Submission Deadline: 31 December 2023 (closed) View: 1449
Prof. Debiao Meng, University of Electronic Science and Technology of China (UESTC), China
Prof. Abílio Manuel Pinho de Jesus, University of Porto (FEUP), Portugal
Prof. Zeng Meng, Hefei University of Technology, China
With the progress of science and technology, more and more complex engineering structures are serving in extreme environments. In the service life of these engineering structures, multi-source mixed uncertainty factors exist widely, which can affect safety and reliability significantly. Thus, how to ensure the high reliability and long service life of complex engineering structures is a research hotspot in the field of engineering design. Computer-aided uncertainty modeling and reliability evaluation for complex engineering structures are powerful tools to tackle the above challenges.
With the continuous advancement of the computer field, different advanced computational technologies have been introduced into computer-aided uncertainty modeling and reliability evaluation, such as artificial neural networks, surrogate models, metaheuristic algorithms, information entropy, fuzzy logic, convex model, multifidelity model, physics-informed neural network, deep learning, etc. However, each of these methods has its own merits and disadvantage. Facing a complex and changing variable environment, it is difficult to say which single technical means is the best. Meanwhile, the continuing development of engineering structures makes the existing methods difficult to deal with all new problems efficiently. Therefore, novel uncertainty modeling and reliability evaluation methods based on these advanced computational technologies are needed to be developed to provide more accurate and efficient estimations of the safety levels for the complex engineering structures of today.
This special issue would aim to establish an academic exchange platform between experts and scholars, also, 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 methods necessary to performing uncertainty modeling and reliability analysis for complex engineering structure. Potential topics include, but are not limited to:
• Uncertainty modeling
• Reliability evaluation and risk assessment
• Structural safety
• Fuzzy logic
• Interval and fuzzy mathematics
• Uncertainty quantification and propagation
• Machine learning
• Structural integrity
• Metaheuristic algorithm
• Information fusion
• Fault diagnosis
• Probabilistic Physics of Failure
• Surrogate models
• Uncertainty-based design optimization
• Signal processing
• Performance degradation modeling and analysis
• Durability and damage tolerance
• Risk analysis and safety of materials and structural mechanics
• Analytical and numerical simulation of materials and structures
• Experimental methods applied to structural integrity
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