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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/969

Title: Reliability and performance-based design by artificial neural network
Authors: Chau, Kwok-wing
Subjects: Design parameters
Neural network
Performance-based design
Structural reliability
Issue Date: Mar-2007
Publisher: Elsevier
Citation: Advances in engineering software, Mar. 2007, v. 38, no. 3, p. 145-149.
Abstract: Whilst conventional approach in structural design is based on reliability-calibrated factored design formula, performance-based design customizes a solution to the specific circumstance. In this work, an artificial neural network approach is employed to determine implicit limit state functions for reliability evaluations in performance-based design and to optimally evaluate a set of design variables under specified performance criteria and corresponding desired reliability levels in design. Case examples are shown for reliability design. Through the establishment of the response and reliability databases, for specified target reliabilities, structural response computations are integrated with the evaluation of design parameters and design can be accomplished. By employing this methodology, with the same performance requirements, pertinent design parameters can be altered in order to evaluate feasible design alternatives, to explore the usage of various structural materials and to define required material quality control.
Description: DOI:10.1016/j.advengsoft.2006.09.008
Rights: Advances in Engineering Software © 2006 Elsevier Ltd. The journal web site is located at http://www.sciencedirect.com.
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/969
ISSN: 09659978
Appears in Collections:CEE Journal/Magazine Articles

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