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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.

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.

Available methodologies for model bias identification are mainly regression-based approaches, such as Gaussian process, Bayesian inference-based models and so on. Accuracy and efficiency of these methodologies may degrade for characterizing the model bias when more system inputs are considered in the prediction model due to the curse of dimensionality for regression-based approaches. This paper proposes a copula-based approach for model bias identification without suffering the curse of dimensionality. The main idea is to build general statistical relationships between the model bias and the model prediction including all system inputs using copulas so that possible model bias distributions can be effectively identified at any new design configurations of the system. Two engineering case studies whose dimensionalities range from medium to high will be employed to demonstrate the effectiveness of the copula-based approach.

Developing a new technology requires decision-makers to understand the technology's implications on an organization's objectives, which depend on user needs targeted by the technology. If these needs are common between two organizations, collaboration could result in more efficient technology development. For hybrid truck design, both commercial manufacturers and the military have similar performance needs. As the new technology penetrates the truck market, the commercial enterprise must quantify how the hybrid's superior fuel efficiency will impact consumer purchasing and, thus, future enterprise profits. The Army is also interested in hybrid technology as it continues its transformation to a more fuel-efficient force. Despite having different objectives, maximizing profit and battlefield performance, respectively, the commercial enterprise and Army can take advantage of their mutual needs.

The pulleys employed in automotive accessory drive systems very often consist of a two piece assembly; a multitude of fastening techniques are used in completing the assembly. There are numerous assembly methods and a variety of distinct pulley configurations dictated by the various automobile manufacturers in accordance with individual accessory drive needs. An expert system is being developed to evaluate the merit of multiple assembly alternatives for a specific pulley application. The expert system provides a consistent evaluation tool for assembly alternatives, balancing the influence of product cost, strength and quality considerations. The knowledge-based system is implemented in an expert system shell called AGNESS (A Generalized Network-based Expert System Shell). The expert system judges the acceptability of various pulley assembly techniques, assigning a high “merit value” to the better designs and proportionately lower values to less desirable designs.

The reach capability of drivers is currently represented in vehicle design practice in two ways. The SAE Recommended Practice J287 presents maximum reach capability surfaces for selected percentiles of a generic driving population. Driver reach is also simulated using digital human figure models. In typical applications, a family of figure models that span a large range of the target driver population with respect to body dimensions is positioned within a digital mockup of the driver's workstation. The articulated segments of the figure model are exercised to simulate reaching motions and driver capabilities are calculated from the constraints of the kinematic model. Both of these current methods for representing driver reach are substantially limited. The J287 surfaces are not configurable for population characteristics, do not provide the user with the ability to adjust accommodation percentiles, and do not provide any guidance on the difficulty of reaches that are attainable.

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.

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.

The effect of skip-firing (which is often applied in optical engine work) on the available in-cylinder oxygen concentration was investigated with a laser-induced fluorescence imaging setup that combines the measurement of fluorescence signals from toluene and 3-pentanone to quantitatively determine the distribution of molecular oxygen. We describe in detail the image processing procedure for this measurement. The reduction of in-cylinder oxygen when switching from skip-fired to continuous-fired engine operation is measured and compared to traditional exhaust measurements.

The addition of synthetic traffic to a driving simulation greatly enhances the realism of the virtual world. Giving this traffic human-like behavior is likewise desirable, and has been the focus of some research over the past few years. This paper presents a modular architecture for including autonomous traffic in a driving simulation, and describes the first steps taken toward the application of this architecture to the DaimlerChrysler Auburn Hills Simulator. By separating the planning part of the agent from the low-level control and vehicle dynamics systems, the described architecture permits the inclusion of powerful, previously developed components in a straightforward way; in the present application, agents use Soar to reason about their actions. This paper gives an overview of the structures of the agents, and of the entire system, describes the components and their implementations, and discusses the current state of the project and plans for the future.

Thermal effectiveness of Exhaust Gas Recirculation (EGR) coolers used in diesel engines can progressively decrease and stabilize over time due to inner fouling layer of the cooler tubes. Thermophoretic force has been identified as the major cause of diesel exhaust soot fouling, and models are proposed in the literature but improvements in simulation are needed especially for the long-term trend of soot deposition. To describe the fouling stabilization behavior, a removal mechanism is required to account for stabilization of the soot layer. Observations from previous experiments on surrogate circular tubes suggest there are three primary factors to determine removal mechanisms: surface temperature, thickness, and shear velocity. Based on this hypothesis, we developed a 1D CFD fouling model for predicting the thermal effectiveness reduction of real EGR coolers. The model includes the two competing mechanisms mentioned that results in fouling balance.

Stringent fuel economy and emissions regulations have driven development of new mixture preparation technologies and increased spark-ignition engine complexity. Additional degrees of freedom, brought about by devices such as cam phasers and charge motion control valves, enable greater range and flexibility in engine control. This permits significant gains in fuel efficiency and emission control, but creates challenges related to proper engine control and calibration techniques. Accurate experimental characterization of high degree of freedom engines is essential for addressing the controls challenge. In particular, this paper focuses on the evaluation of three experimental residual gas fraction measurement techniques for use in a spark ignition engine equipped with dual-independent variable camshaft phasing (VVT).

For 2D surface temperature monitoring applications, a variant of Electrical Impedance Tomography (EIT) was evaluated computationally in this study. Literature examples of poor sensor performance in the center of the 2D domains away from the side electrodes motivated these efforts which seek to overcome some of the previously noted shortcomings. In particular, the use of ‘sensing skins’ with novel tailored baseline conductivities was examined using the EIDORS package for EIT. It was found that the best approach for detecting a temperature hot spot depends on several factors such as the current injection (stimulation) patterns, the measurement patterns, and the reconstruction algorithms. For well-performing combinations of these factors, customized baseline conductivities were assessed and compared to the baseline uniform conductivity.

A series of inflator tank tests was carried out to determine the amount of transient heat losses to the tank wall during these tests. The time history data of tank wall temperature, and tank interior gas temperature and pressure, were measured. The tank wall temperature data were analyzed using an inverse heat conduction method to generate the transient heat loss fluxes from the tank gas to the tank wall. The validity of the results are discussed along with the physical reasoning and experimental observations. This is the first part of an effort in a research project to develop a comprehensive heat transfer model to predict the transient heat losses to the tank wall during the inflator tank test.

A new approach to driver seat-position modeling is presented. The equations of the Seating Accommodation Model (SAM) separately predict parameters of the distributions of male and female fore/aft seat position in a given vehicle. These distributions are used together to predict specific percentiles of the combined male-and-female seat-position distribution. The effects of vehicle parameters-seat height, steering-wheel-to-accelerator pedal distance, seat-cushion angle, and transmission type-are reflected in the prediction of mean seat position. The mean and standard deviation of driver population stature are included in the prediction for the mean and standard deviation of the seat-position distribution, respectively. SAM represents a new, more flexible approach to predicting fore/aft seat-position distributions for any driver population in passenger vehicles. Model performance is good, even at percentiles in the tails of the distribution.

Mixture formation in an optically accessible hydrogen-fueled engine was investigated using Planar Laser-Induced Fluorescence (PLIF) of acetone as a fuel tracer. The engine was motored and fueled by direct high-pressure injection. This paper presents the evolution of the spatial distribution of the ensemble-mean equivalence ratio for six different combinations of nozzle design and injector geometry, each for three different injection timings after intake-valve closure. Asymmetric single-hole and 5-hole nozzles as well as symmetric 6-hole and 13-hole nozzles were used. For early injection, the low in-cylinder pressure and density allow the jet to preserve its momentum long enough to undergo extensive jet-wall and (for multi-hole nozzles) jet-jet interaction, but the final mixture is fairly homogeneous. Intermediately timed injection yields inhomogeneous mixtures with surprisingly similar features observed for all multi-hole injectors.

The soot distribution as function of ambient O₂ mole fraction in a heavy-duty diesel engine was investigated at low load (6 bar IMEP) with laser-induced incandescence (LII) and natural luminosity. A Multi-YAG laser system was utilized to create time-resolved LII using 8 laser pulses with a spacing of one CAD with detection on an 8-chip framing camera. It is well known that the engine-out smoke level increases with decreasing oxygen fraction up to a certain level where it starts to decrease again. For the studied case the peak occurred at an O₂ fraction of 11.4%. When the oxygen fraction was decreased successively from 21% to 9%, the initial soot formation moved downstream in the jet. At the lower oxygen fractions, below 12%, no soot was formed until after the wall interaction. At oxygen fractions below 11% the first evidence of soot is in the recirculation zone between two adjacent jets.

Thermal distortions of friction disks caused by frictional heating modify pressure distribution on friction surfaces. Pressure distribution, in turn, determines distribution of generated frictional heat. These interdependencies create a complex thermoelastic system that, under some conditions, may become unstable and may lead to severe pressure concentrations with very high local temperature and stress. The phenomenon is responsible for many common thermal failure modes of friction elements and is known as frictionally excited thermoelastic instability (TEI). In the paper, one of the cases of TEI is investigated theoretically and experimentally. The study involves a two-disk structure with one fiction disk and one matching steel disk that have one friction interface. An unsteady heat conduction problem and an elastic contact problem are modeled as axisymmetric ones and are solved using the finite element method.

The rapid development of connected and automated vehicle technologies together with cloud-based mobility services are revolutionizing the transportation industry. As a result, huge amounts of data are being generated, collected, and utilized, hence providing tremendous business opportunities. However, this big data poses serious challenges mainly in terms of data privacy. The risks of privacy leakage are amplified by the information sharing nature of emerging mobility services and the recent advances in data analytics. In this paper, we provide an overview of the connected vehicle landscape and point out potential privacy threats. We demonstrate two of the risks, namely additional individual information inference and user de-anonymization, through concrete attack designs. We also propose corresponding countermeasures to defend against such privacy attacks. We evaluate the feasibility of such attacks and our defense strategies using real world vehicular data.