Parametric study of eccentrically loaded concrete encased steel composite columns using artificial neural networks
المؤلف
المصدر
Journal of University of Babylon for Engineering Sciences
العدد
المجلد 25، العدد 5 (31 أكتوبر/تشرين الأول 2017)، ص ص. 1668-1683، 16ص.
الناشر
تاريخ النشر
2017-10-31
دولة النشر
العراق
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
This paper presents a parametric study to investigate the behavior of eccentrically loaded concrete encased steel composite columns (SRC).
The artificial neural network (ANN) technique was adopted in this study by developing an efficient model to predict the behavior of such composite columns, depending on a total of 105 experimental tests for such composite columns with concrete rectangular section encased I-shape structural steel section and subjected to eccentric loads producing bending moment about one of the column section axes.
The developed model was used to investigate the effects on the structural behavior of the eccentrically loaded composite columns owing to the steel contribution ratio, the axis of the applied bending, the concrete strength, and the structural steel yield stress by analyzing of 36 SRC specimens with different structural properties.
Generally, it is shown that the effect of the axis of applied bending moment on the strength of SRC specimens is directly proportional to steel contribution ratio.
It was observed, also, that in spite of the strength of the analyzed composite columns were increased with the increase in the strength of concrete, but the both effects, the axis of the applied bending moment and the increase of structural steel yield stress, are inversely proportional to the increase of concrete strength.
The Predicted strengths of SRC specimens from ANN analysis were compared with that calculated using the EC4, giving good agreement reached to a ratio around 0.96.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Salih, Samuil Mahdi. 2017. Parametric study of eccentrically loaded concrete encased steel composite columns using artificial neural networks. Journal of University of Babylon for Engineering Sciences،Vol. 25, no. 5, pp.1668-1683.
https://search.emarefa.net/detail/BIM-918288
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Salih, Samuil Mahdi. Parametric study of eccentrically loaded concrete encased steel composite columns using artificial neural networks. Journal of University of Babylon for Engineering Sciences Vol. 25, no. 5 (2017), pp.1668-1683.
https://search.emarefa.net/detail/BIM-918288
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Salih, Samuil Mahdi. Parametric study of eccentrically loaded concrete encased steel composite columns using artificial neural networks. Journal of University of Babylon for Engineering Sciences. 2017. Vol. 25, no. 5, pp.1668-1683.
https://search.emarefa.net/detail/BIM-918288
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 1683
رقم السجل
BIM-918288
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر