دوره 4، شماره 4 - ( 8-1393 )                   جلد 4 شماره 4 صفحات 524-509 | برگشت به فهرست نسخه ها

XML English Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Mohebi B, Ghodrati Amiri G, Taheri M. SELECTION OF SUITABLE RECORDS FOR NONLINEAR ANALYSIS USING GENETIC ALGORITHM (GA) AND PARTICLE SWARM OPTIMIZATION (PSO). IJOCE 2014; 4 (4) :509-524
URL: http://ijoce.iust.ac.ir/article-1-190-fa.html
SELECTION OF SUITABLE RECORDS FOR NONLINEAR ANALYSIS USING GENETIC ALGORITHM (GA) AND PARTICLE SWARM OPTIMIZATION (PSO). عنوان نشریه. 1393; 4 (4) :509-524

URL: http://ijoce.iust.ac.ir/article-1-190-fa.html


چکیده:   (21857 مشاهده)
This paper presents a suitable and quick way to choose earthquake records in non-linear dynamic analysis using optimization methods. In addition, these earthquake records are scaled. Therefore, structural responses of three different soil-frame models were examined, the change in maximum displacement of roof was analyzed and the damage index of whole structures was measured. The soil classification of project location was divided into 4 different types according to the velocity of shear waves in the Iranian Code for Seismic Design. As a result, 8 frame models were considered. The selection and scaling were carried out in 2 stages. In the first stage, the matching with design spectrum was carried out using genetic algorithm in order to achieve the mean of structural response. In the second stage, the matching with average of structural responses were carried out using PSO to achieve 1 or 3 accelerograms with related factors in order to be used in structural analysis.
متن کامل [PDF 588 kb]   (6060 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: Optimal design
دریافت: 1393/8/27 | پذیرش: 1393/8/27 | انتشار: 1393/8/27

ارسال نظر درباره این مقاله : نام کاربری یا پست الکترونیک شما:
CAPTCHA

بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.

کلیه حقوق این وب سایت متعلق به دانشگاه علم و صنعت ایران می باشد.

طراحی و برنامه نویسی : یکتاوب افزار شرق

© 2024 CC BY-NC 4.0 | Iran University of Science & Technology

Designed & Developed by : Yektaweb