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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.

Motor vehicle crashes involving child Vulnerable Road Users (VRUs) remain a critical public health concern in the United States. While previous studies successfully utilized the crash scenario typology to examine traffic crashes, these studies focus on all types of motor vehicle crashes thus the method might not apply to VRU crashes. Therefore, to better understand the context and causes of child VRU crashes on the U.S. road, this paper proposes a multi-step framework to define crash scenario typology based on the Fatality Analysis Reporting System (FARS) and the Crash Report Sampling System (CRSS). A comprehensive examination of the data elements in FARS and CRSS was first conducted to determine elements that could facilitate crash scenario identification from a systematic perspective. A follow-up context description depicts the typical behavioral, environmental, and vehicular conditions associated with an identified crash scenario.

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 purpose of this study was to use detailed medical information to evaluate thoracic injuries in elderly patients in real world frontal crashes. In this study, we used analytic morphomics to predict the effect of torso geometry on rib fracture, a major source of injury for the elderly. Analytic morphomics extracts body features from computed tomography (CT) scans of patients in a semi-automated fashion. Thoracic injuries were examined in front row occupants involved in frontal crashes from the International Center for Automotive Medicine (ICAM) database. Among these occupants, two age groups (age < 60 yr. [Nonelderly] and age ≥ 60 yr. [Elderly]) who suffered severe thoracic injury were analyzed. Regression analyses were conducted to investigate injury outcomes using variables for vehicle, demographics, and morphomics. Compared to the nonelderly group, the elderly group sustained more rib fractures.

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).

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.

NASS 80-88 passenger side impacts data were analyzed. Location of primary car damage using the CDC classification, the AIS for injury severity studies, and the interior contacts of the various body areas. Drivers alone, or with passengers were studied separately in both left and right side crashes. Direct impacts to the passenger compartment only are less frequent than to other CDC side zones. Driver interior contacts vary by body region but also by side impacted in the crash. The presence of an unrestrained front passenger appears to enhance driver injury level in left side crashes but the presence of a passenger, in right side crashes appears to moderate driver injury severity.

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.

This study uses full drive cycle simulation to compare the fuel consumption of a vehicle with a turbocharged (TC) engine to the same vehicle with an alternative boosting technology, namely, a hybrid supercharger, in which a planetary gear mechanism governs the power split to the supercharger between the crankshaft and a 48 V 5 kW electric motor. Conventional mechanically driven superchargers or electric superchargers have been proposed to improve the dynamic response of boosted engines, but their projected fuel efficiency benefit depends heavily on the engine transient response and driver/cycle aggressiveness. The fuel consumption benefits depend on the closed-loop engine responsiveness, the control tuning, and the torque reserve needed for each technology. To perform drive cycle analyses, a control strategy is designed that minimizes the boost reserve and employs high rates of combustion dilution via exhaust gas recirculation (EGR).

Cost reduction, quality improvement, and regulatory compliance are well-recognized competitive issues. Companies must excel along each of these fronts while operating in an environment of rapid and multi-faceted change, limited financial and human capital, and increasing product development time pressure. In addition, consumers are demanding automobiles that provide greater performance, function, and comfort while emitting lower emissions, consuming fewer gallons of gasoline, injuring fewer humans, and requiring fewer dollars to build and purchase. A solution to these seemingly conflicting objectives is to take a systems view of the product and industry. This paper explores the material decision process so that manufacturers, component suppliers, and material providers may better understand the interlocking web of compromises that shape the pursuit of value-added alternatives and avoidance of unprofitable compromises.

In many task analyses using digital human figure models, only the terminal or apparently most stressful posture is analyzed. For reaches from a seated position, this is generally the posture with the hand or hands at the target. However, depending on the characteristics of the tasks and the people performing them, analyzing only the terminal posture could be misleading. This possibility was examined using data from a study of the reaching behavior of people with spinal cord injury. Participants performed two-handed forward reaching tasks. These reaches were to three targets located in the sagittal plane. The terminal postures did not differ significantly between those with spinal cord injury and those without. However, motion analysis demonstrated that they employed distinct strategies, particularly in the initial phase of motion.

Degreening is crucial in obtaining a stable catalyst prior to assessing its performance characteristics. This paper characterizes the light-off behavior and conversion efficiency of a Diesel Oxidation Catalyst (DOC) during the degreening process. A platinum DOC is degreened for 16 hours in the presence of actual diesel engine exhaust at 650°C and 10% water (H2O) concentration. The DOC's activity for carbon monoxide (CO) and for total hydrocarbons (THC) conversion is checked at 0, 1, 2, 3, 4, 6, 8, 10, 12, and 16 hours of degreening. Pre-and post-catalyst hydrocarbon species are analyzed via gas chromatography at 0, 4, 8, and 16 hours of degreening. It is found that both light-off temperature and species-resolved conversion efficiencies change rapidly during the first 8 hours of degreening and then stabilize to a large degree. T50, the temperature where the catalyst is 50% active towards a particular species, increases by 14°C for CO and by 11°C for THC through the degreening process.

This paper numerically investigates the performance implications of the use of an electric supercharger in a heavy-duty DD13 diesel engine. Two electric supercharger configurations are examined. The first is a high-pressure (HP) configuration where the supercharger is placed after the turbocharger compressor, while the second is a low-pressure (LP) one, where the supercharger is placed before the turbocharger compressor. At steady state, high engine speed operation, the airflows of the HP and LP implementations can vary by as much as 20%. For transient operation under the Federal Test Procedure (FTP) heavy duty diesel (HDD) engine transient drive cycle, supercharging is required only at very low engine speeds to improve airflow and torque. Under the low speed transient conditions, both the LP and HP configurations show similar increases in torque response so that there are 44 fewer engine cycles at the smoke-limit relative to the baseline turbocharged engine.