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Induction machines (IM) are considered work horse for industrial applications due to their rugged, reliable and inexpensive nature; however, their low power density restricts their use in volume and weight limited environments such as an aerospace, traction and propulsion applications. Given recent advancements in additive manufacturing technologies, this paper presents opportunity to improve power density of induction machines by taking advantage of higher slot fill factor (SFF) (defined as ratio of bare copper area to slot area) is explored. Increase in SFF is achieved by deposition of copper in much more compact way than conventional manufacturing methods of winding in electrical machines. Thus a design tradeoff study for an induction motor with improved SFF is essential to identify and highlight the potentials of IM for high power density applications and is elaborated in this paper.

This specification covers premium quality bolts and screws made of 6Al - 4V titanium alloy.

AS9131 - This standard defines the common nonconformance data definition and documentation that an internal or external supplier or sub-tier supplier must submit when informing a customer of a nonconformity. The requirements shall be are applicable for reporting a nonconforming product to the owner/operator (i.e., end item user), if specified by contract. Reporting of nonconformance data, either electronically or conventionally on paper, is subject to the terms and conditions of the contract. This also includes, where applicable, data access under export control regulations.

This is the Microsoft Word® version of AS9101D, which defines the content and the presentation of the Assessment Report for the AS9100 standard. AS9101DW is an historical document; it has been superseded by AS9101E (note: there is not a Word version of this standard).

This is the Microsoft Word® version of AS9101C, which defines the content and the presentation of the Assessment Report for the AS9100 standard. AS9101CW is an historical document; a newer version, AS9101DW, exists.

ARINC 800 is the first industry standard intended for characterization of aviation-grade high-speed (Gbps) Ethernet links. The test methods are based on realistic representation of cabin networks. The notional cabling architecture is based on IFE seat distribution using multiple intermediate disconnects. Sequential testing is supported by building up number of connectors in the link. Test guidelines for mixed intermediate cable lengths are provided.

This document defines general practices for testing the physical layer of a fiber optic cable system. It is the intention of this document to outline proven practices for engineers and technicians engaged in testing and supporting fiber optic cable systems in aircraft. This document defines general practices for testing the physical layer of a fiber optic cable system. It is the intention of this document to outline proven practices for engineers and technicians engaged in testing and supporting fiber optic cable systems in aircraft.

Given the fast changing market demands, the growing complexity of features, the shorter time to market, and the design/development constraints, the need for efficient and effective verification and validation methods are becoming critical for vehicle manufacturers and suppliers. One such example is fault-tree analysis. While fault-tree analysis is an important hazard analysis/verification activity, the current process of translating design details (e.g., system level and software level) is manual. Current experience indicates that fault tree analysis involves both creative deductive thinking and more mechanical steps, which typically involve instantiating gates and events in fault trees following fixed patterns. Specifically for software fault tree analysis, a number of the development steps typically involve instantiating fixed patterns of gates and events based upon the structure of the code. In this work, we investigate a methodology to translate software programs to fault trees.

The increasing complexity of aerospace products and programs and the growing competitive pressure is facilitating the aggregation of small, medium and large enterprises of certain geographical regions into more integrated and collaborative entities (clusters). Clusters are by their same nature formed by heterogeneous companies, with huge differences not only in size but also for their core competences: such a diversity is a strength of the cluster, but it also increases its complexity. The purpose of this paper is to describe a benchmarking methodology that can be adopted to assess the performances of companies belonging to a cluster from different perspectives: economics and financials, competitive differentiators, specific know how, business strategies, production and logistic effectiveness, quality of core and supporting processes.

In this presentation we will present a COTS solution for an ARINC 653 IMA based system. It will cover IMA concepts from an OS point of view and show how a platform can be built for application development. It will also cover DO-297, and how that can isolate applications for certification and test purposes and allow for easy configuration of multiple applications between different development teams. Presenter Alex Wilson, Wind River

“Spotlight on Design: Insight” features an in-depth look at the latest technology breakthroughs impacting mobility. Viewers are virtually taken to labs and research centers to learn how design engineers are enhancing product performance/reliability, reducing cost, improving quality, safety or environmental impact, and achieving regulatory compliance. The quality of fluids used in aviation, such as oil or fuel, is an extremely important safety issue. One way to reliably monitor fluids is through the use of special measurement sensors. In the episode “Fluid Measurements and Avionics” (9:13), an engineer at Meggitt demonstrates the capabilities of time-domain reflectometry sensors, explaining how they are assembled and used. The business case for monitoring oil and fuel degradation, and how to proactively take advantage of preventative maintenance is also explained.

Simulation-based tolerance analysis is the accepted standard for dimensional engineering in aerospace today. Sophisticated 3D model-based tolerance analysis processes enable engineers to measure variation in complex, often large, assembled products quickly and accurately. Best-in-class manufacturers have adopted Quality Intelligence Management tools for collecting and consolidating this measurement data. Their goal is to completely understand dimensional fit characteristics and quality status before commencing the build process. This results in shorter launch cycles, improved process capabilities, reduced scrap and less production downtime. This paper describes how to use simulation-based approaches to correlate the theoretical tolerance analysis results produced during engineering simulations to actual as-built results. This allows engineers to validate or adjust as-designed simulation parameters to more closely align to production process capabilities.