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Fasteners, commonly used in automotive industry, play an important role in the safety and reliability of the vehicle structural system. In practical application, bolted joints would never undergo fully reversed loading; there always will be positive mean stress on bolt. The mean stress has little influence on the fatigue life if the maximum stress is lower than a threshold which is near the yield stress of the bolt. However, when the sum of the mean stress and the stress amplitude exceeds the threshold, the endurance limit stress amplitude decreases fast as the mean stress increases. The purpose of this paper is to research the fatigue endurance limit of a fastener and establish the threshold for safe design in automotive application. In order to obtain the fatigue endurance limit at different mean stress levels, various mechanical tests were performed on M12x1.75 and M16x1.5 Class 10.9 fasteners using MTS test systems.

The complexities involved in an optimization problem at a system level require knowledge base that has information on different approaches and customization of these approaches to a specific class of the optimization problems. One approach that is commonly used is the metamodel based design optimization. The metamodel is 1) a conceptual model for capturing, in abstract terms, essential characteristics of a given optimization problem, and 2) a schema of sufficient formality to enable the problem modeled to be serialized to statements in a concrete optimization language [1]. Optimization is performed based on this metamodel. This metamodel approach has been proven effective and accurate in providing the global optimum. Depending upon the computational hardware availability in an organization, the metamodel based optimization could be much faster way of achieving the optimized solution. However, the accuracy of the optimization is highly dependent on the quality of metamodel generated.

Multiaxial loading on mechanical products is very common in the automotive industry, and how to design and analyze these products for durability becomes an important, urgent task for the engineering community. Due to the complex nature of the fatigue damage mechanism for a product under multiaxial state of stresses/strains which are dependent upon the modes of loading, materials, and life, modeling this behavior has always been a challenging task for fatigue scientists and engineers around the world. As a result, many multiaxial fatigue theories have been developed. Among all the theories, an existing equivalent stress theory is considered for use for the automotive components that are typically designed to prevent Case B cracks in the high cycle fatigue regime.

To cope with the increasing number of advanced features (e.g., smart-phone integration and side-blind zone alert.) being deployed in vehicles, automotive manufacturers are designing flexible hardware architectures which can accommodate increasing feature content with as fewer as possible hardware changes so as to keep future costs down. In this paper, we propose a formal and quantitative definition of flexibility, a related methodology and a tool flow aimed at maximizing the flexibility of an automotive hardware architecture with respect to the features that are of greater importance to the designer. We define flexibility as the ability of an architecture to accommodate future changes in features with no changes in hardware (no addition/replacement of processors, buses, or memories). We utilize an optimization framework based on mixed integer linear programming (MILP) which computes the flexibility of the architecture while guaranteeing performance and safety requirements.

Current manufacture of alternative energy sources for automobiles, such as fuel cells and lithium-ion batteries, uses repeating energy modules to achieve targeted balances of power and weight for varying types of vehicles. Specifically for lithium-ion batteries, tens to hundreds of identical plastic parts are assembled in a repeating fashion; this assembly of parts requires complex dimensional planning and high degrees of quality control. This paper will address the aspects of dimensional quality for repeated, injection molded thermoplastic battery components and will include the following: First, dimensional variation associated with thermoplastic components is considered. Sources of variation include the injection molding process, tooling or mold, lot-to-lot material differences, and varying types of environmental exposure. Second, mold tuning and cavity matching between molds for multi-cavity production will be analyzed.

Roof racks are designed for carrying luggage during customers' travels. These rails need to be strong enough to be able to carry the luggage weight as well as be able to withstand aerodynamic loads that are generated when the vehicle is travelling at high speeds on highways. Traditionally, roof rail gage thickness is increased to account for these load cases (since these are manufactured by extrusion), but doing so leads to increased mass which adversely affects fuel efficiency. The current study focuses on providing the guidelines for strategically placing lightening holes and optimizing gage thickness so that the final design is robust to noise parameters and saves the most mass without adversely impacting wind noise performance while minimizing stress. The project applied Design for Six Sigma (DFSS) techniques to optimize roof rail parameters in order to improve the load carrying capacity while minimizing mass.

ADA Technologies, Inc. has designed and built a microgravity-tolerant portable fire extinguisher prototype for use in manned spacecraft and planetary habitats. This device employs Fine Water Mist (FWM) as the fire extinguishing agent, and is refillable from standard stores on long-duration missions. The design uses a single storage tank for minimal mass and volume. The prototype employs a dual-fluid atomizer concept where the pressurant gas (nitrogen) also enhances the water atomization process to generate a droplet size distribution in the optimum diameter range of 10 to 50 micrometers. The expanding discharge gas plume carries the mist to the immediate vicinity of the fire where its extensive surface area promotes high heat transfer rates. A series of 80 fire suppression tests was recently completed to evaluate design options for the hardware and validate performance on three representative fire scenarios.

Fine water mist has become a commercial technology for fire suppression in multiple applications. With funding from NASA, ADA Technologies, Inc. (ADA) is developing a handheld fine water mist fire extinguisher for use on manned spacecraft and in future planetary habitats. This design employs only water and nitrogen as suppression agents to allow local refill and reuse. The prototype design incorporates features to generate a uniform fine water mist regardless of the direction of the gravitational vector or lack of gravity altogether. The system has been proven to extinguish open fires and hidden fire scenarios in tests conducted at the Colorado School of Mines (CSM). This design can be deployed as a portable extinguisher or as an automated system for local fire protection in instrument racks or storage spaces. Continued development will result in prototype hardware suitable for use on future manned spacecraft.

Direct osmotic concentration (DOC) is an integrated membrane treatment process designed for the reclamation of spacecraft wastewater. The system includes forward osmosis (FO), membrane evaporation, reverse osmosis (RO) and an aqueous phase catalytic oxidation (APCO) post-treatment unit. This document describes progress in the third year of a four year project to advance hardware maturity of this technology to a level appropriate for human rated testing. The current status of construction and testing of the final deliverable is covered and preliminary calculations of equivalent system mass are funished.