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Prediction of shear behavior of fiber reinforced concrete beams using neural networks / Shaimaa Abdeltawab Mohamed ; Supervised Mustafa Fouad Elkafrawy , Ahmed Mohamed Elnady ,Tamer Elsayed Ahmed Said

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Shaimaa Abdeltawab Mohamed , 2016Description: 97 P. : charts , facsimiles ; 30cmOther title:
  • التنبؤ بسلوك القص في الكمرات الخرسان{u٠٦أأ}ة المسلحة المقواه بالال{u٠٦أأ}اف باستخدام شبكات الخلا{u٠٦أأ}ا العصب{u٠٦أأ}ة [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Civil Engineering Summary: The main objective of this research is to develop an artificial Neural Network that is able to predict shear strength for fiber reinforced concrete beams because of difficulty of it and simplify its use through developing a Graphic User Interface (GUI). Moreover, shear behavior in fiber reinforced concrete beams (FRCBs) is quantified by compressive strength of concrete, longitudinal steel, size effect, fiber's type, content and aspect ratio. The research methodology is based on collecting experimental results of technical investigations carried out so as to predict shear behavior in FRCBs. For this, two back-propagation neural networks have been experimented by MATLAB; their types have been fitting (1st network) and pattern recognition (2nd network) which have been used to classify failure of FRC beams into 6 categories. The training algorithms use feed forward back propagation. The ANNs model has been assessed in comparison with exact values and deduces a good correlation with it
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.05.M.Sc.2016.Sh.P (Browse shelf(Opens below)) Not for loan 01010110069850000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.05.M.Sc.2016.Sh.P (Browse shelf(Opens below)) 69850.CD Not for loan 01020110069850000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Civil Engineering

The main objective of this research is to develop an artificial Neural Network that is able to predict shear strength for fiber reinforced concrete beams because of difficulty of it and simplify its use through developing a Graphic User Interface (GUI). Moreover, shear behavior in fiber reinforced concrete beams (FRCBs) is quantified by compressive strength of concrete, longitudinal steel, size effect, fiber's type, content and aspect ratio. The research methodology is based on collecting experimental results of technical investigations carried out so as to predict shear behavior in FRCBs. For this, two back-propagation neural networks have been experimented by MATLAB; their types have been fitting (1st network) and pattern recognition (2nd network) which have been used to classify failure of FRC beams into 6 categories. The training algorithms use feed forward back propagation. The ANNs model has been assessed in comparison with exact values and deduces a good correlation with it

Issued also as CD

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