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In the process of conducting a reliability analysis of a system, quite often the population of interest is not homogenous; consisting of sub-populations which arise as production operations are adjusted, component suppliers are changed, etc. While these sub-populations are each unique in many ways, they also have much in common. It is also common for data to be available from a variety of different test regimes, e.g. environmental testing and fleet maintenance observations. Hierarchical Bayesian methods provide an organized, objective means of estimating the reliability of the individual systems, the sub-population reliability as well as the reliability of the entire population. This paper provides an introduction to a Bayesian approach that can be extended for more complicated situations.

This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.

Comparisons have been made between dual-fuel (80% port-injection gasoline and 20% direct-injection diesel by mass) Highly Premixed Charge Combustion (HPCC) and blended-fuel (80% gasoline and 20% diesel) Low Temperature Combustion (LTC) modes on a 1-L single-cylinder test engine. In the HPCC mode, both early-injection (E-HPCC) and late-injection (L-HPCC) of diesel have been used. The comparisons have been conducted with a fixed fuel injection rate of 50 mg/cycle at 1500 rpm, and with the combustion phasing fixed (by adjusting the injection timing) so that the 50% heat release point (CA50) is at 8° ATDC. The rapid heat release process of LTC leads to the highest maximum pressure rise rate (MPRR). A two-peak heat release process is observed in L-HPCC, resulting in a lower MPRR. The heat release rate and MPRR values for the E-HPCC are comparable to the L-HPCC values. The EHPCC mode provides the lowest NOX emission. The soot emissions for all three modes are low.

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.

This paper discusses the treatment of uncertainties corresponding to relatively few samples of random-variable quantities. The importance of this topic extends beyond experimental data uncertainty to situations involving uncertainty in model calibration, validation, and prediction. With very sparse samples it is not practical to have a goal of accurately estimating the underlying variability distribution (probability density function, PDF). Rather, a pragmatic goal is that the uncertainty representation should be conservative so as to bound a desired percentage of the actual PDF, say 95% included probability, with reasonable reliability. A second, opposing objective is that the representation not be overly conservative; that it minimally over-estimate the random-variable range corresponding to the desired percentage of the actual PDF. The presence of the two opposing objectives makes the sparse-data uncertainty representation problem an interesting and difficult one.

In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

Advances in avionics and display technology are significantly changing the cockpit environment in current transport aircraft. The MIT Aeronautical Systems Lab (ASL) has developed a part-task flight simulator specifically to study the effects of these new technologies on flight crew situational awareness and performance. The simulator is based on a commercially-available graphics workstation, and can be rapidly reconfigured to meet the varying demands of experimental studies. The simulator has been successfully used to evaluate graphical microburst alerting displays, electronic instrument approach plates, terrain awareness and alerting displays, and ATC routing amendment delivery through digital datalinks.

An aerodynamic model of the entrainment of the head wall quench layer during blowdown and exhaust of an internal combustion engine has been developed. The model may be used to calculate the time resolved concentration and mass flowrate of hydrocarbons (HC) in the exhaust, from a knowledge of engine geometry and operating conditions. It predicts that the area As from which HC are swept will be proportional to the cube root of the ratio of the quench layer thickness δq to the thickness of the viscous boundary layer δv. Since the mass of HC emitted is proportional to the product of the HC density ρHC, the area As and the thickness δq, the HC emissions will be proportional to the product ρHC δq4/3 and this is the most important factor determining the emissions.

The use of hydrogen as a fuel supplement for lean-burn engines at higher compression ratios has been studied extensively in recent years, with good promise of performance and efficiency gains. With the advances in reformer technology, the use of a gaseous fuel stock, comprising of substantially higher fractions of hydrogen and other flammable reformate species, could provide additional improvements. This paper presents the performance and emission characteristics of a gas mixture of equal volumes of hydrogen, CO, and methane. It has recently been reported that this gas mixture can be produced by reforming of ethanol at comparatively low temperature, around 300C. Experiments were performed on a 1.8-liter passenger-car Nissan engine modified for single-cylinder operation. Special pistons were made so that compression ratios ranging from CR= 9.5 to 17 could be used. The lean limit was extended beyond twice stoichiometric (up to lambda=2.2).

A novel engine management strategy for achieving fast catalyst light-off without the use of an exhaust air pump in a port-fuel-injected, spark ignition engine was developed. A conventional 4-cylinder engine was operated with three cylinders running rich and the fourth one as an air pump to supply air to the exhaust manifold. Under steady-state cold coolant conditions, this strategy achieved near total oxidation of CO and HC with sufficiently retarded spark timing, resulting in a 400% increase in feedgas enthalpy flow and a 90% reduction in feedgas HC emissions compared to conventional operation. The strategy was also evaluated for crank starts. Using the existing engine hardware, implementing the strategy resulted in a reduction in catalyst light-off time from 28.0 seconds under conventional operation to 9.1 seconds.

This paper presents a numerical model of the rotational and lateral dynamics of the piston (secondary motion) and piston slap in mixed lubrication. Piston dynamic behavior, frictional and impact forces are predicted as functions of crank angle. The model considers piston skirt surface waviness, roughness, skirt profile, thermal and mechanical deformations. The model considers partially-flooded skirt and calculates the pressure distributions and friction in the piston skirt region for both hydrodynamic and boundary lubrication. Model predictions are compared with measurements of piston position using gap sensors in a single-cylinder engine and the comparison between theory and measurement shows remarkable agreement.

A free piston, internal combustion (IC) engine, operating at high compression ratio (∼30:1) and low equivalence ratio (ϕ∼0.35), and utilizing homogeneous charge compression ignition combustion, has been proposed by Sandia National Laboratories as a means of significantly improving the IC engine's cycle thermal efficiency and exhaust emissions. A zero-dimensional, thermodynamic model with detailed chemical kinetics, and empirical scavenging, heat transfer, and friction component models has been used to analyze the steady-state operating characteristics of this engine. The cycle simulations using hydrogen as the fuel, have indicated the critical factors affecting the engine's performance, and suggest the limits of improvement possible relative to conventional IC engine technologies.

A twin-land oil control ring (TLOCR) model is used to evaluate TLOCR friction and the results are compared to the experiment measurement in a single cylinder floating liner engine under motoring condition. The model is based on a correlation between the hydrodynamic pressure and film thickness, which is generated using a deterministic model. The well-known three-regime lubrication is predicted with the model for ring with different ring tensions under various engine running conditions. A good match is found for the model and experiment results.

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.

In an optically-accessible single-cylinder engine fuelled with hydrogen, OH* chemiluminescence imaging and planar laser induced fluorescence (PLIF) are used to qualitatively evaluate in-cylinder mixture formation. The experiments include measurements for engine operation with hydrogen injection in-cylinder either prior to or after intake valve closure (IVC). Pre-IVC injection is used to produce a near homogeneous mixture in-cylinder to establish a baseline comparison for post-IVC injection. To assess the effects of injection pressure on mixture formation, two injection pressures are used for post-IVC injection. For post-IVC injection with start of injection (SOI) coincident with IVC, mixture distribution is similar to pre-IVC injection and there are little differences between the two injection pressures. With retard of SOI from IVC, mixture inhomogeneities increase monotonically for both injection pressures.

This work is a comprehensive technical review of existing literature and a synthesis of current understanding of the governing physics behind the interaction of multiple fuel injections, ignition, and combustion behavior of multiple-injections in diesel engines. Multiple-injection is a widely adopted operating strategy applied in modern compression-ignition engines, which involves various combinations of small pre-injections and post-injections of fuel before and after the main injection and splitting the main injection into multiple smaller injections. This strategy has been conclusively shown to improve fuel economy in diesel engines while achieving simultaneous NOX, soot, and combustion noise reduction - in addition to a reduction in the emissions of unburned hydrocarbons (UHC) and CO by preventing fuel wetting and flame quenching at the piston wall.

A fuel volatility model based on the major species present in the fuel has been formulated. The model accurately predicts the ASTM distillation curves and Reid Vapor Pressure for hydrocarbon fuels. The model may be used to assess the fuel effects on the extent of evaporation and the vapor composition in the mixture preparation process.

ESA has been developing regenerative physicochemical air revitalisation technology for more than 20 years. The effort is now maturing into a flight demonstration experiment which is planned to be located in the Columbus module on ISS. The experiment shall be sized for a crew of three. It will comprise a CO2 concentration assembly, a Sabatier reactor and an electrolyser. The paper describes the adaptation of ARES to the available Columbus interfaces as well as ARES development status, performances, benefits to the ISS and operational agreements with ISS partners.

The Automated Transfer Vehicle (ATV) Thermal Control System (TCS) has the task to ensure the required internal environment at level of pressurized module and to thermally control the not pressurised modules and installed equipment, using passive and active control means, in response to the relevant applicable requirements. The ATV vehicle is assially subdivided into three main modules: the Integrated Cargo Carrier (ICC), the Equipped Avionics Bay (EAB) and the Equipped Propulsion Bay (EPB). Each of these modules present elaborated and specific thermal design solutions, to satisfy the different required operative tasks. The extensive thermal analysis campaign performed at ATV vehicle level and in progress for the next Qualification Review (QR) to justify and support the thermal control design solutions and verification status is described.