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Fracture split forged steel connecting rods are utilized in many new high performance automotive engines to increase durability. Higher strength levels are needed as the power density increases. Fracture splitting without plastic deformation is necessary for manufacturability. Metallurgical design is a key for achieving the required performance levels. Several medium carbon steels containing 0.07 wt pct P, 0.06 wt pct S and various amounts of Mn, Si, V, and N were produced by vacuum induction melting laboratory heats and hot working the cast ingots into plates. The plates were cooled at varying rates to simulate typical cooling methods after forging. Microstructures were generally ferrite and pearlite as evaluated by light optical and scanning electron microscopy. Mechanical properties were determined by standard tensile tests, high strain rate notched tensile tests, and Charpy V-notch impact tests to assess “splittability”.

This paper presents a reconstruction technique in which nonlinear optimization is used in combination with an impact model to quickly and efficiently find a solution to a given set of parameters and conditions to reconstruct a collision. These parameters and conditions correspond to known or prescribed collision information (generally from the physical evidence) and can be incorporated into the optimized collision reconstruction technique in a variety of ways including as a prescribed value, through the use of a constraint, as part of a quality function, or possibly as a combination of these means. This reconstruction technique provides a proper, effective, and efficient means to incorporate data collected by Event Data Recorders (EDR) into a crash reconstruction. The technique is presented in this paper using the Planar Impact Mechanics (PIM) collision model in combination with the Solver utility in Microsoft Excel.

This paper attempts to integrate a derivative-free probability analysis method to Reliability-Based Robust Design Optimization (RBRDO). The Eigenvector Dimension Reduction (EDR) method is used for the probability analysis method. It has been demonstrated that the EDR method is more accurate and efficient than the Second-Order Reliability Method (SORM) for reliability and quality assessment. Moreover, it can simultaneously evaluate both reliability and quality without any extra expense. Two practical engineering problems (vehicle side impact and layered bonding plates) are used to demonstrate the effectiveness of the EDR method.

In the last decade, considerable advances have been made in reliability-based design optimization (RBDO). One assumption in RBDO is that the complete information of input uncertainties are known. However, this assumption is not valid in practical engineering applications, due to the lack of sufficient data. In practical engineering design, information concerning uncertainty parameters is usually in the form of finite samples. Existing methods in uncertainty based design optimization cannot handle design problems involving epistemic uncertainty with a shortage of information. Recently, a novel method referred to as Bayesian Reliability-Based Design Optimization (BRBDO) was proposed to properly handle design problems when engaging both epistemic and aleatory uncertainties [1]. However, when a design problem involves a large number of epistemic variables, the computation task for BRBDO becomes extremely expensive.

This paper presents an innovative approach for quality engineering using the Eigenvector Dimension Reduction (EDR) Method. Currently industry relies heavily upon the use of the Taguchi method and Signal to Noise (S/N) ratios as quality indices. However, some disadvantages of the Taguchi method exist such as, its reliance upon samples occurring at specified levels, results to be valid at only the current design point, and its expensiveness to maintain a certain level of confidence. Recently, it has been shown that the EDR method can accurately provide an analysis of variance, similar to that of the Taguchi method, but is not hindered by the aforementioned drawbacks of the Taguchi method. This is evident because the EDR method is based upon fundamental statistics, where the statistical information for each design parameter is used to estimate the uncertainty propagation through engineering systems.

In recent years, Nearfield Acoustical Holography (NAH) has been used to identify stationary vehicle exterior noise sources. However that application has usually been limited to individual components. Since powertrain noise sources are hidden within the engine compartment, it is difficult to use NAH to identify those sources and the associated partial field that combine to create the complete exterior noise field of a motor vehicle. Integrated Nearfield Acoustical Holography (INAH) has been developed to address these concerns: it is described here. The procedure entails sensing the sources inside the engine compartment by using an array of reference microphones, and then calculating the associated partial radiation fields by using NAH. In the second part of this paper, the use of farfield arrays is considered. Several array techniques have previously been applied to identify noise sources on moving vehicles.

This paper describes the heat transfer model of a composite aluminum brake rotor and compares the predicted temperatures to dynamometer measurements taken during a 15 fade stop trial. The model is based on meshed surface geometry which is simulated using RadTherm software. Methods for realistically modeling heat load distribution, surface rotation, convection cooling and radiation losses are also discussed. A comparison of the simulation results to the dynamometer data shows very close agreement throughout the fade stop trial. As such, the model is considered valid and will be used for further Steel Clad Aluminum (SCA) rotor development.

The introduction of a thin fluid layer between two layers of sheet metal offers a highly effective and economical alternative to the use of constrained viscoelastic damping layers in sheet metal structures. A diesel engine gear cover, which is constructed of two sheet metal sections spot welded together, takes advantage of fluid layer damping to produce superior vibration and sound radiation performance. In this paper, the bending of a double layered plate coupled through a thin fluid layer is modeled using a traveling wave approach which results in a impedance function that can be used to assess the vibration and sound radiation performance of practical double layered plate structures. Guided by this model, the influence of fluid layer thickness and inside-to-outside sheet thickness is studied.

To reduce the number and severity of accidents, automakers have invested in active safety systems to detect and track neighboring vehicles to prevent accidents. These systems often employ RADAR and LIDAR, which are not degraded by low lighting conditions. In this research effort, reflections from deer were measured using two sensors often employed in automotive active safety systems. Based on a total estimate of one million deer-vehicle collisions per year in the United States, the estimated cost is calculated to be $8,388,000,000 [1]. The majority of crashes occurs at dawn and dusk in the Fall and Spring [2]. The data includes tens of thousands of RADAR and LIDAR measurements of white-tail deer. The RADAR operates from 76.2 to 76.8 GHz. The LIDAR is a time-of-flight device operating at 905 nm. The measurements capture the deer in many aspects: standing alone, feeding, walking, running, does with fawns, deer grooming each other and gathered in large groups.

A complete analysis of any vehicular collision needs to consider certain aspects of human factors. However, this is especially true of nighttime collisions, in which a more specialized approach is required. Classical collision investigation (frequently referred to as accident reconstruction) is comprised of kinetic and kinematic considerations including skid analysis, momentum techniques and other methods. While analysis based on these concepts is typically unaffected by low visibility conditions, the opposite is true of the perceptual and cognitive aspects of a “humans-in-the-loop” analysis, which can be enormously impacted by low visibility. Only by applying appropriate human factors techniques can the analyst make a defensible determination of how and why a nighttime collision occurred.

Surrogate targets are used throughout the automotive industry to safely and repeatably test Advanced Driver Assistance Systems (ADAS) and will likely find similar applications in tests of Automated Driving Systems. For those test results to be applicable to real-world scenarios, the surrogate targets must be representative of the real-world objects that they emulate. Early target development efforts were generally divided into those that relied on sophisticated radar measurement facilities and those that relied on ad-hoc measurements using automotive grade equipment. This situation made communication and interpretation of results between research groups, target developers and target users difficult. SAE J3122, “Test Target Correlation - Radar Characteristics”, was developed by the SAE Active Safety Systems Standards Committee to address this and other challenges associated with target development and use. J3122 addresses four topics.

A previous paper on this topic presented the use of design of experiments (DOE) to evaluate the sensitivity of vehicle dynamics simulation of the postimpact motion of a vehicle that included high initial rotational rates. That investigation involved only one software package and thus was confined to one simulation model for the purposes of developing and refining the analysis method rather than including a variety of simulation models for broader application. This paper expands the application of the method to investigate the comparative behavior and sensitivity of several other vehicle dynamic simulation models commonly used in the field of crash reconstruction. The software packages included in the studies presented in this paper are HVE (SIMON and EDSMAC4), PC-Crash and VCRware. This paper will present the results of the study, conducted using DOE, involving these models.

This aim of this study was to introduce and test three different design enhancements to the contrast-sensitivity charts developed by Ayers and Kubose [1]. Contrast-sensitivity charts are the current, critical instrument for generating photographic representations of low-illumination scenes. However, their range of applicability is limited to a specific range of lighting conditions for any given scene, and a limited set of testing and perceptual conditions for observers. A total of four contrast charts were presented to ten dark-adapted observers in nine different lighting conditions that changed in ascending order from low to high levels of illumination. For each lighting condition, the order and orientation of the charts was randomized. Observations related to the number of detected contrast levels were then compared to find the utilization ranges for each chart.

In an accident reconstruction, vehicle speeds and positions are always of interest. When provided with scene photographs or fixed-location video surveillance footage of the crash itself, close-range photogrammetry methods can be useful in locating physical evidence and determining vehicle speeds and locations. Available 3D modeling software can be used to virtually match photographs or fixed-location video surveillance footage. Dash- or vehicle-mounted camera systems are increasingly being used in light vehicles, commercial vehicles and locomotives. Suppose video footage from a dash camera mounted to one of the vehicles involved in the accident is provided for an accident reconstruction but EDR data is unavailable for either of the vehicles involved. The literature to date describes using still photos to locate fixed objects, using video taken from stationary camera locations to determine the speed of moving objects or using video taken from a moving vehicle to locate fixed objects.