect to the hollow-cone, low-pressure injectors adopted in the last decade. This paper presents the results of an experimental campaign conducted on the spray produced by a GDI six-holes injector into a constant volume vessel with optical access. The vessel was filled with air at atmospheric pressure. Different operating conditions were considered for an injection pressure ranging from 3 to 20 MPa. For each operating condition, spray images were acquired by a CCD camera and then post processed to evaluate the spray penetration and cone angles.

In this paper a three-dimensional time-domain CFD approach has been employed to predict and analyze the acoustic attenuation performance of complex perforated muffler geometries, where strong 3D effects limit the validity of the use of one-dimensional models. A pressure pulse has been imposed at the inlet to excite the wave motion, while unsteady flow computation have been performed to acquire the time histories of the pressures upstream and downstream of the silencer. Pressures in the time domain have been then transformed to acoustic pressures in the frequency domain, to predict the transmission loss.

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 objective of this study was to utilize Statistical Energy Analysis (SEA) to simulate the effects of a variety of noise control treatments on the interior sound pressure level (SPL) of a commercial excavator cab. In addition, the effects of leaks on the SPL of the excavator cab were also investigated. This project was conducted along with various tests that were used to determine the inputs needed to accurately represent the loads that the cab experienced during operation. This paper explains the how the model was constructed, how the loads were applied to the model, the results that were obtained from application of treatments, and a study of the effects of introducing leaks to the cab structure in the SEA model.

The classical methods of measuring acoustic absorption coefficient using an impedance tube and a reverberation chamber are well established [1, 2]. However, these methods are not suitable for in-situ applications. The two in-situ methods; single channel microphone (P- probe) and dual channel acoustic pressure and particle velocity (Pu-probe) methods based on measurement of impulse response functions of the material surface under test, provide considerable advantage in data acquisition, signal processing, ease and mobility of measurement setup. This paper evaluates the measurement techniques of these two in-situ methods and provides results of acoustic absorption coefficient of a commercial artificial Astroturf, a Dow quash material, and a grass surface.

The capability to detect combustion in a diesel engine has the potential of being an important control feature to meet increasingly stringent emission regulations and for the development of alternative combustion strategies such as HCCI and PCCI. In this work, block mounted accelerometers are investigated as potential feedback sensors for detecting combustion characteristics in a high-speed, high pressure common rail (HPCR), 1.9L diesel engine. Accelerometers are positioned in multiple placements and orientations on the engine, and engine testing is conducted under motored, single and pilot-main injection conditions. Engine tests are then conducted at varying injection timings to observe the resulting time and frequency domain changes of both the pressure and acceleration signals.

An experimental and modeling study was conducted to study the passive regeneration of a catalyzed particulate filter (CPF) by the oxidation of particulate matter (PM) via thermal and Nitrogen dioxide/temperature-assisted means. Emissions data in the exhaust of a John Deere 6.8 liter, turbocharged and after-cooled engine with a low-pressure loop EGR and a diesel oxidation catalyst (DOC) - catalyzed particulate filter (CPF) in the exhaust system was measured and used for this study. A series of experiments was conducted to evaluate the performance of the DOC, CPF and DOC+CPF configurations at various engine speeds and loads.

Steady-state particulate loading experiments were conducted on an advanced production catalyzed particulate filter (CPF), both with and without a diesel oxidation catalyst (DOC). A heavy-duty diesel engine was used for this study with the experiments conducted at 20, 40, 60 and 75 % of full load (1120 Nm) at rated speed (2100 rpm). The data obtained from these experiments were used and are necessary for calibrating the MTU 1-D 2-Layer CPF model. These experimental and modeling results were compared to previous research conducted at MTU that used the same engine but an earlier development version of the combination of DOC and CPF. The motivation for the comparison of the two systems was to determine whether the reformulated production catalysts performed as good or better than the early development catalysts. The results were compared to understand the filtration and oxidation differences between the two DOC+CPF and the CPF-only aftertreatment systems.

A methodology to estimate the mass of particulate retained in a catalyzed particulate filter as a function of measured total pressure drop, volumetric flow rate, exhaust temperature, exhaust gas viscosity and cake and wall permeability applicable to real-time computation is discussed. This methodology is discussed from the view point of using it to indicate when to initiate active regeneration and as an On-Board Diagnostic tool to detect filter failures. Steady-state loading characterization experiments were conducted on a catalyzed diesel particulate filter (CPF) in a Johnson Matthey CCRT® (catalyzed continuously regenerating trap) system. The experiments were performed using a 10.8 L 2002 Cummins ISM heavy-duty diesel engine. Experiments were conducted at 20, 60 and 75% of full engine load (1120 Nm) and rated speed (2100 rpm) to measure the pressure drop, transient filtration efficiency, particulate mass balance, and gaseous emissions.

Active regeneration of a catalyzed particulate filter (CPF) is affected by a number of parameters specifically particulate matter loading and inlet temperature. The MTU 1-D 2-Layer CPF model [1] was used to analyze these effects on the pressure drop, oxidation and filtration characteristics of a CPF during active regeneration. In addition, modeling results for post loading experiments were analyzed to understand the difference between loading a clean filter as compared to a partially regenerated filter. Experimental data obtained with a production Cummins regenerative particulate filter for loading, active regenerations and post loading experiments were used to calibrate the MTU 1-D 2-Layer CPF model. The model predicted results are compared with the experimental data and were analyzed to understand the CPF characteristics during active regeneration at 1.1, 2.2 and 4.1 g/L particulate matter (PM) loading and CPF inlet temperatures of 525, 550 and 600°C.