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One of the primary issues in the interpretation of vehicle impact response data, observed from vehicle crash test events, is coping with variability. This vehicle response inconsistency generally causes test results to be unpredictable and makes CAE test validation work difficult as well. This paper, considering the uncertain characteristics of vehicle impact events, has implemented a stochastic assessment of vehicle NCAP response variation through a CAE vehicle impact model, and it has accomplished the three primary study objectives as stated follows: 1) Identify the response variation causing factors stochastically from various structural and environmental factor candidates and quantify the degree of their influences on crash response, 2) Develop a methodology for interpreting the significance of the factor effects in conjunction with vehicle impact mechanics and physics, and 3) Implement a stochastic improvement of the vehicle NCAP responses and their repeatability

In stereo photogrammetry, the accuracy of calculating the location of a point in space, decreases as the angle between the two cameras decreases. For vehicle crash testing, the need for accurate 3D data conflicts with the need for flexible positioning of the cameras, to enable unobstructed views of the targets inside the vehicle throughout the impact event. This paper discusses a method for increasing the quantity and quality of film analysis data when small subtended angles are used. The method uses the 3D information developed through triangulation of two cameras as input to a single camera analysis.

The Frequency Response Function (FRF) is a fundamental component to identifying the dynamic characteristics of a system. FRF's have a significant impact on modal analysis and root cause analysis of NVH issues. In most cases the FRF can be easily measured, but there are instances when the measurement is unobtainable due to spatial constraints. This paper outlines a simple experimental method for obtaining a high quality input-output FRF of a structure in areas where an impact hammer can not reach during impact testing. Traditionally, the FRF in such an area is obtained by using a load cell extender with a hammer impact excitation. A common problem with this device is a double hit, that yields unacceptable results.

The Hybrid III family of dummies is used to estimate the response of an occupant during a crash. One recent area of interest is the response of the neck during air bag loading. The biomechanical response of the Hybrid III dummy's neck was based on inertial loading during crash events, when the dummy is restrained by a seat belt and/or seat back. Contact loading resulting from an air bag was not considered when the Hybrid III dummy was designed. This paper considers the effect of air bag loading on the 5th percentile female Hybrid III dummies. The response of the neck is presented in comparison to currently accepted biomechanical corridors. The Hybrid III dummy neck was designed with primary emphasis on appropriate flexion and extension responses using the corridors proposed by Mertz and Patrick. They formulated the mechanical performance requirements of the neck as the relationship between the moment at the occipital condyles and the rotation of the head relative to the torso.

This paper deals with the multi-parameter and boundary mannequin techniques in creating human models in automotive applications. The concepts and applications of single-parameter, multiple parameter and boundary mannequin method are discussed respectively to clarify certain confusion. Emphasis is put on how to create boundary mannequins for a specific application, which may have been puzzling many engineers in practical applications. The authors would like to share their experience in using the digital human modeling software and make discussions on some common issues. A number of case studies from typical automotive manufacturing assembly operations are also presented to demonstrate the usage of the multi-parameter and boundary mannequin techniques.

This paper contains a review of methods for deriving risk curves from biomechanical data obtained from impact experiments on human surrogates. It covers many of the problems and pitfalls of obtaining realistic human risk curves from impact experiments. The strength and weakness of both parametric and non-parametric methods are evaluated. The limitations of standard analysis of censored impact test data are presented. Methods are given for determining risk curves from both doubly censored data and data obtained from impacts to body regions in which there are more than one mechanism of injury. A detailed set of examples is presented in which different experimental data are analyzed using the Consistent Threshold method and the logistic approach. Finally risk curves for published data are presented for the femur, head, thorax, and neck.

A major task of road and airfield maintenance for transportation departments in the Northern United States and in cold regions globally is snow removal. In addition, there is a service industry built on snowplow equipped light trucks to remove snow from vehicle serviceways and parking lots. Thus, a source of stresses on a truck frame are the forces applied by the plow. Unfortunately, very little research has been performed to provide design models that will predict these forces. In this paper, both theoretical and experimental work on developing expressions for snowplow forces will be discussed.

The pulse severities from various vehicle impact tests need to be assessed during the impact structure development and targeting stage to assure that the occupants can meet the injury criteria as required. The conventional method using TTZV (time to zero velocity), TDC (total dynamic crush), and G1/G2 (two stage averaged pulse) is often unable to give a quick and clear answer to the question being raised. A simple numerical tool is developed here to assess the pulse severity with a single parameter in which the severity is expressed as the amount of chest travel under a certain target restraint curve or chest A-D curve. The tool is applied to several front impact vehicle pulses to show the effectiveness. The new method developed here can be used to assess the pulse severity in an easy and objective way along with conventional parameters.

In 1998, Rouhana et al. described development of a new device, called the IR-TRACC (InfraRed - Telescoping Rod for Assessment of Chest Compression). In its original concept, the IR-TRACC uses two infrared LEDs inside of a telescoping rod to measure deflection. One LED serves as a light transmitter and the other as a light receiver. The output from the receiver LED is converted to a linear function of chest compression using an analog circuit. Tests have been performed with IR-TRACC units at various labs around the world since 1998. A first-generation IR-TRACC system was retrofit into a Q3 dummy by TNO. Similarly, a mid sized male Hybrid III dummy thorax and a small female Hybrid III dummy thorax have been designed by First Technology Safety Systems (FTSS) such that each contains 4 second-generation IR-TRACC units. The second-generation IR-TRACC is the result of continued development by FTSS, especially in the areas of the analysis circuit, manufacturing and calibration methods.

This study will analyze existing procedures and commercially available testing equipment for low temperature impact testing of plastic materials. The results of this analysis will be used to identify continuous improvement opportunities and develop recommended practices for low temperature impact testing to support ongoing efforts to meet related durability and performance needs of automotive components.

It is commonly known that in an automotive manufacturing assembly line several workers perform either a common task or a number of different tasks simultaneously, and there is a need to represent such a multi-worker operation realistically in a digital environment. In the past years, most digital human modeling applications were limited only in a single worker case. This paper presents how to simulate multi-worker operations in a digital workcell. To establish an effective communication and interaction between the mannequins, some existing commercial software package has provided a digital input/output mechanism. The motion for each mannequin is often programmed independently, but can be interrupted anytime by the other digital human models or devices via a communication channel.

With the rapid development of artificial intelligence, the autonomous vehicles (AV) have attracted considerable attention in the automotive industry. However, different factors negatively impact the adoption of the AVs, delaying their successful commercialization. Accretion of atmospheric icing, especially wet snow, on AV sensors causes blockage on their lenses, making them prone to lose their sight, in turn, increasing potential chances of accidents. In this study, two different designs are proposed in order to prevent snow accretion on the lenses of AVs via air flow across the lens surface. In both designs, lenses made of plain glass and superhydrophobic coated glass surfaces are tested. While some researchers have shown promise of water repellency on superhydrophobic surfaces, more snow accretion is observed on the superhydrophobic surfaces, when compared to the plain glass lenses.

It is often necessary to measure three-axis displacement of a deforming or moving part in static or dynamic impact tests. A point moving in the three-dimensional space can be monitored and measured using three string-pots or other distance measuring devices with a methodology developed here. A numerical algorithm along with required equations are shown and discussed. The algorithm was applied as an example to static seat pull test and compared to results from film analysis. The application with string pots is useful especially when the point of concern gets hidden or blocked by other parts disabling the photogrammetry technology.

A new approach for improving estimates of the kinematic response of ATDs (anthropomorphic test devices) to vehicle crash events has been developed. This approach employs the Kalman Filter; a state model based estimation approach that has been widely applied to system dynamics problems ranging from navigation to missile guidance. The Kalman Filter approach combines measurements of crash event phenomena (acceleration and displacement), kinematic models of ATD behavior and statistics of sensor noise to create precise estimates of ATD motion during a crash. This paper presents an implementation of a state model and Kalman Filter for a sensor data collected from the chest of an ATD during an out-of-position airbag deployment test. Favorable comparisons are made between the Kalman Filter model approach and traditional methods involving numerical integration and differentiation.

The effects of vehicle “stiffness” and mass on the occupant response during a crash may be determined by evaluation of accident data. However, “stiffness” and mass may be correlated, making it difficult to separate their effects. In addition, a single-valued “stiffness”, although well defined for linear case, is not well defined for non-linear systems, such as in vehicle crash, making the separation task even more difficult. One approach to addressing the lack of a clear definition of stiffness is to use multiple definitions. Each stiffness definition can then be correlated with mass to look for trends. In this study, such an approach was taken, and the different stiffness definitions were given and their values were obtained from rigid barrier crash test data. No clear relationship between mass and stiffness appears to exist. All the stiffness measures reviewed show, at best, only a weak correlation with mass. A stiffness analysis among different vehicle types was also carried out.