MS02 Design of Complex Dynamical Engineering Systems under Uncertain Conditions
Prof. Hector Jensen: firstname.lastname@example.org
Prof. Hector Jensen, Department of Civil Engineering, Federico Santa Maria Technical University, Valparaiso, Chile, email@example.com
Prof. Jianbing Chen, Department of Structural Engineering, School of Civil Engineering, Tongji University, Shanghai, China, firstname.lastname@example.org
Dr. Yongbo Peng, Department of Structural Engineering, School of Civil Engineering, Tongji University, Shanghai, China, email@example.com
Abstract of the special session：
Design of complex dynamical engineering systems require crucial engineering decisions under considerable uncertainty. System performance predictions may be sensitive to modeling and excitation uncertainties. Experience in a number of engineering disciplines reveal the necessity to quantify and manage uncertainties during the design process in order to keep project risks in check and system performance accountable. The proper design procedures that explicitly treat uncertainties generally enhances the reliability and the performance of systems, allowing risk-informed decisions to be made. The task of designing a system comprises applying strategies for uncertainty quantification and optimization. This in turn demands evaluating the system’s performance repeatedly, considering different scenarios and different design solutions, which can be very costly (and usually prohibitive) from the numerical viewpoint. In view of this challenge, the design of complex systems under uncertain conditions has become the subject of active research.
This mini-symposium aims to address the latest progress on approaches and methods for designing complex dynamical engineering systems under uncertain operating conditions. The topics to be covered include, but are not limited to: reliability estimation; performance-based design optimization; reliability-based design; stochastic load representations; advanced simulation techniques; robust solutions; meta-models for reliability estimation; maintenance schedule; reliability-based optimal control; multi-objective optimal design; optimization algorithms; and life-cycle cost optimization. Both theoretical developments and applications involving systems of engineering interest are particularly welcomed.
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