A framework for optimization of target reliability index for a building class based on aggregated cost. (November 2019)

• Record Type: Journal Article
• Authors: Gudipati, Vamshi Krishna; Cha, Eun Jeong
• Is Part Of: Structural safety. Volume 81(2019)
• Publication Date: 2019-11
• Subjects: Aggregated cost -- Buildings -- Neural network -- Optimization -- Seismic design -- Target reliability index; Structural stability -- Periodicals; Safety factor in engineering -- Periodicals; Reliability (Engineering) -- Periodicals; Constructions -- Stabilité -- Périodiques; Coefficient de sécurité en ingénierie -- Périodiques; Fiabilité -- Périodiques; 620.86
• DOI: 10.1016/j.strusafe.2019.101873
• Languages: English
• ISSNs: 0167-4730

Abstract

Highlights: Framework for target safety optimization of a building class was introduced. Neural network-based response estimation tool for a building class was developed. Optimization framework is computationally efficient. ASCE-7 target reliability is found to be more stringent than the optimal values. Abstract: To effectively manage the seismic risk of the built-environment, the target safety levels that design standards are based on should be properly managed by considering the total risk to the built-environment and to the community. This paper introduces a framework for optimizing the target safety levels based on the total life-cycle cost of a portfolio of buildings. Building inventory is categorized to obtain a clear relationship between target safety level and its realizations to design, which is reflected in the proposed framework. To address the issue of unrealistic computation cost in implementing optimization process in target safety level determination, the framework utilizes a neural network for structural response estimation. A procedure to develop a neural network for dynamic response estimation of a group of buildings is also introduced in the paper. The proposed framework is illustrated to obtain the optimal target reliability index for mid-rise office buildings.