Performance-based multi-hazard topology optimization of wind and seismically excited structural systems

被引:31
|
作者
Suksuwan, Arthriya [1 ]
Spence, Seymour M. J. [1 ]
机构
[1] Univ Michigan, Dept Civil & Environm Engn, Ann Arbor, MI 48109 USA
关键词
Performance-Based Design; Topology optimization; Multi-hazard engineering; Wind engineering; Seismic engineering; Monte Carlo simulation; RELIABILITY-BASED DESIGN; LOADING UNCERTAINTY; TALL BUILDINGS; CONTINUUM; FRAMEWORK; MODELS;
D O I
10.1016/j.engstruct.2018.06.039
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The integration of topology optimization procedures into modem structural design frameworks is gaining interest as an innovative approach for achieving more efficient designs. To this end, probabilistic performance based topology optimization frameworks have recently been proposed for the identification of optimal structural systems subject to extreme wind or seismic events considered in isolation. However, there are large geographic regions that are subject to both wind and seismic hazards. Therefore, the development of methods that can ensure that target performance metrics are met within a multi-hazard setting is a crucial step towards improving the reliability of structural systems. This paper is focused on proposing a simulation-centered performance-based topology optimization framework for the identification of optimal structural systems for multi-hazard wind and seismic environments. A probabilistic performance assessment framework is firstly proposed based on synergistically describing the performance of wind or seismically excited systems. Based on this framework, a multi-hazard topology optimization strategy is proposed. In particular, the methodology is centered on the definition of an approximate optimization sub-problem that not only decouples the simulation-based performance assessment from the optimization loop, but also transforms the dynamic and uncertain optimization problem into an explicit static and deterministic problem therefore enabling its efficient resolution using any gradient-based optimizer. Optimal lateral load resisting systems that rigorously meet the probabilistic performance constraints set within the multi hazard environment are therefore identified. A case study is presented demonstrating the potential of the proposed framework.
引用
收藏
页码:573 / 588
页数:16
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