بهینه سازی تجزیه و تحلیل الاستو پلاستیک خرپا با استفاده از الگوریتم ژنتیک
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|8157||2013||13 صفحه PDF||سفارش دهید||4670 کلمه|
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله شامل 4670 کلمه می باشد.
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Engineering Structures, Volume 50, May 2013, Pages 1–12
In this paper, the incremental elasto-plastic analysis method, is utilized to predict the collapse load factor of truss structures. The obtained collapse load factor is then incorporated into truss optimization using a Genetic Algorithm (GA) in order to generate truss structures which cannot only maintain load-carrying capacity under ordinary load conditions, but also avoid collapse under accidental load conditions such as an extremely large earthquake. Our designed optimization scheme is successfully implemented to solve two optimization problems, indicating the successful realization of designed optimization scheme.
The Genetic Algorithm, based on the Darwinian survival-of-the fittest theory, is an efficient and broadly applicable global search algorithm because it works directly with solutions instead of the derivate information . Since Adeli and Cheng  presented optimization of space structures by integrating GA with the penalty function method, a number of papers have been published on structural optimization using Genetic Algorithms in the literature. Research has been carried out in recent decades focusing on either the improvement of the optimization method of GA , ,  and  or the speeding up of the optimization process through advanced computers ,  and . On the other hand, there are also a number of studies ,  and  focusing only on truss structural optimization problems and some of them have contributed to practical truss optimization  and . Our review of the literature indicates no article with respect to truss optimization taking into account the ultimate load-carrying ability of the truss structure. According to the design procedure in Japan, structural design usually consists of two design stages. In the first design stage, structures must be able to keep their load-carrying capacity under ordinary load conditions such as dead load and live load. In the second design stage, structures ought to have sufficient resistance to some accidental load conditions such as extremely large earthquakes and drastic typhoons. As a rule, in the first design stage, stresses of structural members calculated via the Finite Element Method (FEM) must be limited to the allowable stress required by related design criteria. Next, during the second design stage, structures undergo plastic analysis to predict their ultimate load-carrying ability, which is often evaluated by the collapse load factor . With the guarantee of the collapse load factor being larger than the load factor of an accidental loading, engineers can ensure the structure’s safety under accidental load cases. The incremental elasto-plastic method  is conventionally used for the calculation of the collapse load factor of a frame structure. In this study, we use it to calculate the collapse load factor of truss structures under a few assumptions. Based on the authors’ earlier study , by adding the ratio of the collapse load factor to the load factor of an accidental load as a constraint to the truss optimization using GA, this paper attempts to present a truss optimization problem with consideration of both the first and second design stages.
نتیجه گیری انگلیسی
The authors’ goal in this research has been to advance the likelihood of application of truss optimization to actual truss structural design by taking into consideration the ultimate load-carrying capacity of the truss structure. The incremental elasto-plastic analysis method is utilized as the technique for the calculation of the collapse load factor of the truss structure, and the ratio of the obtained collapse load factor to the load factor of accidental load is imposed as a constraint in the truss optimization using Genetic Algorithm. As a result, truss optimization entailing two design stages can be realized. To the best of the authors’ knowledge, this is the first time for the truss optimization considering the ultimate resistance has been presented. The conclusion of this study is that solving two optimization problems of a double-layer truss structure and a dome truss structure results in simple, lightweight structures with all constraints being well satisfied, proving the robustness of the proposed scheme.