Optimization of uncertain and dynamic high-rise structures for occupant comfort: An adaptive kriging approach

• Published in: Structural safety Vol. 75; pp. 57 - 66
• Main Author: Spence, Seymour M.J.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.11.2018; Elsevier BV
• Subjects: Building failures; Cladding; Comfort; Design; Design parameters; High rise buildings; Kriging interpolation; Metamodeling; Monte Carlo simulation; Occupant comfort; Optimization; Optimization algorithms; Parameter uncertainty; Reliability engineering; Reliability-based optimization; Stochastic models; Stochastic processes; Stochastic systems; Wind engineering; Reliability-based optimization; Wind engineering; Occupant comfort; Stochastic systems; Metamodeling; Monte Carlo simulation
• ISSN: 0167-4730; 1879-3355
• DOI: 10.1016/j.strusafe.2018.05.008

•A framework for occupant comfort optimization of wind-excited buildings is proposed.•The framework can treat a wide class of occupant comfort performance metrics.•The approach is based on the development of a novel adaptive kriging metamodel.•The method can treat general stochastic wind load models and system uncertainties.•The framework is scalable to high-dimensional design spaces. Performance requirements concerning serviceability often govern the design of high-rise structures. While various methods have been proposed for obtaining optimal systems that meet serviceability constraints set on the performance of non-structural components, e.g. the cladding system, methods are still lacking for optimizing under constraints aimed at ensuring occupant comfort. This is especially true for systems whose performance is assessed within modern performance-based design frameworks that consider a full range of uncertainties, including wind loads modeled as stochastic processes. This paper is focused on the development of a novel optimization framework for overcoming these limitations. The method is based on constructing an adaptive kriging metamodel of the probabilistic performance metric of interest in the low-dimensional modal space of the system. By then relating this space to the design variables, an approach is defined that can handle a wide class of occupant comfort metrics within high-dimensional spaces of design variables and uncertain parameters.