Modeling and Optimization of Complex Engineering Systems under Uncertainties

Dear Colleagues,

In engineering problems, complex systems usually consist of many subsystems. The coupled disciplines represented by these subsystems are interrelated. Additionally, multi-source mixed uncertainties are accompanied by the transmission and accumulation of coupled information in complex systems. Therefore, the modeling and design processes of complex systems in engineering problems are often time-consuming and inefficient. Moreover, the reliability and safety of system performance cannot be completely guaranteed.

To tackle the above challenges, the development of advanced modeling technology and a design optimization algorithm of complex engineering systems considering mixed uncertainties is necessary. On the one hand, the continuing development of engineering systems makes it difficult for existing modeling methods to efficiently address all new problems. On the other hand, because of the limited time and cost, designers have to select an appropriate method among various design and optimization methods to solve their problems. Consequently, newer uncertainty-based design and optimization methods should be developed to provide greater options for engineering designers.

The aim of this Special Issue is to establish an academic forum between experts and scholars and come to an agreement regarding the current state of this research field; draw a roadmap of where research is headed, highlight issues, and discuss their possible solutions; and provide the data, models and tools necessary for performing complex system modeling and a multidisciplinary design optimization algorithm considering mixed uncertainties. Potential topics include, but are not limited to:

• System modeling;
• Multidisciplinary design optimization;
• System reliability and risk assessment;
• Structural safety;
• Interval and fuzzy mathematics;
• Structural analysis;
• Optimization problem and computational methods;
• Information fusion;
• Fault diagnosis;
• Probabilistic physics of failure;
• Uncertainty-based design optimization;
• Uncertainty quantification and propagation;
• Performance degradation modeling and analysis.

Dr. Debiao Meng
Dr. Shui Yu
Guest Editors

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