Shear capacity assessment of reinforced concrete deep beams using artificial neural network

Document Type : Original Article

Authors

1 Department of Civil Engineering Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

2 Civil Eng., Allameh Jafari

3 Civil Eng., Vali-e-Asr University of Rafsanjan

Abstract

مراجع
]1[ کیا، س. م، (1393). شبکه­های عصبی در MATLAB ویرایش سوم، تهران، دانشگاهی کیان.
]2[ طرح و اجرای ساختمان­های بتن ارمه، دفتر مقررات ملی ساختمان، وزارت راه و شهرسازی. مبحث نهم.
[3] Elcordy MF, Chang KC and Lee GC. (1993). Neural networks trained by analytically simulated damage states. J Comput Civil Eng, 7(2):130-45.
[4] Sand A and Saka M. (2001). Prediction of ultimate shear strength of reinforced-concrete deep beams using neural networs. J Struct Eng, 127(7):818-828.
[5] Inel M. (2007). Modeling ultimate deformation capacity of RC columns using artificial neural networks. Eng Struct, 29(3):329-35.
[6] Tang S, Kong FK snd Poh SP. (1998). Shear strength of reinforcement and prestressed concrete deep beams. Proceedings of the Institution of Civil Engineers - Structures and Buildings, 128(2):112-123.
[7] Naderpour H and Alavi SA. (2017). A proposed model to estimate shear contribution of FRP in strengthened RC beams in terms of Adaptive Neuro-Fuzzy Inference System. Composite Structures, 170:.215-227.
[8] Hosseini G. (2017). Capacity Prediction of RC Beams Strengthened with FRP by Artificial Neural Networks Based on Genetic Algorithm. Soft Computing in Civil Engineering, 1(1):93-98.
[9] Farahnaki R. (2017). The application of particle swarm optimization and artificial neural networks to estimating the strength of reinforced concrete flexural members. Soft Computing in Civil Engineering, 1(2):1-7.
]10[ نادرپور حسین و فخاریان پویان. (1396). پیش‏ بینی مقاومت پیچشی تیرهای بتن ‏آرمه تقویت شده با FRP با استفاده از شبکه‏ های عصبی مصنوعی. مهندسی سازه و ساخت، شناسه دیجیتال 10.22065/JSCE.2017.70668.1023.
[11] Kong FK. (2002). Reinforced concrete Deep Beams. Taylor & Francis e – Library, Van Nostrand Reinhold New York.
[12] Smith KN and Vantsiotis AS. (1982). Shear strength of deep beams. ACI struct J, 79(3): 201-213.
[13] Kong FK, Robins PJ and Cole DF. (1970). Web reinforcement effects on deep beams. ACI struct J, 67(12):1010-1018.
[14] ACI , Committee 318. (2015). Building Code Requirements for Structural Concrete ( ACI 218 – 05 ) and Commentary ( ACI 318 – 05 ), USA.
[15] ACI – 318 , ACIC, (2008). 318 – 08 : Building Code Requirements for Structural Concrete and Commentary . American Concrete Institute.
[16] Mau ST and Hsu TSTC. (1989). Formula for the shear strength of deep beams. ACI Struct J, 86(5):516-523.
[17] Tang CY and Tan KH. (2004). Interactive mechanical model for shear strength of deep beams. J struct Eng, 130(10):1634-1544.
[18] CIRIA-Guide 2, C.I.R.a.I.A. (1977). CIRIA Guide 2: The Design of Deep Beams in Reinforcement Concrete.
[19] Hagan MT and Menhaj M. (1999). Training feed-forward networks with the Marquardt algorithm. IEEE Transactions on Neural Networks, 5:989-93.

Keywords

References

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History

  • Receive Date: 07 January 2018
  • Revise Date: 14 February 2018
  • Accept Date: 23 April 2018

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