1403/02/05
حبیب اکبرزاده بنگر

حبیب اکبرزاده بنگر

مرتبه علمی: دانشیار
ارکید:
تحصیلات: دکترای تخصصی
اسکاپوس:
دانشکده: دانشکده مهندسی و فناوری
نشانی:
تلفن: 09111165785

مشخصات پژوهش

عنوان
Predicting the Ductility of RC Beams Using Nonlinear Regression and ANN
نوع پژوهش
JournalPaper
کلیدواژه‌ها
RC beam ; Confinement ;Curvature ductility; Nonlinear regression ; Artificial neural network
سال
2016
مجله Iranian Journal of Science and Technology-Transactions of Civil Engineering
شناسه DOI
پژوهشگران Habib Akbarzadeh Bengar ، Mohammad Reza Abdollahtabar ، javad shayanfar

چکیده

To avoid a brittle failure of reinforced concrete (RC) frame, the ductility of beams has an important role during earthquake. The calculation of the accurate values of ductility of confined RC beams is complicated, and therefore, a direct and accurate approach is necessary. This study presents two approaches to predict the curvature ductility of RC beams using results of a new method. In the new method, a procedure was developed that curvature ductility of 250 confined and unconfined RC beams were calculated based on actual characteristics of a confined and unconfined compression concrete. In the first approach, an equation was proposed to predict curvature ductility of RC beam by using nonlinear regression based on result of 250 beams. In the second approach, an ANN model was trained to predict curvature ductility of RC beam based on result of 250 beams. An experimental database containing 51 RC beams as flexural test was used to validate the proposed equation and ANN model. A statistical analysis was then performed to evaluate and compare the proposed equation and ANN model for tested RC beams. The statistical analysis results show that ANN model can predict the curvature ductility of RC beam with slightly less scatter in comparison with the proposed equation. Overall, both approaches can predict curvature ductility of RC beam by a proper accuracy.