Fault Diagnosis, Detection and Reliability Enhancement in Aerospace Engineering

Dear Colleagues,

Reliability, resilience, and fault awareness have become foundational requirements in modern aerospace systems. As aircraft, spacecraft, launch vehicles, and autonomous aerial platforms evolve toward higher levels of autonomy, tighter system integration, and longer operational lifetimes, ensuring dependable performance under uncertainty is no longer optional. It is a system-level necessity spanning design, verification, operation, and maintenance.

This Special Issue invites original contributions that advance the theory, methods, and practical implementation of reliability analysis, fault detection and diagnosis, and fault-tolerant operation across the aerospace system lifecycle. Contributions may address individual subsystems or integrated architectures, with relevance to both airborne and spaceborne platforms, including crewed, uncrewed, and distributed systems.

Topics of interest encompass, but are not limited to, flight dynamics and control, guidance and navigation, propulsion and power systems, avionics and embedded software, communication and sensing networks, vibration failure mechanism of key components and systems, structural and thermal subsystems, and integrated mission management. Particular attention is given to approaches that account for subsystem coupling, cross-domain fault propagation, and system-of-systems behavior.

The Special Issue places strong emphasis on the use of artificial intelligence, machine learning, and hybrid physics-based/data-driven methods for fault diagnosis, predictive maintenance, health monitoring, and reliability enhancement. Submissions that propose interpretable, verifiable, and industry-ready solutions are especially encouraged. Of particular interest are methodologies that introduce quantitative reliability metrics and confidence measures applicable at component, subsystem, and system levels, enabling informed decision-making in safety-critical aerospace applications.

Both theoretical developments and experimentally validated studies are welcome, including digital twin frameworks, hardware-in-the-loop testing, and operational case studies that demonstrate robustness, scalability, and real-world applicability.

Topics of interest include, but are not limited to, the following:

• System-level reliability modeling and assessment for aerospace platforms.
• Fault detection, diagnosis, and isolation in multi-subsystem environments.
• Fault-tolerant guidance, navigation, and control for air and space vehicles.
• Reliability and health monitoring of propulsion, power, avionics, and sensing systems.
• Software reliability, cyber-physical resilience, and embedded system robustness.
• AI-, ML-, and hybrid model-based approaches to fault prediction and mitigation.
• Integrated sensor–actuator networks and distributed fault management.
• Digital twins, experimental validation, and benchmarking of fault management frameworks.
• Vibration failure mechanism of key components and systems

Dr. Sajad Saraygord Afshari
Dr. Enayatollahi Mina
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• aerospace systems reliability
• fault detection and diagnosis
• fault-tolerant systems
• health monitoring and prognostics
• artificial intelligence and machine learning
• cyber-physical systems
• autonomous and space systems