Computing Methods for Aerospace Reliability Engineering

Dear Colleagues,

With the rapid progress in aerospace science and technology, structural complexity, functional integration, and environmental diversification have increasingly become the development trends in advanced aerospace equipment such as aircraft engines, steam turbines, satellites, drones, rockets, spacecraft, etc. Under harsh operating environments and multi-source uncertain factors, this advanced aerospace equipment may be subject to severe safety and reliability problems. Therefore, effective reliability analysis and design techniques for aerospace engineering systems are becoming extremely important. With the help of advanced mathematical approaches/tools, increasing interest is currently being paid to new computing methods to reveal accurate reliability modeling of aerospace engineering, from materials to components, and components to systems. In this case, novel computing methods and applications based on these advanced computational technologies are desired to provide more accurate and efficient reliability design for aerospace engineering systems.

This Special Issue would aim to establish a common understanding about the state of the field and draw a road map on where the research is heading, highlight the issues and discuss the possible solutions, and provide the data, models, and tools necessary to perform high-efficacy modeling and reliability design for aerospace engineering systems. Potential topics include, but are not limited to:

• Reliability evaluation
• Reliability-based optimization design
• Multidisciplinary design optimization
• Uncertainty modeling
• Uncertainty quantification
• Structural integrity
• Surrogate models
• Complex structural systems
• Artificial intelligence
• Evolutionary algorithms
• Fuzzy logic
• Interval modeling
• Mixed uncertainties
• Bayesian modeling
• Machine learning
• Deep learning
• Signal processing
• Data-driven/model-driven modeling
• Physics-informed modeling
• Neural network computing for aerospace

Dr. Lukai Song
Dr. Yat Sze Choy
Guest Editors

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