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In an attempt to predict the responses of side crash pressure sensors, the Corpuscular Particle Method (CPM) was adopted and enhanced in this research. Acceleration-based crash sensors have traditionally been used extensively in automotive industry to determine the air bag firing time in the event of a vehicle accident. The prediction of crash pulses obtained from the acceleration-based crash sensors by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crash zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side impact applications.

An Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors in an attempt to assist pressure sensor algorithm development by using computer simulations. Acceleration-based crash sensors have traditionally been used to deploy restraint devises (e.g., airbags, air curtains, and seat belts) in vehicle crashes. The crash pulses recorded by acceleration-based crash sensors usually exhibit high frequency and noisy responses depending on the vehicle's structural design. As a result, it is very challenging to predict the responses of acceleration-based crash sensors by using computer simulations, especially those installed in crush zones. Therefore, the sensor algorithm developments for acceleration-based sensors are mostly based on physical testing.

This study demonstrates the use of pressure sensing technology to predict the crash severity of frontal impacts. It presents an investigation of the pressure change in the front structural elements (bumper, crush cans, rails) during crash events. A series of subsystem tests were conducted in the laboratory that represent a typical frontal crash development series and provided empirical data to support the analysis of the concept. The pressure signal energy at different sensor mounting locations was studied and design concepts were developed for amplifying the pressure signal. In addition, a pressure signal processing methodology was developed that relies on the analysis of the air flow behavior by normalizing and integrating the pressure changes. The processed signal from the pressure sensor is combined with the restraint control module (RCM) signals to define the crash severity, discriminate between the frontal crash modes and deploy the required restraint devices.

This work presents a study of crash energy and severity in frontal offset Vehicle-To-Vehicle (VTV) crash tests. The crash energy is analyzed based on analytical formulations and empirical data. Also, the crash severity of different VTV tests is analyzed and compared with the corresponding full frontal rigid barrier test data. In this investigation, the Barrier Equivalent Velocity (BEV) concept is used to calculate the initial impact velocity of frontal offset VTV test modes such that the offset VTV tests are equivalent to full frontal impact tests in terms of crash severity. Linear spring-mass model and collinear impact assumptions are used to develop the mathematical formulation. A scale factor is introduced to account for these assumptions and the calculated initial velocity is adjusted by this scale factor. It is demonstrated that the energies due to lateral and rotational velocity components are very small in the analyzed frontal VTV tests.

Understanding the variation in the deployment times for crash sensor systems is important to ensure robust performance of a crash sensor system. Increases in both the numbers of crash modes and deployable devices have reduced the margins for the decisions about when to deploy any given device. Currently, the industry practice is to run a sweep over the potential sources of variation, recording the minimum and maximum deployment time. Questions such as: “How often do the extremes occur?” or “Are there multiple peaks in the deployment time?” can not be answered. This work uses numerical analysis methods to build on the current sweep methodology to obtain information on the distribution of the deployment times so that questions such as these can be answered when evaluating sensor calibrations. The end result is better informed engineering decisions during the calibration development.

1 The fluid spray exits the nozzle in the form of a stream, which decays rapidly to ligaments that break up into droplets. All these transitions occur in a very short time and region. This work provides a fundamental analysis of the jet stability in general form, but it is devoted particularly to fluidic jets. Such jets exist in different industrial applications; automobile windshield washer and diesel fuel injector sprays are good examples. A computational analysis is developed that predicts the break up distance and velocity of the fluidic jets, which is one of the important factors that helps in prediction of the spray pattern and droplet strike location. Thus reduces number of the required prototypes and saves time and cost. Also, a parametric study is conducted to analyze the effect the jet breakup on the spray trajectory.

In the course of developing a body-on-frame vehicle for barrier crash performance, automotive manufacturers must take into account numerous regulatory and corporate requirements. One of the most common barrier crash modes is the perpendicular front barrier crash used to verify compliance to F/CMVSS 208. The frontal rail or “horn” is the primary component that absorbs a significant amount of the vehicle's crash energy. The frontal rail collapse determines the vehicle deceleration. This paper evaluates several frontal horn designs for perpendicular front barrier impacts. Two basic frontal rail architectures are evaluated: a uniform rectangular cross section and a tapered cross section. For a 35 mph (15.65 m/s) impact test condition, a parametric design study was commenced to evaluate the affect of gauges, convolutions, triggers, and initiating holes for a total of eleven configurations.

This research provides a fundamental study of the fluid mechanics of an automobile washer spray system from the reservoir to the windshield. A computational model is developed that specifies the strike location of the washer spray on the windshield. The model is useful to designers as an initial locator for nozzles, thus reducing wind-tunnel and road test time. A new algebraic model predicting the frequency and exit velocity of fluidic devices is successfully developed. It is generated by applying design of experiment and statistical regression analysis on a set of computational experimental data. The two phase flow (air and washer liquid) is modeled using the source panel method for the air flow and Newton’s Second Law to track the spray droplets. The numerical scheme is designed to simplify the complexity of the two-phase flow analysis and is thus computationally economical. The computational results have been compared with experimental tests.

The crush resistance of roof structures is critical to minimizing injuries and enhancing occupant survival during rollover crashes. Federal Motor Vehicle Safety Standard FMVSS 216 requires the roof structure to resist a load equal to one and one half (1&1/2) the unloaded weight of the vehicle during the first 127 millimeters (five inches) of deformation. This paper discusses the analytical methodologies applied and challenges encountered developing a hybrid Aluminum-Random Chop Material (RCM) roof structure. The roof structure materials are extruded 6260T6 aluminum and RCM. This hybrid roof structure has to satisfy not only the FMVSS 216 roof crush resistance, but also packaging, torsional stiffness and head impact requirements. Due to packaging constraints, the structure has to be developed without the roof bow at the B-pillar level.