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Metal additive manufacturing has high potential to produce automobile parts, due to its shape flexibility and unique material properties. On the other hand, residual stress which is generated by rapid solidification causes deformation, cracks and failure under building process. To avoid these problems, understanding of internal residual stress distribution is necessary. However, from the view point of measureable area, conventional residual stress measurement methods such as strain gages and X-ray diffractometers, is limited to only the surface layer of the parts. Therefore, neutron which has a high penetration capability was chosen as a probe to measure internal residual stress in this research. By using time of flight neutron diffraction facility VULCAN at Oak Ridge National Laboratory, residual stress for mono-cylinder head, which were made of aluminum alloy, was measured non-distractively. From the result of precise measurement, interior stress distribution was visualized.

This paper describes a simulation approach for the modeling of tandem external gear pumps. A tandem gear pump is the combination of two pumps with a common drive shaft. Such design architecture finds application in certain automotive transmission systems. The model presented in this work is applicable for pumps with both helical and spur gears. The simulation model is built on the HYGESim (HYdraulic GEars machines Simulator) previously developed by the authors for external spur gear units. In this work, the model formulation is properly extended to the capabilities of simulating helical gears. Starting directly from the CAD drawings of the unit, the fluid-dynamic model solves the internal instantaneous tooth space volume pressures and the internal flows following a lumped parameter approach. The simulation tool considers also the radial micro-motion of the gears, which influences the internal leakages and the features of the meshing process.

Increasing the strength of materials is effective in reducing weight and boosting structural part performance, but there are cases in where the residual strain generated during the process of manufacturing of high-strength materials results in a decline of durability. It is therefore important to understand how the residual strain in a manufactured component changes due to processing conditions. In the case of a connecting rod, because the strain load on the connecting rod rib sections is high, it is necessary to clearly understand the distribution of strain in the ribs. However, because residual strain is generally measured by using X-ray diffractometers or strain gauges, measurements are limited to the surface layer of the parts. Neutron beams, however, have a higher penetration depth than X-rays, allowing for strain measurement in the bulk material.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

This work introduces a new design algorithm to optimize progressively folding thin-walled structures and in order to improve automotive crashworthiness. The proposed design algorithm is composed of three stages: conceptual thickness distribution, design parameterization, and multi-objective design optimization. The conceptual thickness distribution stage generates an innovative design using a novel one-iteration compliant mechanism approach that triggers progressive folding even on irregular structures under oblique impact. The design parameterization stage optimally segments the conceptual design into a reduced number of clusters using a machine learning K-means algorithm. Finally, the multi-objective design optimization stage finds non-dominated designs of maximum specific energy absorption and minimum peak crushing force.

One primary concern with applying an AWD system to a front wheel drive (FWD) vehicle architecture is the additional weight and drag associated with the AWD drivetrain components, resulting in an increase in fuel consumption compared to FWD-only models. Therefore, Honda recently developed a next-generation integrated AWD unit that reduces weight and drag loss, and increases the SH-AWD cornering performance while maintaining the performance requirements of the previous rear drive unit. These targets were achieved primarily through the application of hydraulically-actuated clutches and an increase in the “speed-increasing ratio”. This paper describes the development, system validation and future technology implications of this recent advancement.

In many engineering domains like aerospace, vehicle or engine design the analysis of flow fields, acquired from computational fluid dynamics (CFD) simulations can reveal important insights on the behavior of the simulated objects. However, the huge amount of flow data produced by each simulation complicates the data processing and limits the application of data mining and machine learning tools for the flow analysis. The paper introduces a compact streamline and feature based representation of three dimensional flow fields, in order to overcome this limitation. The compact representation defines the basis for a subsequent quantification of flow field similarities.

Recently, ozone addition has come under scrutiny as a means of controlling ignition timing for Low Temperature (LTC) combustion, which defeats the NOx-PM tradeoff using a highly dilute, homogeneous mixture. This is because ozone decomposes into atomic oxygen and hydroxyl radicals that influence the early phases of the ignition delay process. In order to understand ozone's influence on combustion better, this work analyzes the effects of ozone-assisted combustion for a single-cylinder, direct-injection Compression Ignition engine via a mechanical pump-line-nozzle fuel system and an electronically controlled common-rail fuel injection system. Experimental outcomes indicate a relatively small influence of ozone for the mechanical injection system with a comparably decreased effect for the common rail system.