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RISS 인기검색어
- 검색키워드
- 저자 : Ashraf F. Ashour (검색결과 8 건)
- 무료
- 기관 내 무료
- 유료
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Shear Capacity of Reinforced Concrete Beams Using Neural Network
Yang, Keun-Hyeok,Ashour, Ashraf F.,Song, Jin-Kyu Korea Concrete Institute 2007 International Journal of Concrete Structures and M Vol.1 No.1
Optimum multi-layered feed-forward neural network (NN) models using a resilient back-propagation algorithm and early stopping technique are built to predict the shear capacity of reinforced concrete deep and slender beams. The input layer neurons represent geometrical and material properties of reinforced concrete beams and the output layer produces the beam shear capacity. Training, validation and testing of the developed neural network have been achieved using 50%, 25%, and 25%, respectively, of a comprehensive database compiled from 631 deep and 549 slender beam specimens. The predictions obtained from the developed neural network models are in much better agreement with test results than those determined from shear provisions of different codes, such as KBCS, ACI 318-05, and EC2. The mean and standard deviation of the ratio between predicted using the neural network models and measured shear capacities are 1.02 and 0.18, respectively, for deep beams, and 1.04 and 0.17, respectively, for slender beams. In addition, the influence of different parameters on the shear capacity of reinforced concrete beams predicted by the developed neural network shows consistent agreement with those experimentally observed.
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Analysis of R/C frames considering cracking effect and plastic hinge formation
Kara, Ilker Fatih,Ashour, Ashraf F.,Dundar, Cengiz Techno-Press 2017 Structural Engineering and Mechanics, An Int'l Jou Vol.63 No.5
The design of reinforced concrete buildings must satisfy the serviceability stiffness criteria in terms of maximum lateral deflections and inter story drift in order to prevent both structural and non-structural damages. Consideration of plastic hinge formation is also important to obtain accurate failure mechanism and ultimate strength of reinforced concrete frames. In the present study, an iterative procedure has been developed for the analysis of reinforced concrete frames with cracked elements and consideration of plastic hinge formation. The ACI and probability-based effective stiffness models are used for the effective moment of inertia of cracked members. Shear deformation effect is also considered, and the variation of shear stiffness due to cracking is evaluated by reduced shear stiffness models available in the literature. The analytical procedure has been demonstrated through the application to three reinforced concrete frame examples available in the literature. It has been shown that the iterative analytical procedure can provide accurate and efficient predictions of deflections and ultimate strength of the frames studied under lateral and vertical loads. The proposed procedure is also efficient from the viewpoint of computational time and convergence rate. The developed technique was able to accurately predict the locations and sequential development of plastic hinges in frames. The results also show that shear deformation can contribute significantly to frame deflections.
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Shear Capacity of Reinforced Concrete Using Neural network
양근혁,Ashraf F. Ashour,송진규 한국콘크리트학회 2007 International Journal of Concrete Structures and M Vol.1 No.1
Optimum multi-layered feed-forward neural network (NN) models using a resilient back-propagation algorithm and early stopping technique are built to predict the shear capacity of reinforced concrete deep and slender beams. The input layer neurons represent geometrical and material properties of reinforced concrete beams and the output layer produces the beam shear capacity. Training, validation and testing of the developed neural network have been achieved using 50%, 25%, and 25%, respectively, of a comprehensive database compiled from 631 deep and 549 slender beam specimens. The predictions obtained from the developed neural network models are in much better agreement with test results than those determined from shear provisions of different codes, such as KBCS, ACI 318-05, and EC2. The mean and standard deviation of the ratio between predicted using the neural network models and measured shear capacities are 1.02 and 0.18, respectively, for deep beams, and 1.04 and 0.17, respectively, for slender beams. In addition, the influence of different parameters on the shear capacity of reinforced concrete beams predicted by the developed neural network shows consistent agreement with those experimentally observed.
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Wenjie Ge,Ashraf F. Ashour,Weigang Lu,Dafu Cao 한국콘크리트학회 2020 International Journal of Concrete Structures and M Vol.14 No.2
Experimental and theoretical investigations on the flexural performance of steel reinforced ECC-concrete composite beams subjected to freeze-thaw cycles are presented in this paper. Four groups of reinforced composite beams with different ECC height replacement ratios subject to 0, 50, 100 and 150 cycles of freeze-thaw were physically tested to failure. Experimental results show that the bending capacity decreases with the increase of freeze-thaw cycles regardless of ECC height replacement ratios. However, the ultimate moment, stiffness and durability of ECC specimens and ECC-concrete composite specimens are greater than those of traditional concrete specimens, owing to the excellent tensile performance of ECC materials. With the increase of ECC height, the crack width and average crack spacing gradually decrease. According to materials’ constitutive models, compatibility and equilibrium conditions, three failure modes with two boundary failure conditions are proposed. Simplified formulas for the moment capacity are also developed. The results predicted by the simplified formulas show good agreement with the experimental moment capacity and failure modes. A parametric analysis is conducted to study the influence of strength and height of ECC, amount of reinforcement, concrete strength and cycles of freeze-thaw on moment capacity and curvature ductility of ECC-concrete composite beams.
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Analysis of R/C frames considering cracking effect and plastic hinge formation
Ilker Fatih Kara,Ashraf F. Ashour,Cengiz Dundar 국제구조공학회 2017 Structural Engineering and Mechanics, An Int'l Jou Vol.63 No.5
The design of reinforced concrete buildings must satisfy the serviceability stiffness criteria in terms of maximum lateral deflections and inter story drift in order to prevent both structural and non-structural damages. Consideration of plastic hinge formation is also important to obtain accurate failure mechanism and ultimate strength of reinforced concrete frames. In the present study, an iterative procedure has been developed for the analysis of reinforced concrete frames with cracked elements and consideration of plastic hinge formation. The ACI and probability-based effective stiffness models are used for the effective moment of inertia of cracked members. Shear deformation effect is also considered, and the variation of shear stiffness due to cracking is evaluated by reduced shear stiffness models available in the literature. The analytical procedure has been demonstrated through the application to three reinforced concrete frame examples available in the literature. It has been shown that the iterative analytical procedure can provide accurate and efficient predictions of deflections and ultimate strength of the frames studied under lateral and vertical loads. The proposed procedure is also efficient from the viewpoint of computational time and convergence rate. The developed technique was able to accurately predict the locations and sequential development of plastic hinges in frames. The results also show that shear deformation can contribute significantly to frame deflections.
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