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论文类型：期刊论文

发表时间：2014-05-01

发表刊物：STRUCTURAL SAFETY

收录刊物：SCIE、EI、Scopus

卷号：48

页面范围：1-14

ISSN号：0167-4730

关键字：Risk design optimization; Reliability-based design optimization; Multi-objective optimization; Many-objective evolutionary algorithm; Performance-based wind engineering; Particle swarm optimization

摘要：Risk design optimization (RDO) is a competent approach for automated performance-based structural design by achieving a balance between safety and economy. Performance-based wind engineering (PBWE) is aimed at improving the life-cycle functionality of wind-sensitive structures, hence could be the very field RDO is tailor-made for. In this paper, we embed PBWE of tall buildings into RDO and tackle some difficulties when integrating them directly. We first formulate an integrated stiffness and vibration control RDO problem, and employ a frequency domain closed-form solution for uncertainty quantification and uncertainty propagation through the excitation-response-performance chain. Then we reveal the multi-objective optimization nature of RDO, and circumvent the difficulties in serviceability loss estimation by replacing scalar total cost with high-dimensional objective vector. Micro multi-objective particle swarm optimization in conjunction with kernel-learning based principle component analysis is employed to solve the corresponding many-objective problem with multiple probabilistic constraints and discrete design variables. The optimization results of CAARC benchmark indicate that we simplify risk-based PBWE of tall buildings from a complex multi-objective decision making process into a relatively easy multi-attribute decision making process. Accordingly, convincing decisions can be made based on the explicit building performance rather than the unreliable loss information. (C) 2014 Elsevier Ltd. All rights reserved.