Determining Moment-Curvature Relationship of Reinforced Concrete Rectangular Shear Walls
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32804
Determining Moment-Curvature Relationship of Reinforced Concrete Rectangular Shear Walls

Authors: Gokhan Dok, Hakan Ozturk, Aydin Demir

Abstract:

The behavior of reinforced concrete (RC) members is quite important in RC structures. When evaluating the performance of structures, the nonlinear properties are defined according to the cross sectional behavior of RC members. To be able to determine the behavior of RC members, its cross sectional behavior should be known well. The moment-curvature (MC) relationship is used to represent cross sectional behavior. The MC relationship of RC cross section can be best determined both experimentally and numerically. But, experimental study on RC members is very difficult. The aim of the study is to obtain the MC relationship of RC shear walls. Additionally, it is aimed to determine the parameters which affect MC relationship. While obtaining MC relationship of RC members, XTRACT which can represent robustly the MC relationship is used. Concrete quality, longitudinal and transverse reinforcing ratios, are selected as parameters which affect MC relationship. As a result of the study, curvature ductility and effective flexural stiffness are determined using this parameter. Effective flexural stiffness is compared with the values defined in design codes.

Keywords: Moment-curvature, reinforced concrete, shear wall, numerical.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1132042

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2257

References:


[1] Caglar, N. and Garip, Z.S. (2013), “Neural network based model for seismic assessment of existing RC buildings”, Comput. Concr., 12, 229-242.
[2] Caglar, N. (2009), “Neural network based approach for determining the shear strength of circular reinforced concrete columns”, Constr. Build. Mater., 23, 3225-3232.
[3] Gunaratnam, D.J. and Gero, J.S. (2008), “Effect of representation on the performance of neural networks in structural engineering applications”, Comput. Aided Civil Infrastruct. Eng., 9(2), 97–108.
[4] Pala, M., Caglar, N., Elmas, M., Cevik, A. and Saribiyik, M. (2008), “Dynamic soil-structure interaction analysis of buildings with neural networks”, Constr. Build. Mater., 22(3), 330-342.
[5] Pala, M. (2006). “New formulation for distortional buckling stress”. J. Constr. Steel Res., 62, 716–722.
[6] Adeli, H. and Samant, A. (2000), “An adaptive conjugate gradient neural network–wavelet model for traffic incident detection”, Comput. Aided Civil Infrastruct. Eng., 15 (4), 251–260.
[7] Bishop, C.M. (1995), Neural Networks for Pattern Recognition, Oxford University Press, Oxford, England.
[8] Kulkarni, A.D. (1994), “Artificial Neural Networks for Image Understanding”, Van Nosrand Reinhold, NY, USA
[9] Caglar N., Demir A., Ozturk H., Akkaya A.(2015), “A simple formulation for effective flexural stiffness of circular reinforced concrete columns”, Engineering Applications of Artificial Intelligence, 2015, 38(2015)79–87.
[10] Jadid, M.N. and Fairbairn D.R. (1996), “Neural-network applications in predicting moment-curvature parameters from experimental data”, Eng. Appl. Artif. Intell., 9 (3), 309-319.
[11] Arslan, M.H. (2012), “Estimation of curvature and displacement ductility in reinforced concrete buildings”, KSCE J. Civil Eng., 16 (5), 759-770.
[12] Petschke, T., Corres, H.A., Ezeberry, J.I., Pérez, A. and Recupero, A. (2013), “Expanding the classic moment-curvature relation by a new perspective onto its axial strain”, Comput. Concr., An Int. J., 11 (6), 515-529.
[13] Dogangun, A. (2013), Design and Calculation of Reinforced Concrete Structures, Birsen Press, Istanbul, Turkey, ISBN: 978-975-511-310-X.
[14] Ersoy, U. and Ozcebe, G. (1998), “Moment-curvature relationship of confined concrete sections”, IMO Technical Journal, December, Digest 98, 549-553.
[15] Ersoy, U., Ozcebe, G. and Tankut, T. (2008), Reinforced Concrete, Department of Civil Engineering, METU Press, Ankara, Turkey.
[16] XTRACT and User Manual, “Cross-sectional X structural analysis of components, Imbsen Software Systems, 9912 Business Park Drive”, Suite 130 Sacramento, CA 95827.
[17] TEC (2007), Turkish Earthquake Code, Ankara, Turkey.
[18] TS 500 (2002), Requirements for Design and Construction of Reinforced Concrete Structures, Ankara, Turkey.
[19] Mander, J.B., Priestley, M.J.N. and Park, R. (1988), “Theoretical stress-strain model for confined concrete”. J. Struct. Eng., 114(8), 1804-1826.