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This document has been declared "CANCELLED" as of July 2008 and has been superseded by PRI AC7102/1. By this action, this document will remain listed in the Numerical Section of the Aerospace Standards Index noting that it is superseded by PRI AC7102/1. Cancelled specifications are available from SAE.

This Aerospace Standard (AS) establishes the requirements for suppliers of Nonconventional Machining Services to be accredited by the National Aerospace and Defense Contractors Accreditation Program (NADCAP). NADCAP accreditation is granted in accordance with SAE AS7003 after demonstration of compliance with the requirements herein. The requirements may be supplemented by additional requirements specified by the NADCAP Nonconventional Machining and Surface Enhancement (NMSE) Task Group. Using the corresponding Audit Criteria (PRI AC7116) will ensure that accredited Nonconventional Machining suppliers meet all of the requirements in this standard and all applicable supplementary standards. The purpose of this audit program is to assess a supplier's ability to consistently provide a product or service that conforms to the technical specifications and customer requirements.

This Aerospace Standard (AS) is to be used as a supplement to SAE AS7109. In addition to the requirements contained in AS7109, the requirements contained herein shall apply to suppliers seeking NADCAP Coatings accreditation who are engaged in thermal spray.

This SAE Aerospace Standard (AS) defines the requirements for air cycle air conditioning systems used on military air vehicles for cooling, heating, ventilation, and moisture and contamination control. General recommendations for an air conditioning system, which may include an air cycle system as a cooling source, are included in MIL-E-18927E and JSSG-2009. Air cycle air conditioning systems include those components which condition high temperature and high pressure air for delivery to occupied and equipment compartments and to electrical and electronic equipment. This document is applicable to open and closed loop air cycle systems. Definitions are contained in Section 5 of this document.

Abstract Letter from the Guest Editors

Abstract The objective of this article is to evaluate the effects of different blast protective modules to military vehicle structures and occupants. The dynamic responses of the V-shape integral basic armor, the add-on honeycomb sandwich structure module, and the anti-shock seat-dummy system were simulated and analyzed. The improvements of occupant survivability by different protective modules were compared using occupant injury criteria. The integral armored cab can maintain the integrity of the cab body structure. The add-on honeycomb sandwich armor reduces the peak structural deformation and velocity of the cab floor by 34.9% and 47.4%, respectively, compared with the cab with integral armors only. The integral armored cab with the anti-shock seat or the honeycomb sandwich structures reduces the occupant shock responses below the injury criteria. For different blast threat intensities, the selection of appropriate protective modules can meet protection requirements.

Abstract Autonomy has the potential to make the most radical impact by significantly reducing the number of soldiers in harm’s way and changing the military paradigm. Benefits of autonomy to improve the Army’s mission capabilities and the rapid evolution of military systems exerts pressure to develop these systems quickly. Since the associated technological development is highly fast paced and stochastic, approaches that develop systems for stochastic future scenarios are required. In this article we present a vision for the autonomous high-mobility military systems for that future. We discuss the ramifications of autonomy in five areas: (1) fleet organization, (2) physical attributes of high-mobility military systems, (3) individual behaviors of autonomous assets, (4) interactions between humans and autonomous systems, and (5) operation and teaming strategies. We present the future vision, implications, requirements, and technological challenges for each of the five areas.

This Aerospace Standard (AS) is to be used as a supplement to SAE AS7109. In addition to the requirements contained in AS7109, the requirements contained herein shall apply to suppliers seeking NADCAP Coatings accreditation who are engaged in stripping of coated material.

This document has been declared "CANCELLED" as of June 2017. By this action, this document will remain listed in the Numerical Section of the Aerospace Standards Index. Cancelled specifications are available from SAE.

After manufacture, every military vehicle experiences a unique history of dynamic loads, depending on loads carried, missions completed, etc. Damage accumulates in vehicle structures and components accordingly, leading eventually to failures that can be difficult to anticipate, and to unpredictable consequences for mission objectives. The advent of simulation-based fatigue life prediction tools opens a path to Digital Twin based solutions for tracking damage, and for gaining control over vehicle reliability. An incremental damage updating feature has now been implemented in the Endurica CL fatigue solver with the aim of supporting such applications for elastomer components. The incremental updating feature is demonstrated via the example of a simple transmission mount component. The damage state of the mount is computed as it progresses towards failure under a series of typical loading histories.

A common scenario in engineering design is the availability of several black-box functions that describe an event with different levels of accuracy and evaluation cost. Solely employing the highest fidelity, often the most expensive, black-box function leads to lengthy and costly design cycles. Multi-fidelity modeling improves the efficiency of the design cycle by combining information from a small set of observations of the high-fidelity function and large sets of observations of the low-fidelity, fast-to-evaluate functions. In the context of Bayesian optimization, the most popular multi-fidelity model is the auto-regressive (AR) model, also known as the co-kriging surrogate. The main building block of the AR model is a weighted sum of two Gaussian processes (GPs). Therefore, the AR model is well suited to exploit information generated by sources that present strong linear correlations.

Abstract Fighter pilots must study models of aircraft dynamics before learning complex maneuvers and tactics. Similarly, autonomous fighter aircraft applications may benefit from a model-based learning approach. Instead of using a preexisting physics model of a given aircraft, a machine learning system can learn a predictive model of the aircraft physics from training data. Furthermore, it can model interactions between multiple friendly aircraft, enemy aircraft, and the environment. Such a system can also learn to represent state variables that are not directly observable, as well as dynamics that are not hard coded. Existing model-based methods use a deep neural network that takes observable state information and agent actions as input and provides predictions of future observations as output. The proposed method builds upon this approach by adding a residual feedforward skip connection from some of the inputs to all of the outputs of the deep neural network.

In the early days, there were significant limitations to the build size of laser powder bed fusion (L-PBF) additive manufacturing (AM) machines. However, machine builders have addressed that drawback by introducing larger L-PBF machines with expansive build volumes. As these machines grow, their size capability approaches that of directed energy deposition (DED) machines. Concurrently, DED machines have gained additional axes of motion which enable increasingly complex part geometries—resulting in near-overlap in capabilities at the large end of the L-PBF build size. Additionally, competing technologies, such as binder jet AM and metal material extrusion, have also increased in capability, albeit with different starting points. As a result, the lines of demarcation between different processes are becoming blurred.

Materials play a key role in our day to day life and have shaped the industrial revolution to a great extent. Right selection of material for meeting a particular objective is the key to success in today’s world where the cost as well as sustainability of any equipment or a system have assumed greater significance than ever before. In automotive industry, materials have a definitive role as far as the mobility and safety is concerned. Materials that can absorb the required energy or impact can be manufactured through different manufacturing as well as metallurgical processes which involves appropriate heat treatment and bringing correct chemical compositions etc. However, they can also be formed by simpler methods such as combining certain materials together in the form of layered combinations to form light weight composites.

Fuel tank is considered as safety component in the vehicle, and it has to be tested to meet the safety requirements as per AIS 095. Earlier, fuel tanks were manufactured by using Hot dipped cold rolled steel material and the weld zones are applied with Anti-corrosive coating. Few fuel tanks were reported with Corrosion problems. The root cause analysis was carried out considering the raw material, manufacturing process, transpiration, storage and usage. As an improvement, the new fuel tank is designed to eliminate the limitations of the existing fuel tank. 3D modeling was done to check space and mounting requirement in the layout and used for volume calculations. FE analysis was performed to check structural stability. Emphasis given on Interchange-ability to cater the new fuel tanks in place of old as spares requirement. The fuel tank has developed with Alumina steel material.

This document has been declared "CANCELLED" as of April 2005 and has been superseded by PRI AC7108/2. By this action, this document will remain listed in the Numerical Section of the Aerospace Standards Index noting that it is superseded by PRI AC7108/2. Cancelled specifications are available from SAE.

Almost 75% of all elements are metals. Metals can be classified as either ferrous or non-ferrous and generally conduct electricity and heat well. Most metals are malleable and ductile and are, in general, heavier than other elemental substances. The following six eLearning courses are included in the Materials bundle. Each course is approximately one-hour in duration. See topics/outline for additional details. Introduction to Metals, Ferrous Metals, Nonferrous Metals, Classification of Steel, Essentials of Heat Treatment of Steel Exotic Alloys

Game-changing opportunities abound for the application of vehicle health management (VHM) across multiple transportation-related sectors, but key unresolved issues continue to impede progress. VHM technology is based upon the broader field of advanced analytics. Much of traditional analytics efforts to date have been largely descriptive in nature and offer somewhat limited value for large-scale enterprises. Analytics technology becomes increasingly valuable when it offers predictive results or, even better, prescriptive results, which can be used to identify specific courses of action. It is this focus on action which takes analytics to a higher level of impact, and which imbues it with the potential to materially impact the success of the enterprise. Artificial intelligence (AI), specifically machine learning technology, shows future promise in the VHM space, but it is not currently adequate by itself for high-accuracy analytics.

Abstract To assist in initializing the conceptual design of hypersonic aircraft, we outline a new, systematic framework based on historical aircraft data and primarily composed of design data and regression models. It is a rapid, low-fidelity analysis to provide a starting point for the conceptual design process by (1) assessing the performance capabilities of four types of high-speed aircraft, (2) providing initial estimates for weights and geometry with uncertainty, and (3) exploring how changes in these affect performance within design spaces. Using this framework, an initial set of reasonable aircraft configurations is obtained based on speed, altitude, and payload requirements, which can serve to accelerate the design process and avoid unforeseen problems later in the design cycle. An example is provided to demonstrate the application of the framework to launch the conceptual design of a new hypersonic aircraft with a given set of mission requirements.