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Predicting the Shear Strength of Fiber Reinforced Concrete Corbels Via Support Vector Machines

Year 2018, Volume: 39 Issue: 2, 496 - 514, 29.06.2018

Ahmet Emin Kurtoğlu

https://doi.org/10.17776/csj.434263
Cited By: 2

Abstract

Precast corbels are commonly preferred structural members in industrial
buildings. In this study, a novel application of support vector machines (SVM)
is employed for the prediction of ultimate shear strength of fiber reinforced
corbels, for the first time in literature. SVM models are developed and analyzed
using a database of available test results in literature. Predictions of the
selected model are compared against the test results and those of available
model proposed by Fattuhi (1994). Proposed model has the capability to predict
the shear strength of both steel fiber reinforced concrete (SFRC) and glass
fiber reinforced concrete (GFRC) corbels. Additionally, a parametric study with
a wide range of variables is carried out to test the effect of each parameter
on the shear strength. The results confirm the high prediction capacity of
proposed model.

Keywords

Support vector machines reinforced concrete corbel fiber reinforced concrete steel fiber glass fiber shear strength

References

  • [1]. American Concrete Institute, State-of-the-Art Report on Fiber Reinforced Concrete. ACI Committee 544, 2002.
  • [2]. Fanella D.A. and Naaman A.E., Stress-Strain Properties of Fiber Reinforced Mortar in Compression, J. Amer. Concr. Inst., 82 (1985) 475-483.
  • [3]. Thomas J. and Ramaswamy A., Mechanical Properties of Steel Fiber-Reinforced Concrete, J. Mater. Civ. Eng., 19 (2007) 385-392.
  • [4]. Deluce J.R., Cracking Behaviour of Steel Fibre Reinforced Concrete Containing Conventional Steel Reinforcement. MSc Thesis, 2011.
  • [5]. Fattuhi N.I., SFRC Corbel Tests, ACI Struct. J., 84 (1987) 119-123.
  • [6]. Fattuhi N.I., Column-Load Effect on Reinforced Concrete Corbels, J. Struct. Eng., 116 (1990) 188-197.
  • [7]. Fattuhi N.I., Strength of FRC Corbels in Flexure, J. Struct. Eng., 120 (1994) 360-377.
  • [8]. Fattuhi N.I. and Hughes B.P., Ductility of Reinforced Concrete Corbels Containing Either Steel Fibers or Stirrups, ACI Struct. J., 86 (1989) 644-651.
  • [9]. Fattuhi N.I and Hughes B.P., Reinforced Steel Fiber Concrete Corbels with Various Shear Span-To-Depth Ratios, ACI Mater. J., 86 (1989) 590-596. [10]. Campione G., La Mendola L., Mangiavillano M.L., Steel fiber-Reinforced Concrete Corbels: Experimental Behavior and Shear Strength Prediction, ACI Struct. J., 104 (2007) 570-579.
  • [11]. Campione G., Performance of Steel Fibrous Reinforced Concrete Corbels Subjected to Vertical and Horizontal Loads, J. Struct. Eng., 135 (2009) 519-529.
  • [12]. Muhammad A., Behavior and Strength of High-Strength Fiber Reinforced Concrete Corbels Subjected to Monotonic or Cyclic (Repeated) Loading, PhD thesis, Dept. of Building and Construction Eng., University of Technology, Baghdad, 1998.
  • [13]. Yang J.M., Lee J.H., Yoon, Y.S., Cook W.D., Mitchell D., Influence of Steel Fibers and Headed Bars on The Serviceability of High-Strength Concrete Corbels, J. Struct. Eng., 138 (2011) 123-129.
  • [14]. Kurtoglu A.E., Gulsan M.E., Abdi H.A., Kamil M.A., Cevik A., Fiber Reinforced Concrete Corbels: Modeling Shear Strength Via Symbolic Regression. Comp. and Concr., 20 (2017) 1-10.
  • [15]. Boser B.E., Guyon I.M., Vapnik V.N., A Training Algorithm for Optimal Margin Classifiers, Proceedings of The Fifth Annual Workshop on Computational Learning Theory, (1992) 144-152.
  • [16]. Wang, L., (Ed). Support Vector Machines: Theory and Applications. Berlin: Springer, 2005.
  • [17]. Chen N., Lu W., Yang J., Li G., (Eds). Support Vector Machine in Chemistry. World Scientific, 2004.
  • [18]. Cherkassky V. and Ma Y., Selection of Meta-Parameters for Support Vector Regression, Artificial Neural Networks - ICANN 2002, (2002) 687-693.
  • [19]. Zhang W. and Song Z., Prediction of Concrete Corrosion in Sulfuric Acid by SVM-Based Method, 2nd International Conference on Electronic and Mechanical Engineering and Information Technology, 2012.
  • [20]. Yang S., Fang C.Q., Yuan Z.J., Study on Mechanical Properties of Corroded Reinforced Concrete Using Support Vector Machines, Appl. Mech. and Mater., 578 (2014) 1556-1561.
  • [21]. Cao Y.F., Wu W., Zhang H.L., Pan J.M., Prediction of the Elastic Modulus of Self-Compacting Concrete Based on SVM, Appl. Mech. and Mater., 357 (2013) 1023-1026.
  • [22]. Li H.S., Lu Z.Z., Yue, Z.F., Support Vector Regression for Structural Reliability Analysis, Appl. Math. and Mech., 27 (2006) 1295-1303.
  • [23]. Okkan U., Serbes Z.A., Rainfall–Runoff Modeling Using Least Squares Support Vector Machines, Environmetrics, 23 (2012) 549-564.
  • [24]. Çevik A., Kurtoğlu A.E., Bilgehan M., Gülşan M.E., Albegmprli H.M., Support Vector Machines in Structural Engineering: A Review, J. Civil Eng. and Manag., 21 (2015) 261-281.
  • [25]. Kumar S., Barai S., Neural Networks Modeling of Shear Strength of SFRC Corbels Without Stirrups, Appl. Soft Comput., 10 (2010) 135-148.
  • [26]. Sherrod P.H., DTREG Predictive Modeling Software, Users Manual, 2008.

Lifli Betonarme Kısa Konsolların Kesme Dayanımının Destek Vektör Makineleri ile Tahmini

Year 2018, Volume: 39 Issue: 2, 496 - 514, 29.06.2018

Ahmet Emin Kurtoğlu

https://doi.org/10.17776/csj.434263
Cited By: 2

Abstract

Prefabrik kısa konsollar, özellikle sanayi
yapılarında sıkça tercih edilen yapı elemanlarıdır. Bu çalışmada, lifli
betonarme kısa konsolların kesme dayanımı, literatürde ilk defa, destek vektör
makineleri (DVM) ile tahmin edilmiştir. Mevcut deneysel veriler kullanılarak
DVM modelleri oluşturulmuş ve tahmin performansları analiz edilmiştir. Seçilen
modelin tahminleri, deney sonuçları ve literatürde mevcut olan modelin
(Fattuhi, 1994) tahminleri ile karşılaştırılmıştır. Model, çelik lifli kısa
konsolların yanı sıra cam lifli konsolların taşıma kapasitelerini de tahmin
edebilmektedir. Ayrıca model, her bir girdi parametresinin etkisini incelemek
amacıyla, parametrik analize tabi tutulmuştur. Sonuçlar, önerilen modelin yüksek tahmin
kapasitesine sahip olduğunu göstermektedir.

Keywords

Destek vektör makineleri betonarme kısa konsol lifli betonarme çelik lif cam lif kesme dayanımı

References

  • [1]. American Concrete Institute, State-of-the-Art Report on Fiber Reinforced Concrete. ACI Committee 544, 2002.
  • [2]. Fanella D.A. and Naaman A.E., Stress-Strain Properties of Fiber Reinforced Mortar in Compression, J. Amer. Concr. Inst., 82 (1985) 475-483.
  • [3]. Thomas J. and Ramaswamy A., Mechanical Properties of Steel Fiber-Reinforced Concrete, J. Mater. Civ. Eng., 19 (2007) 385-392.
  • [4]. Deluce J.R., Cracking Behaviour of Steel Fibre Reinforced Concrete Containing Conventional Steel Reinforcement. MSc Thesis, 2011.
  • [5]. Fattuhi N.I., SFRC Corbel Tests, ACI Struct. J., 84 (1987) 119-123.
  • [6]. Fattuhi N.I., Column-Load Effect on Reinforced Concrete Corbels, J. Struct. Eng., 116 (1990) 188-197.
  • [7]. Fattuhi N.I., Strength of FRC Corbels in Flexure, J. Struct. Eng., 120 (1994) 360-377.
  • [8]. Fattuhi N.I. and Hughes B.P., Ductility of Reinforced Concrete Corbels Containing Either Steel Fibers or Stirrups, ACI Struct. J., 86 (1989) 644-651.
  • [9]. Fattuhi N.I and Hughes B.P., Reinforced Steel Fiber Concrete Corbels with Various Shear Span-To-Depth Ratios, ACI Mater. J., 86 (1989) 590-596. [10]. Campione G., La Mendola L., Mangiavillano M.L., Steel fiber-Reinforced Concrete Corbels: Experimental Behavior and Shear Strength Prediction, ACI Struct. J., 104 (2007) 570-579.
  • [11]. Campione G., Performance of Steel Fibrous Reinforced Concrete Corbels Subjected to Vertical and Horizontal Loads, J. Struct. Eng., 135 (2009) 519-529.
  • [12]. Muhammad A., Behavior and Strength of High-Strength Fiber Reinforced Concrete Corbels Subjected to Monotonic or Cyclic (Repeated) Loading, PhD thesis, Dept. of Building and Construction Eng., University of Technology, Baghdad, 1998.
  • [13]. Yang J.M., Lee J.H., Yoon, Y.S., Cook W.D., Mitchell D., Influence of Steel Fibers and Headed Bars on The Serviceability of High-Strength Concrete Corbels, J. Struct. Eng., 138 (2011) 123-129.
  • [14]. Kurtoglu A.E., Gulsan M.E., Abdi H.A., Kamil M.A., Cevik A., Fiber Reinforced Concrete Corbels: Modeling Shear Strength Via Symbolic Regression. Comp. and Concr., 20 (2017) 1-10.
  • [15]. Boser B.E., Guyon I.M., Vapnik V.N., A Training Algorithm for Optimal Margin Classifiers, Proceedings of The Fifth Annual Workshop on Computational Learning Theory, (1992) 144-152.
  • [16]. Wang, L., (Ed). Support Vector Machines: Theory and Applications. Berlin: Springer, 2005.
  • [17]. Chen N., Lu W., Yang J., Li G., (Eds). Support Vector Machine in Chemistry. World Scientific, 2004.
  • [18]. Cherkassky V. and Ma Y., Selection of Meta-Parameters for Support Vector Regression, Artificial Neural Networks - ICANN 2002, (2002) 687-693.
  • [19]. Zhang W. and Song Z., Prediction of Concrete Corrosion in Sulfuric Acid by SVM-Based Method, 2nd International Conference on Electronic and Mechanical Engineering and Information Technology, 2012.
  • [20]. Yang S., Fang C.Q., Yuan Z.J., Study on Mechanical Properties of Corroded Reinforced Concrete Using Support Vector Machines, Appl. Mech. and Mater., 578 (2014) 1556-1561.
  • [21]. Cao Y.F., Wu W., Zhang H.L., Pan J.M., Prediction of the Elastic Modulus of Self-Compacting Concrete Based on SVM, Appl. Mech. and Mater., 357 (2013) 1023-1026.
  • [22]. Li H.S., Lu Z.Z., Yue, Z.F., Support Vector Regression for Structural Reliability Analysis, Appl. Math. and Mech., 27 (2006) 1295-1303.
  • [23]. Okkan U., Serbes Z.A., Rainfall–Runoff Modeling Using Least Squares Support Vector Machines, Environmetrics, 23 (2012) 549-564.
  • [24]. Çevik A., Kurtoğlu A.E., Bilgehan M., Gülşan M.E., Albegmprli H.M., Support Vector Machines in Structural Engineering: A Review, J. Civil Eng. and Manag., 21 (2015) 261-281.
  • [25]. Kumar S., Barai S., Neural Networks Modeling of Shear Strength of SFRC Corbels Without Stirrups, Appl. Soft Comput., 10 (2010) 135-148.
  • [26]. Sherrod P.H., DTREG Predictive Modeling Software, Users Manual, 2008.
There are 25 citations in total.

Details

Primary Language English
Journal Section Engineering Sciences
Authors

Ahmet Emin Kurtoğlu

Publication Date June 29, 2018
Submission Date July 13, 2017
Acceptance Date May 8, 2018
Published in Issue Year 2018Volume: 39 Issue: 2

Cite

APA Kurtoğlu, A. E. (2018). Predicting the Shear Strength of Fiber Reinforced Concrete Corbels Via Support Vector Machines. Cumhuriyet Science Journal, 39(2), 496-514. https://doi.org/10.17776/csj.434263

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