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With an initial focus on critical fight management systems, the committee will evaluate applications for AI usage in aviation and aerospace and will propose standards to support implementation and certification

The new Advanced Technology and Training Center (ATTC), which opened yesterday after a ribbon-cutting ceremony, will focus on breakthroughs in condition-based maintenance and the intersection of artificial intelligence (AI), robotics, and automation within that domain.

This document discusses guidelines for the development of Aircraft Systems leveraging AI capabilities, taking into account the overall aircraft operating environment and functions. This includes validation of requirements and verification of the design implementation for certification and product assurance and guidelines with the assessment of safety.

A “toolbox” approach to systematizing the application of AI tools is described. A recommended overall approach for successful application development is suggested.

However, this requires models based on the physics of the system to be built into the digital twin, links to data from sensors on the real live system, and sophisticated algorithms incorporating artificial intelligence (AI) and machine learning (ML). All of this can be used for integrated vehicle health management (IVHM) decisions, such as determining future failure, root cause analysis, and optimized energy performance. ...The Adoption of Digital Twins in Integrated Vehicle Health Management, however, still has a range of unsettled topics that cover technological reliability, data security and ownership, user presentation and interfaces, as well as certification of the digital twin’s system mechanics (i.e., AI, ML) for use in safety-critical applications. Click here to access the full SAE EDGETM Research Report portfolio.

The recent emergence of powerful artificial intelligence (AI) software development tools promises to reduce the time and effort associated with transforming an expert's knowledge into the operational software system required to implement automatic shutdown avoidance. ...To conduct an evaluation of the applicability of using AI techniques for life support processes, the National Aeronautics and Space Administration (NASA) developed a prototype expert system for automated fault detection, isolation, and correction of a regenerative carbon dioxide (CO2) removal subsystem.

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.

Innovations in Mobility: Aerospace Digital Summitaerospace mobility leaders convene leverage cutting-edge technology, design, develop safety measures, integrate current regulations, suggest future policies, expand markets, diversify revenue streams.

MIL-STD-1553, Aircraft Internal Time Division Command/Response Multiplex Data Bus, is a military standard which has become one of the basic standardization tools being used by the DOD for avionic interfaces. The standard describes the method of communication and the electrical interface requirements for devices using this standard. The 1 Mbps serial communication bus is the prime integration scheme for electronic devices in military avionics today. This paper addresses the application of the standard to military avionic integrations, describes the scope of the standard, the technical issues resolved in selecting the particular approach, and describes several military avionic examples using the standard.

The exploration of substantial money-saving areas of suitable usage for ECM (Electrochemical Metallizing) on aircraft components which are not in the purview of the original equipment manufacturer. The focus of the paper is upon the less spectacular maintenance opportunities rather than the much discussed repair of landing gear and engine components, all of which are strictly controlled by manufacturer's specifications because of safety considerations. Non-critical parts only require documented engineering specifications which are controlled by internal corporate engineering management. Our objective is to present areas of cost savings available to maintenance departments which have frequently been overlooked in the past. The perceived need is for some presentation of examples of applications which can be found in the normal day-to-day operations of aircraft maintenance activities so that similar opportunities may be identified and acted upon.

The Raytheon Company is testing a new artificial intelligence (AI) tool developed to help determine when the multi-mode radar installed on U.S. Air Force CV-22 tiltrotor aircraft is in need of service.

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

This document does not prescribe specific technologies or methodologies but rather provides guidelines applicable to a range of prognostic tools, from traditional physics-based models to advanced Artificial Intelligence (AI) / Machine-Learning (ML) based algorithms. It is designed to be adaptable and generic, accommodating the evolving nature of prognostic technologies in aviation maintenance.

Major improvements in gas-turbine engine life management and diagnostics can be achieved using artificial intelligence. More effective use of data collected in flight will be possible, post flight maintenance will be expedited, and unnecessary engine removals eliminated. Most importantly, real-time measurement of life consumption would enable the safe life of fracture critical components to be fully used before their retirement. A comprehensive on-board life measurement and diagnostics system for gas-turbine engines is necessary to support probabilistic design and life prediction methodologies for gas turbine engines and the introduction of two-level maintenance in the Air Force.

This SAE Aerospace Recommended Practice (ARP) examines the whole construct of an Engine Health Management (EHM) system. This keystone document gives a top-level view and addresses EHM description, benefits, and capabilities, and provides examples. This ARP purposely addresses a wide range of EHM architectures to demonstrate possible EHM design options. This ARP is not intended as a legal document and does not provide detailed implementation steps, but does address general implementation concerns and potential benefits. Other SAE documents (Aerospace Standards, Aerospace Recommended Practices, and Aerospace Information Reports) address specific component specifications, procedures and "lessons learned".

Space Station preliminary design studies examined the role of advanced automation and artificial intelligence to facilitate ECLSS control and diagnostics. Advanced automation techniques using independent embedded controllers were selected for the initial station, especially for centralized processes such as water recovery, air revitalization, and waste management. This paper examines the role that advanced computer capabilities can play to enhance advanced missions such as growth station, Moon and Mars exploration. The benefits of artificial intelligence are presented from both the expert system and learned system perspective.

The growth in global economies has led to a world that has become much more mobile in the last few decades. The number of enplanements has increased and is expected to continue to do so at an annual average rate of 1.8% through 2039 [1]. Prior to the COVID-19 pandemic, the number of aircraft in service was expected to increase annually to meet the travel demand. Next-generation, more-complex aircraft were scheduled to replace the older aircraft at a pace that still allowed sufficient capacity to meet the increasing demand. The events of 2020 have driven the industry to accelerate retirement of older aircraft while deferring the introduction of new aircraft. While the length of the industry recovery period cannot be predicted, most analysts believe that demand for travel will return once a vaccine is widely available.

This SAE Aerospace Information Report (AIR) offers an overview of the aspects of intellectual property (IP) protection, legislative compliance, business model, and technologies which need to be considered and addressed to implement a data interoperability, secure business model and technology platform to enable prognostics and health management (PHM) in the digital age. While this information report is restricted to the aerospace domain and also to commercial aviation, the concepts are applicable to any other domain that employs data for supporting health management functionality.

During the last year, the principles and predictive tools for this analyzer have been advanced beyond the nominal understanding considered heretofore acceptable for specialized uses of IMS. The importance and need for these advances reside in the creation of automated intelligence (to minimize the need for human resources) and in the formation of tools for the identification of chemicals not previously characterized by IMS. In our findings, IMS spectra were found to arise from considerations both of proton affinities in the initial event of ion creation and of ion stabilities in the non-equilibrium, uni-polar drift region. Aliphatic amines were systematically explored and kinetic measurements were made on ion stabilities and used in modeling the origins of ion mobility spectra. Neural networks were used to explore an existing data base and results revealed hitherto unknown properties of ion mobility spectra.

Interplanetary manned missions will change significantly the requirements imposed upon Life Support Systems (LSS) and specifically the requirements on LSS Automated Control Systems (ACS). During interplanetary manned missions the possibilities to control the operation of a specific system from the Ground Mission Control Center (GMCC) are diminished considerably. Therefore, this demands survivability and intelligent level enhancement LSS ACS.