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In the automotive industry, FMEA occurrence ranking is made to a standard such as SAE J1739. The SAE J1739 standard, as does other comparative standards, provides numerical probability criteria to aid ranking. Problems arise when the part or system under analysis is new, and there is no field data to estimate the probability of failure occurrence. Attempts to use qualitative verbal criteria or to go by the “feel” often result in inconsistency or large variability across and within FMEA projects. This paper presents a case study in which this problem was solved by the development of a tool that enables consistent - and efficient - FMEA occurrence rankings. The tool takes input from the user in the form of multiple-choice answers and calculates the final solution.

In 1972, the first SAE paper describing the use of computer simulation as a design tool for automotive air conditioning was written by these authors. Since then, many such simulations have been used and new tools such as CFD have been applied to this problem. This paper reviews the work over that past 35 years and presents several of the improvements in the basic component and system models that have occurred. The areas where “empirical” information is required for model support and the value of CFD cabin and external air flow modeling are also discussed.

Pedestrian finite element models (PFEM) are used to investigate and predict the injury outcomes from vehicle-pedestrian impact. As postmortem human surrogates (PMHS) differ in anthropometry across subjects, it is believed that the biofidelity of PFEM cannot be properly evaluated by comparing a generic anthropometry model against the specific PMHS test data. Global geometric personalization can scale the PFEM geometry to match the height and weight of a specific PMHS, while local geometric personalization via morphing can modify the PFEM geometry to match specific PMHS anatomy. The goal of the current study was to evaluate the benefit of morphed PFEM compared to globally-scaled and generic PFEM by comparing the kinematics against PMHS test results. The AM50 THUMS PFEM (v4.01) was used as a baseline for anthropometry, and personalized PFEM were created to the anthropometric specifications of two obese PMHS used in a previous pedestrian impact study using a mid-size sedan.

Some rollover testing methodologies require specification of vehicle kinematic parameters including travel speed, vertical velocity, roll rate, and pitch angle, etc. at the initiation of vehicle to ground contact, which have been referred to as touchdown conditions. The complexity of the vehicle, as well as environmental and driving input characteristics make prediction of realistic touchdown conditions for rollover crashes, and moreover, identification of parameter sensitivities of these characteristics, is difficult and expensive without simulation tools. The goal of this study was to study the sensitivity of driver input on touchdown parameters and the risk of rollover in cases of steering-induced soil-tripped rollovers, which are the most prevalent type of rollover crashes. Knowing the range and variation of touchdown parameters and their sensitivities would help in picking realistic parameters for simulating controlled rollover tests.

The application of optical diagnostics in turbulent reactive flows often suffers from the beam steering (BS) effects, resulting in degraded image quality and/or measurement accuracy. This work investigated a method to correct the BS effects to improve the accuracy of optical diagnostics, with particle imagine velocimetry (PIV) measurements on turbulent reactive flames as an example. The proposed method used a guiding laser to correct BS. Demonstration in laboratory turbulent flames showed promising results where the accuracy of PIV measurement was significantly enhanced. Applicability to more complicated and practical situations are discussed.