Search Results

Parts, such as bolts, turbine wheels, discs, buckets, and blades, for high strength and oxidation resistance up to 1500 F when suitably heat treated.

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

This specification covers established metric manufacturing tolerances applicable to aluminum alloy drawn tubing ordered to metric dimensions. These tolerances apply to all conditions, unless otherwise noted. The term "excl" applies only to the higher figure of the specified range.

This specification covers established metric manufacturing tolerances applicable to aluminum alloy drawn tubing ordered to metric dimensions. These tolerances apply to all conditions, unless otherwise noted. The term "excl" applies only to the higher figure of the specified range.

This specification covers a corrosion and heat resistant nickel alloy in the form of sheet, strip, and plate procured in SI (metric) units.

This specification covers a corrosion and heat resistant nickel alloy in the form of sheet, strip, and plate procured in SI (metric) units.

This specification covers a corrosion and heat resistant nickel alloy in the form of sheet, strip, and plate procured in SI (metric) units. AMS 5598 is the equivalent, specified in inch/pound units, of this MAM.

The field of motor vehicle rollover research and testing has been one of multiple and varied approaches, dating back to at least the 1930's. The approach has been as simple as tipping a vehicle over at the top of a steep hill ( Wilson et al., 1972 ), to as complex as releasing a vehicle from an elevated roll spit mounted to the rear of a moving tractor and trailer ( Cooper et al., 2001 and Carter et al., 2002 ). Presenter Peter Luepke, P Luepke Consulting

Real-time simulation of truck and trailer combinations can be applied to hardware-in-the-loop (HIL) systems for developing and testing electronic control units (ECUs). The large number of configuration variations in vehicle and axle types requires the simulation model to be adjustable in a wide range. This paper presents a modular multibody approach for the vehicle dynamics simulation of single track configurations and truck-and-trailer combinations. The equations of motion are expressed by a new formula which is a combination of Jourdain's principle and the articulated body algorithm. With the proposed algorithm, a robust model is achieved that is numerically stable even at handling limits. Moreover, the presented approach is suitable for modular modeling and has been successfully implemented as a basis for various system definitions. As a result, only one simulation model is needed for a large variety of track and trailer types.

The use of Engine Health Management (EHM) systems has been growing steadily in both the civilian and the military aerospace sectors. Barring a few notable exceptions (such as certain temperature and thrust margin monitoring) regulatory authorities around the world have not required these systems to be certified in any way. This is changing rapidly. New airframes and engines are increasingly being designed with the assumption that EHM will be an integral part of the way customers will operate these assets. This leads to a need for better guidelines on how such systems should be certified. The SAE E-32 committee on Propulsion System Health Monitoring is leading an industry-wide effort to develop a set of guidelines for certifying EHM systems.

The presentation describes technology developments and the integration of these technologies into new emission control systems. As in other years, the reader will find a wide range of topics from various parts of the world. This is reflective of the worldwide scope and effort to reduce diesel exhaust emissions. Topics include the integration of various diesel particulate matter (PM) and Nitrogen Oxide (NOx) technologies as well as sensors and other emissions related developments. Presenter Atsuo Kondo, NGK Insulators, Ltd.

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.

In Aeronautic industry, when we launch a new industrialization for an aircraft sub assembly we always have the same questions in mind for drilling operations, especially when focusing on lean manufacturing. How can we avoid dismantling and deburring parts after drilling operation? Can a drilling centre perform all the tasks needed to deliver a hole ready to install final fastener? How can we decrease down-time of the drilling centre? Can a drilling centre be integrated in a pulse assembly line? How can we improve environmental efficiency of a drilling centre? It is based on these main drivers that AIRBUS has developed, with SPIE and SOS, a new generation of drilling centre dedicated for hard materials such as titanium, and high thicknesses. The first application was for the assembly of the primary structure of A350 engine pylons. The main solution that was implemented meeting several objectives was the development of orbital drilling technology in hard metal stacks.

Impact of driving patterns on fuel economy is significant in hybrid electric vehicles (HEVs). Driving patterns affect propulsion and braking power requirement of vehicles, and they play an essential role in HEV design and control optimization. Driving pattern conscious adaptive strategy can lead to further fuel economy improvement under real-world driving. This paper proposes a real-time driving pattern recognition algorithm for supervisory control under real-world conditions. The proposed algorithm uses reference real-world driving patterns parameterized from a set of representative driving cycles. The reference cycle set consists of five synthetic representative cycles following the real-world driving distance distribution in the US Midwestern region. Then, statistical approaches are used to develop pattern recognition algorithm. Driving patterns are characterized with four parameters evaluated from the driving cycle velocity profiles.