|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|138600||2018||13 صفحه PDF||سفارش دهید||10456 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Advances in Engineering Software, Volume 117, March 2018, Pages 123-135
Two advanced optimization approaches to solving a reliability-based design problem are presented. The first approach is based on the utilization of an artificial neural network and a small-sample simulation technique. The second approach considers an inverse reliability task as a reliability-based optimization task using a double-loop optimization method based on small-sample simulation. Both techniques utilize Latin hypercube sampling with correlation control. The efficiency of both approaches is tested using three numerical examples of structural design â a cantilever beam, a reinforced concrete slab and a post-tensioned composite bridge. The advantages and disadvantages of the approaches are discussed.