Performance-based bi-objective design optimization of wind-excited building systems

被引:7
|
作者
Suksuwan, Arthriya [1 ]
Spence, Seymour M. J. [1 ]
机构
[1] Univ Michigan, Dept Civil & Environm Engn, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会;
关键词
Bi-objective optimization; Performance-based design; Wind engineering; System-level loss assessment; Monte Carlo simulation; Stochastic wind loads; High-dimensional problems; Kriging metamodeling; STOCHASTIC SUBSET OPTIMIZATION; EPSILON-CONSTRAINT METHOD; TALL BUILDINGS; RELIABILITY OPTIMIZATION; SHAPE OPTIMIZATION; STRUCTURES SUBJECT; UNCERTAIN; FRAMEWORK; COST; SIMULATION;
D O I
10.1016/j.jweia.2019.03.028
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper proposes a framework for the bi-objective optimization of uncertain and dynamic wind-excited systems whose susceptibility to system-level damage is modeled through probabilistic fragility-based loss measures. In particular, the proposed framework is based on first reformulating the bi-objective stochastic optimization problem into a suite of single-objective optimization problems through the e-constraint approach. Secondly, a new optimization sub-problem is introduced for efficiently solving the single-objective problems, whose formulation is based on combining the auxiliary variable vector approach with a new kriging-enhanced approximation scheme. Because the sub-problem can be fully calibrated and subsequently solved from the results of a single performance assessment carried out in a fixed point of the design space, efficiency and scalability to high-dimensional problems is achieved. Through solving a sequence of sub-problems, solutions to the epsilon-constraint problems are obtained leading to the identification of the Pareto-optimal solutions of the original bi-objective optimization problem. To illustrate the applicability, efficiency and scalability of the proposed framework, an example of application to a large-scale structure is presented, where structural material volume and a system-level loss measure defined in terms of expectation and standard deviation of the total repair cost are simultaneously minimized.
引用
收藏
页码:40 / 52
页数:13
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