Abstract
Reinforced concrete may be subjected to temperature due to climatic change or fire. However, deep beams can be exposed to various temperatures. This study will be treated and focused on the criteria of thermal analysis of deep beams. Many lectures are verified by nonlinear finite element method. Also, a parametric study is carried out to investigate the effect of some factors on the behavior of deep beams exposed to elevated temperature. The models are analyzed by the finite element method using (ANSYS) package. These factors are temperature, concrete compressive strength, and the shear span-to-effective depth (a/d) ratio. The results show that when the temperature increases with constant compressive strength and (a/d) ratio, the load capacity and deflection at failure are decreased, while when compressive strength increased, the load capacity and deflection at failure are increased for the same (a/d) ratio and the same temperature. Finally, the results show that the load capacity decreases and deflection increases with an increase in (a/d) ratio for the same temperature and same compressive strength. In addition to the parametric study, the proposed model to predict the strength of the deep beams exposed to high temperature is derived using artificial neural network by MATLAB and SPSS facilities. The error (R) had been (0.99) and square value (R2 = 0.98). This means that the model is efficient and the error is very small.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
ACI Committee 318: Building Code Requirements for Structural Concrete. American Concrete Institute, Farmington Hills, USA (2011)
ACI Committee 318M: Building Code Requirements for Structural Concrete. American Concrete Institute, Michigan, USA (2014)
Ama’ash, H.: New model for shear resistance of simple supported reinforced concrete deep beam. Kufa J. Eng. 3(1) (2011) (In Arabic)
Chen, W.F.: Plasticity in Reinforced Concrete. McGraw-Hill, USA. https://doi.org/10.1016/0045-7825(82)90016-0
Osman, B.H.: Shear in R.C. deep beams. M.Sc. thesis, University of Khartoum, Sudan (2008)
ANSYS, Copyright: ANSYS Help, Release 11.0. (2007)
Abdul Razzaq, K.S.: Effect of heating on simply supported reinforced concrete deep beams. Diyala J. Eng. Sci. 08(02), 116–133 (2015)
Felicetti, R., Gambarova, P.G., Semiglia, M.: Residual capacity of HSC thermally damaged deep beams. J. Struct. Eng. 125(3), 319–327 (1999). https://doi.org/10.1061/(ASCE)0733-9445(1999)125:3(319)
American Concrete Institute: Building Code Requirements for Reinforced Concrete. Detroit, ACI-381-14 (2014)
Antony, N.K., Ramadass, S., Ramanujan, J.: Parametric study on the shear strength of concrete deep beam using ANSYS. Am. J. Eng. Res. (AJER) 4, 51–59 (2013)
Eurocode 2: Design of Concrete Structures, Part 1-2; General Rules—Structural Fire Design. Brussels (1996)
European Committee for Standardisation (CEN): Eurocode 3: Design of Steel Structures, Part 1.1: General Rules and Rules for Buildings, DD ENV 1-1.EC3 (1993)
European Committee for Standardisation (CEN): Eurocode 4: Design of Composite Steel and Concrete Structures, Part 1.1: General Rules and Rules for Buildings, DD ENV 1-1 (1994)
Guo Z.: Experiment and Calculation of Reinforced Concrete at Elevated Temperatures. Tsinghua University Press. Published by Elsevier Inc., The Netherlands (2011). https://doi.org/10.1016/c2010-0-65988-8
Al-Zwainy F.M.: The use of artificial neural networks for productivity estimation of finishing stone works for building projects. Eng. Dev. J. 16(2), 42–60 (2012)
Landau, S., Everitt, B.S.: A Handbook of Statistical Analyses using SPSS. Chapman & Hall/CRC Press LLC, UK (2004)
Mahmood A.S.: Predicting of torsional strength of prestressed concrete beams using artificial neural networks. Int. J. Sci. Eng. Res. 6(2), 1222–1230 (2015)
Rasheed F.: Artificial neural network circuit for spectral pattern recognition. M.Sc. thesis, Texas A&M University (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zayan, H.S., Farhan, J.A., Mahmoud, A.S., AL-Somaydaii, J.A. (2019). A Parametric Study and Design Equation of Reinforced Concrete Deep Beams Subjected to Elevated Temperature. In: Pradhan, B. (eds) GCEC 2017. GCEC 2017. Lecture Notes in Civil Engineering , vol 9. Springer, Singapore. https://doi.org/10.1007/978-981-10-8016-6_15
Download citation
DOI: https://doi.org/10.1007/978-981-10-8016-6_15
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8015-9
Online ISBN: 978-981-10-8016-6
eBook Packages: EngineeringEngineering (R0)