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Standard

Artificial Intelligence in Aeronautical Systems: Statement of Concerns

2021-04-30
CURRENT
AIR6988
This document reviews current aerospace software, hardware, and system development standards used in the certification/approval process of safety-critical airborne and ground-based systems, and assesses whether these standards are compatible with a typical Artificial Intelligence (AI) and Machine Learning (ML) development approach. The document then outlines what is required to produce a standard that provides the necessary accommodation to support integration of ML-enabled sub-systems into safety-critical airborne and ground-based systems, and details next steps in the production of such a standard.
Technical Paper

Artificial Intelligence Applications in Aerospace

1987-08-01
871540
This paper summarizes the technical and management strategy of the Boeing Commercial Airplane Company's Computing Management Organization for the application of Artificial Intelligence. The training to support the application development is described. A summary of typical applications is presented.
Technical Paper

Artificial Intelligence Application to Advanced ECLS Systems

1989-07-01
891503
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. ...The benefits of artificial intelligence are presented from both the expert system and learned system perspective.
Technical Paper

The Utilization of Artificial Intelligence for Turboprop Maintenance

1994-10-01
942152
This paper shows the methods, techniques and codes developed as Artificial Intelligence tools for turboprop maintenance. Diagnostics is the main area of maintenance considered while Expert Systems and Back Propagation Neural Networks are the Artificial Intelligence subjects discussed. ...Diagnostics is the main area of maintenance considered while Expert Systems and Back Propagation Neural Networks are the Artificial Intelligence subjects discussed. The codes allow consideration of the turboprop with different configurations.
Technical Paper

Artificial Intelligence in Air Cargo System

2022-05-26
2022-26-0022
This paper focuses on Artificial Intelligence (AI) implementation can reduce the inefficiency and inconsistency due to the manual intervention in cargo operation in different areas.
Technical Paper

Using Artificial Intelligence Methods to Predict Doses from Large Solar Particle Events in Space

2004-07-19
2004-01-2324
Since these dose-time profiles are nonlinear functions, the use of artificial neural networks as the forecasting mechanism is ideal. In this work we report on the status of development of a “nowcast” methodology that utilizes a set of artificial neural networks that can forecast profiles of dose versus time since event onset using dose and dose rate information obtained early on as the event begins. ...In this work we report on the status of development of a “nowcast” methodology that utilizes a set of artificial neural networks that can forecast profiles of dose versus time since event onset using dose and dose rate information obtained early on as the event begins.
Journal Article

Tool Wear Classification in Automated Drilling Operations of Aircraft Structure Components using Artificial Intelligence Methods

2022-03-08
2022-01-0040
Since the aircraft industry has a particularly high requirement for defect-free production of structural components, this paper presents a study on the online-detection of tool wear in automated drilling processes using a combination of external sensor technology and Artificial Intelligence methods. For this reason, a laboratory setup to conduct automatic drilling operations in fuselage material is introduced.
Collection

SAE International Journal of Aerospace 2022 Special Issue: Artificial Intelligence, Machine Learning, and Deep Learning in Aerospace

2022-10-14
Volume 15, Issue 2, 2022 All articles in this special issue have been carefully selected to cover critical aspects of artificial intelligence, machine learning, and deep learning in aerospace. Special Issue Editors: Dnyanesh Rajpathak, General Motors, USA Mark Roboff, SKYTHREAD, USA Huafeng Yu, Research & Technology, Boeing, USA Gautam Biswas, Vanderbilt University, USA The SAE International Journal of Aerospace is the preeminent source for peer-reviewed, cutting-edge engineering research within the aerospace industry.
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