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This course is verified by Probitas as meeting the AS9104/3A requirements for Continuing Professional Development. Project Management and Advanced Product Quality Planning (APQP) are two critical techniques used in product development in the mobility industry today. This course will bring these techniques together in an easy to understand format that goes beyond the typical concept of constructing timelines and project planning, by exploring not only the Automotive APQP process, but also key aspects of PM processes.

Abstract Letter from the Guest Editors

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.

Abstract Presently, 270 V direct current (DC) systems replace older 28 V DC voltage systems in both the civil and military aviation industry due to the requirement for more electrical power needs on board. Therefore, the existing avionics require retrofitting. The conversion from 270 V to 28 V appears to be quite promising for both old and new systems. This study aims to design an interleaved synchronous modular buck converter topology as a candidate for these requirements. Calculations for the converter design are conducted considering aviation standards. Switching with pulse-width modulation (PWM) is used to control the power converter. A double-loop feedback control system based on voltage and current feedback is designed. Therefore, the buck converter circuit with 1145 W power output is proposed, which supplies a 28 V and 41 A DC output from a 270 V DC input. The concept is verified using simulations and hardware-in-the-loop (HIL) experimental results.

This paper presents a Military Space Plane design concept. While the current military space plane activity is focused on rocket-powered concepts, the concept presented here is powered by a rocket-based combined cycle engine that uses both rocket and air-breathing engine cycles. The design concept is the reference SSTO design concept used in the NASA HRST ANSER study. The reference concept is a derivative of the NASA air-breathing Access to Space study SSTO design concept. The Access to Space air-breathing vehicle's combined cycle engine was replaced by the Aerojet rocket-based combined cycle engine. The orbital performance capability of the reference design concept is presented for 100 n mi., polar, and 225 n mi., 51 deg. orbits. The sensitivity of GTOW to payload and margin is also presented.

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.

This SAE Aerospace Information Report (AIR) is prepared for stakeholders seeking information about the evolution, integration, and approval of SHM technologies for military aircraft systems. The report provides this information in the form of (a) two military organizations’ perspectives on requirements, and (b) general SHM challenges and industry perspectives. The report only provides information to generate awarness of prespectives for military aircraft and, hence, assists those who are involved in developing SHM systems understanding the broad range of regulations, requirements, and standards published by military organizations that are available in the public domain from the military organizations.

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.

Additive manufacturing (AM) technology, also known as 3D printing, has transitioned from concepts and prototypes to part-for-part substitution and the creation of unique AM-specific part geometries. These applications are increasingly present in demanding, mission-critical fields such as medicine and aerospace, which require materials with certain thermal, stiffness, corrosion, and static loading properties. To advance in these arenas, metallic, ceramic, and polymer composite AM parts need to be free from discontinuities. The manufacturing processes have to be stable, robust, and repeatable. And the nondestructive testing (NDT) technology and inspection methods will need to be sufficiently capable and reliable to ensure that discontinuities will be detected to prevent the components from being accepted for use. As the second installment of a six-part series of SAE EDGE™ Research Reports on AM, this one discusses the need, challenges, technologies, and opportunities for NDT in AM.

This interface standard applies to fuzes used in airborne weapons that use a 3-in fuze well. It defines: Physical envelope of the fuze well at the interface with the fuze. Load bearing surfaces of the fuze well. Physical envelope of the fuze and its connector. Mechanical features (e.g., clocking feature). Connector type, size, location and orientation. Retaining ring and its mechanical features (e.g., thread, tool interface). Physical envelope of the retaining ring at the interface with the fuze. Physical space available for installation tools. Torque that the installation tool shall be capable of providing. This standard does not address: Materials used or their properties. Protective finish. Physical environment of the weapon. Explosive interface or features (e.g., insensitive munitions (IM) mitigation). Charging tube. Torque on the retaining ring or loads on the load bearing surfaces.

The “holy grail” for prognostics and health management (PHM) professionals in the aviation sector is to have integrated vehicle health management (IVHM) systems incorporated into standard aircraft maintenance policies. Such a change from current aerospace industry practices would lend credibility to this field by validating its claims of reducing repair and maintenance costs and, hence, the overall cost of ownership of the asset. Ultimately, more widespread use of advanced PHM techniques will have a positive impact on safety and, for some cases, might even allow aircraft designers to reduce the weight of components because the uncertainty associated with estimating their predicted useful life can be reduced. We will discuss how standard maintenance procedures are developed, who the various stakeholders are, and – based on this understanding - outline how new PHM systems can gain the required approval to be included in these standard practices.

Mass is one important suspicious object for breast cancer diagnosis in mammograms. Computer-aided detection (CAD) based on fully supervised deep learning achieves high performance for mass detection in mammograms. The lack of fine-grained expert labels becomes the bottleneck for the large-scale application of CAD to achieve detection in mammograms. Weakly supervised methods provide a solution to tackle the annotation problems, including in the application for mass detection. However, previous works face the problem of insufficient localization information, which affect the ability of mass detection. In this paper, we propose a multi-view enhancing mass detection network (MVMDNet) with dual view inputs that contains craniocaudal (CC) and mediolateral oblique (MLO) view of mammograms, where different view features are interacted and fused to enhance localization information.

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.

As the complexity of systems expands with increasing emphasis for digital transformation, the aerospace industry is generating big data to meet customer requirements. The ability to that data to solve challenging problems is limited by many factors, including the capabilities of current classical computing systems. Impact of Quantum Computing in Aerospace discusses how quantum computing systems offer (possibly quadratic to exponentially) greater computational power over classical computers. The power of quantum computing is tremendous and has many potential impacts on the aerospace industry; however, there are also many unsettled topics surrounding the future of the technology. Click here to access the full SAE EDGETM Research Report portfolio.

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.

This document includes a standard set of management practices that can be used, or espoused, by the OEMs for use during the design and development of electronic systems to mitigate the effects of future Diminishing Manufacturing Sources and Material Shortages (DMSMS). While this document focuses primarily on microelectronic devices, the methods described here may also apply to other commodities.

Abstract - The Warrior Injury Assessment Manikin (WIAMan) was developed to assess injury in Live Fire Test and Evaluation (LFTE) and laboratory development tests of vehicles and vehicle technologies subjected to underbody blast (UBB) loading. While UBB events impart primarily vertical loading, the occupant location in the vehicle relative to the blast can result in some inherent non-vertical, or off-axis loading. In this study, the WIAMan Technology Demonstrator (TD) was subjected to 18 tests with a 350g, 5-ms time duration drop tower pulse using an original equipment manufacturer (OEM) energy attenuating seat in four conditions: purely vertical, 15° forward tilt, 15° rearward tilt, and 15° lateral tilt to simulate the partly off-axis loading of an UBB event. The WIAMan TD showed no signs of damage upon inspection. Time history data indicates the magnitude, curve shape, and timing of the response data were sensitive to the off-axis loading in the lower extremity, pelvis, and spine.

This Aerospace Standard (AS) is to be used to supplement AS7108. In addition to the requirements contained in AS7108, the requirements contained herein shall apply to suppliers seeking NADCAP accreditation for painting and dry film coatings.

Abstract The demand for contactless, rapid manufacturing has increased over the years, especially during the COVID-19 pandemic. Additive manufacturing (AM), a type of rapid manufacturing, is a computer-based system that precisely manufactures products. It proves to be a faster, cheaper, and more efficient production system when integrated with cloud-based manufacturing (CBM). Similarly, the need for semiconductors has grown exponentially over the last five years. Several companies could not keep up with the increasing demand for many reasons. One of the main reasons is the lack of a workforce due to the COVID-19 protocols. This article proposes a novel technique to manufacture semiconductor chips in a fast-paced manner. An algorithm is integrated with cloud, machine vision, sensors, and email access to monitor with live feedback and correct the manufacturing in case of an anomaly.