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Reliability and performance-based design by artificial neural network

机译:基于人工神经网络的可靠性和基于性能的设计

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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.
机译:结构设计的常规方法基于可靠性校准的因式设计公式,而基于性能的设计则针对特定情况定制解决方案。在这项工作中,采用了人工神经网络方法来确定隐式极限状态函数,以进行基于性能的设计中的可靠性评估,并在指定的性能标准和设计中相应的所需可靠性水平下优化评估一组设计变量。显示了用于可靠性设计的案例。通过建立响应和可靠性数据库,针对指定的目标可靠性,将结构响应计算与设计参数评估集成在一起,即可完成设计。通过采用具有相同性能要求的该方法,可以更改相关的设计参数,以评估可行的设计替代方案,以探索各种结构材料的用途并定义所需的材料质量控制。

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