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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.

In recent years, the increasing complexity of modern aerospace systems has driven the rapid adoption of robust Model-Based Systems Engineering (MBSE). MBSE is a development methodology centered around computational models, which are instrumental in supporting the design and analysis of intricate systems. In this context, the Architecture Analysis and Design Language (AADL) and Systems Modeling Language (SysML) are two prominent modeling languages for specifying and analyzing the structure and behavior of a cyber-physical system. Both languages have their own specific use cases and tool environments and are typically employed to model different aspects of system design. Although multiple software tools are available for transforming models from one language to another, their effectiveness is limited by fundamental differences in the semantics of each language.

Abstract Threat identification and security analysis have become mandatory steps in the engineering design process of high-assurance systems, where successful cyberattacks can lead to hazardous property damage or loss of lives. This article describes a novel approach to perform security analysis on embedded systems modeled at the architectural level. The tool, called Security Threat Evaluation and Mitigation (STEM), associates threats from the Common Attack Pattern Enumeration and Classification (CAPEC) library with components and connections and suggests potential defense patterns from the National Institute of Standards and Technology (NIST) Special Publication (SP) 800-53 security standard. This article also provides an illustrative example based on a drone package delivery system modeled in AADL.

This paper describes an approach to integrating high-fidelity vehicle dynamics with a high-fidelity gaming engine, specifically with respect to terrain. The work is motivated by the experimental need to have both high-fidelity visual content with high-fidelity vehicle dynamics to drive a motion base simulator. To utilize a single source of terrain information, the problem requires the just-in-time sharing of terrain content between the gaming engine and the dynamics model. The solution is implemented as a client-server with the gaming engine acting as a stateless server and the dynamics acting as the client. The client is designed to actively maintain a locally cashed terrain grid around the vehicle and actively refresh it by polling the server in an on-demand mode of operation. The paper discusses the overall architecture, the protocol, the server, and the client designs. A practical implementation is described and shown to effectively function in real-time.

Enhanced SATCOMs for Unmanned Aerial Systems The Bus Too Tough to Die Combating Infrared Threats on the Battlefield Optical Interconnect Design Challenges in Space High-Performance Computing for the Next-Generation Combat Vehicle Merging Antenna and Electronics Boosts Energy and Spectrum Efficiency Integrated Magneto-Optical Devices for On-Chip Photonic Systems Development of magneto-optical (MO) materials could lead to a range of nonreciprocal optical devices for emerging standardized photonic integrated circuit (PIC) fabrication processes. Low Power Optical Phase Array Using Graphene on Silicon Photonics Electrostatic doping of 2D materials embedded in waveguides could enable ultrafast devices with unprecedented power. Spatial Resolution and Contrast of a Focused Diffractive Plenoptic Camera New technology captures spectral and spatial information of a scene in one snapshot while raising pixel counts and improving image quality.

Beyond VMEbus - A New Concept Taming the Thermal Behavior of Solid-State Military Lasers Solving the Challenge of Thermal Design in Aerospace Electronics Improving Component Life in Abrasive, Corrosive Aerospace Environments New Pulse Analysis Techniques for Radar and EW Validation of Ubiquitous 2D Radar Converting Existing Copper Wire Firing System to a Fiber-Optically Controlled Firing System for Electromagnetic Pulsed Power Experiments Technological improvements make pulsed-power experiments with gunpowder- or air-driven guns safer. Low-Cost Ground Sensor Network for Intrusion Detection COTS-based system could provide increased level of security with less manpower. In-Network Processing on Low-Cost IoT Nodes for Maritime Surveillance Commercially available system of distributed wireless sensors could increase the Navy's intelligence collection footprint.

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This Human Systems Integration (HSI) Standard Practice identifies the Department of Defense (DoD) approach to conducting HSI programs as part of procurement activities. This Standard covers HSI processes throughout design, development, test, production, use, and disposal. Depending on contract phase and/or complexity of the program, tailoring should be applied. The scope of this standard includes prime and subcontractor HSI activities; it does not include Government HSI activities, which are covered in the DoD HSI Handbook. HSI programs should use the latest version of standards and handbooks listed below, unless a particular revision is specifically cited in the contract.

Engineering Events staff at SAE International in Warrendale, Pennsylvania, have extended the call for abstracts through September 21 for the organization’s AeroTech aerospace and defense technology conference, which will take place at the Fort Worth Convention Center in Fort Worth, Texas, March 14-16, 2023. Visit the AeroTech call for abstracts page for more information and to get started.

This SAE Aerospace Standard (AS) establishes guidelines for the use of IEEE-1394-2008 Beta (formerly IEEE-1394b) as a data bus network in military and aerospace vehicles. It encompasses the data bus cable and its interface electronics for a system utilizing S400 over copper medium over extended lengths. This document contains extensions/restrictions to “off-the-shelf” IEEE-1394 standards, and assumes that the reader already has a working knowledge of IEEE-1394. This document does not identify specific environmental requirements (electromagnetic compatibility, temperature, vibration, etc.); such requirements will be vehicle-specific and even LRU-specific. However, the hardware requirements and examples contained herein do address many of the environmental conditions that military and aerospace vehicles may experience. One should refer to the appropriate sections of MIL-STD-461E for their particular LRU, and utilize handbooks such as MIL-HDBK-454A and MIL-HDBK-5400 for guidance.

This standard defines requirements for the preparation and execution of the audit process. In addition, it defines the content and composition for the audit reporting of conformity and process effectiveness to the 9100-series standards, the organization's QMS documentation, and customer and statutory/regulatory requirements. The requirements in this standard are additions or represent changes to the requirements and guidelines in the standards for conformity assessment, auditing, and certification as published by ISO/IEC (i.e., ISO/IEC 17000, ISO/IEC 17021-1). When there is conflict with these standards, the requirements of the 9101 standard shall take precedence.

This document defines the minimum requirements for auditors, CBs, Auditor Authentication Bodies (AABs), Training Provider Approval Bodies (TPABs), and Training Providers (TPs) who participate in the IAQG Industry Controlled Other Party (ICOP) scheme. The requirements in this standard supplement those defined within the 9104/1, 9104/2, ISO/IEC 17021-1, and ISO/IEC 17021-3 standards. Data protection for the parties subject to this document and other relevant requirements of the ICOP scheme are managed via bi-lateral contracts between the joint controllers of the data.

This standard includes ISO 9001:20152 quality management system requirements and specifies additional aviation, space, and defense industry requirements, definitions, and notes. It is emphasized that the requirements specified in this standard are complementary (not alternative) to customer and applicable statutory and regulatory requirements. If there is a conflict between the requirements of this standard and customer or applicable statutory or regulatory requirements, the latter shall take precedence.

Success in metal additive manufacturing (AM) relies on the optimization of a large set of process parameters to achieve materials whose properties and performance meet design and safety requirements. Despite continuous improvements in the process over the years, the quality of AM parts remains a major concern for manufacturers. Today, researchers are starting to move from discrete geometry-dependent build parameters to continuously variable or dynamically changing parameters that are geometry- and scan-path aware. This approach has become known as “feedforward control.” Process Control for Defect Mitigation in Laser Powder Bed Fusion Additive Manufacturing discusses the origins of feedforward control, its early implementations in AM, the current state of the art, and a path forward to its broader adoption. Click here to access the full SAE EDGETM Research Report portfolio.

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.

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.

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.