Modeling the Shear Strength of Reinforced Aerated Concrete Slabs via Support Vector Regression

Öz

Autoclaved aerated concrete (AAC) attracts attention as it provides superior material characteristics such as high thermal insulation and environmentally friendly properties. Apart from non-structural applications, AAC is being considered as a structural material due to its characteristics such as lighter weight compared to normal concrete, resulting in lower design cost. This study focuses on the feasibility of support vector regression (SVR) in predicting the shear resistance of reinforced AAC slabs. An experimental dataset with 271 data points extracted from eight sources is used to develop models. Based on random selection, the dataset is divided into two portions, 75% for model development and 25% is for testing the validity of the model. Two SVR model types (epsilon and Nu) and four kernel functions (linear, polynomial, sigmoid and radial basis) are used for model development and the results of each model and kernel type is presented in terms of correlation coefficient (R2) and mean squared error (MSE). Results show that epsilon model type with radial basis function yields the best SVR model.

Anahtar Kelimeler

• Autoclaved aerated concrete,reinforced concrete slab,shear strength,support vector regression,modelling

Kaynakça

1. A. Thongtha, S. Maneewan, C. Punlek, and Y. Ungkoon, "Investigation of the compressive strength, time lags and decrement factors of AAC-lightweight concrete containing sugar sediment waste", Energy and Buildings, vol. 84, No., pp. 516-525, 2014.
2. X. Qu and X. Zhao, "Previous and present investigations on the components, microstructure and main properties of autoclaved aerated concrete–A review", Construction and Building Materials, vol. 135, pp. 505-516, 2017.
3. A. Bonakdar, F. Babbitt, and B. Mobasher, "Physical and mechanical characterization of fiber-reinforced aerated concrete (FRAC)", Cement and Concrete Composites, vol. 38, pp. 82-91, 2013.
4. A. Taghipour, E. Canbay, B. Binici, A. Aldemir, U. Uzgan, and Z. Eryurtlu, "Seismic behavior of reinforced autoclaved aerated concrete wall panels", ce/papers, vol. 2, No. 4, pp. 259-265, 2018.
5. S. Aroni and B. Cividini, "Shear strength of reinforced aerated concrete slabs", Materials and Structures, vol. 22, No. 6, pp. 443-449, 1989.
6. N. Edgren, "Shear tests on Siporex slabs (Newarthill Factory, UK)'", unpublished report (Internationella Siporex AB, Central Laboratory, 1981–82).
7. A. Matsumura, "Shear strength and behavior of reinforced autoclaved lightweight cellular concrete members", Trans. Architect. Inst. Jpn, vol. 343, pp. 13-23, 1984.
8. Y. Kanoh, "Report of Hebel research'", unpublished report (Meiji University, 1969).

9. Y. Kanoh, "Shear strength of the reinforced autoclaved lightweight concrete one-way slabs'", Proceedings of Research Papers of the Faculty of Engineering, Meiji University, vol., No. 21, 1966.
10. N. Edgren, "Shear tests on Siporex slabs (Dalby Factory, Sweden)'", unpublished report (Internationella Siporex AB, Central Laboratory, 1979).
11. B. Cividini, "Ispitivanje granicne nosivosti armiranih ploca od plinobetona (Investigation of bearing capacity of reinforced aerated concrete slabs)", Proceedings of 17th JUDIMK Congress, Sarajevo, October, pp. 19-41, 1982.
12. D. Briesemann, Die schubtragfähigkeit bewehrter platten und balken aus dampfgehärtetem gasbeton anch versuchen, Ernst, 1980.
13. R. Blaschke, "Shear load behaviour of AAC reinforced units of high compressive strength (GB 6.6)'", unpublished report (Ytong Research Laboratory, Schrobenhausen, 1988), 1988.
14. N. Edgren, "Shear tests on Siporex slabs (Bernon Factory, France)'", unpublished report (Internationella Siporex AB, Central Laboratory, 1979–80).
15. P. Regan, "Shear in reinforced aerated concrete", International Journal of Cement Composites and Lightweight Concrete, vol. 1, No. 2, pp. 47-61, 1979.
16. B.E. Boser, I.M. Guyon, and V.N. Vapnik, "A training algorithm for optimal margin classifiers", Proceedings of the fifth annual workshop on Computational learning theory, pp. 144-152, 1992.
17. L. Wang, Support Vector Machines: theory and applications, vol. 177, Springer, 2005
18. N. Chen, W. Lu, J. Yang, and G. Li, Support vector machine in chemistry, vol. 11, World Scientific, 2004
19. V. Cherkassky and Y. Ma, Selection of meta-parameters for support vector regression, Artificial Neural Networks— ICANN 2002, Springer, 2002, 687-693.
20. G.N. Smith, "Probability and statistics in civil engineering", Collins Professional and Technical Books, vol. 244, No., 1986.