دوره 4، شماره 1 - ( 12-1392 )                   جلد 4 شماره 1 صفحات 1-26 | برگشت به فهرست نسخه ها


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Gholizadeh S, Aligholizadeh V, Mohammadi M. NEURAL NETWORK-BASED RELIABILITY ASSESSMENT OF OPTIMALLY SEISMIC DESIGNED MOMENT FRAMES. International Journal of Optimization in Civil Engineering. 2014; 4 (1) :1-26
URL: http://ijoce.iust.ac.ir/article-1-159-fa.html
NEURAL NETWORK-BASED RELIABILITY ASSESSMENT OF OPTIMALLY SEISMIC DESIGNED MOMENT FRAMES. دانشگاه علم و صنعت ایران. 1392; 4 (1) :1-26

URL: http://ijoce.iust.ac.ir/article-1-159-fa.html


چکیده:   (2554 مشاهده)
In the present study, the reliability assessment of performance-based optimally seismic designed reinforced concrete (RC) and steel moment frames is investigated. In order to achieve this task, an efficient methodology is proposed by integrating Monte Carlo simulation (MCS) and neural networks (NN). Two NN models including radial basis function (RBF) and back propagation (BP) models are examined in this study. In the proposed methodology, MCS is used to estimate the total exceedence probability associated with immediate occupancy (IO), life safety (LS) and collapse prevention (CP) performance levels. To reduce the computational burden of MCS process, the required nonlinear responses of the generated structures are predicted by RBF and BP models. The numerical results imply the superiority of BP to RBF in prediction of structural responses associated with performance levels. Finally, the obtained results demonstrate the high efficiency of the proposed methodology for reliability assessment of RC and steel frame structures.
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نوع مطالعه: پژوهشي | موضوع مقاله: Optimal design
دریافت: ۱۳۹۳/۱/۱۴ | پذیرش: ۱۳۹۳/۱/۱۴ | انتشار: ۱۳۹۳/۱/۱۴

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