Introduce Applicability of Multi-Layer Perceptron to Predict the Behaviour of Semi-Interlocking Masonry Panel

Authors: O. Zarrin, M. Ramezanshirazi

Abstract:

The Semi Interlocking Masonry (SIM) system has been developed in Masonry Research Group at the University of Newcastle, Australia. The main purpose of this system is to enhance the seismic resistance of framed structures with masonry panels. In this system, SIM panels dissipate energy through the sliding friction between rows of SIM units during earthquake excitation. This paper aimed to find the applicability of artificial neural network (ANN) to predict the displacement behaviour of the SIM panel under out-of-plane loading. The general concept of ANN needs to be trained by related force-displacement data of SIM panel. The overall data to train and test the network are 70 increments of force-displacement from three tests, which comprise of none input nodes. The input data contain height and length of panels, height, length and width of the brick and friction and geometry angle of brick along the compressive strength of the brick with the lateral load applied to the panel. The aim of designed network is prediction displacement of the SIM panel by Multi-Layer Perceptron (MLP). The mean square error (MSE) of network was 0.00042 and the coefficient of determination (R2) values showed the 0.91. The result revealed that the ANN has significant agreement to predict the SIM panel behaviour.

Keywords: Semi interlocking masonry, artificial neural network, ANN, multi-layer perceptron, MLP, displacement, prediction.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1474855

References:

[1] H. Derakhshan, "Out-of-Plane Testing of an Unreinforced Masonry Wall Subjected to One-Way Bending", Australian Earthquake Engineering Conference, At Ballarat, Victoria, Australia, 2008.
[2] M. C. Griffith, G. Magenes, G. Melis, and L. Picchi, "Evaluation of out-of-plane stability of unreinforced masonry walls subjected to seismic excitation," Journal of Earthquake Engineering Structures, 2003. 7 (SPEC. 1).
[3] K. Doherty, M.C. Griffith, N. T. K. Lam, and J.Wilson, "Displacement-Based Seismic Analysis for Out-of-Plane Bending of Unreinforced Masonry Walls," Earthquake Engineering and Structural Dynamics, 2002, 31(4).
[4] C.C. Simsir, "Influence of Diaphragm Flexibility on the Out-of-Plane Dynamic Response of Unreinforced Masonry Walls," University of Illinois, 2004.
[5] K. Lin, Y.Z. Totoev, L. Hongjun, W. Chunli, "Experimental Characteristics of Dry Stack Masonry under Compression and Shear Loading," Materials Science Journal, 2015.
[6] Z. Wang, Y.Z. Totoev, A. Page, W. Sher, and K. Lin, "Numerical Simulation of Earthquake Response of Multi-Storey Steel Frame with SIM Infill Panels," Advances in Structural Engineering and Mechanics (ASEM15), 2015.
[7] H. Liu, P.L, K. Lin, and S. Zhao, "Cyclic Behavior of Mortarless Brick Joints with Different Interlocking Shapes," Materials Science Journal, 2016.
[8] Y.P.a.K. Yuen, J.S, "Nonlinear Seismic Responses and Lateral Force Transfer Mechanisms of RC Frames with Different Infill Configurations," Engineeing Structure Journal, 2015, 91.
[9] H. Jiang, X. Liu, and J. Mao, "Full-Scale Experimental Study on Masonry Infilled RC Moment-Resisting Frames Under Cyclic Loads," Engineering Structural Journal, 2015, 91.
[10] L.a.T. Cavaleri, F.D, "Cyclic Response of Masonry Infilled RC Frames: Experimental Results and Simplified Modeling," Soil Dynamics and Earthquakes Engineering, 2014, 65.
[11] L.F. Cavaleri, and M. Papia, "Infilled Frames: Developments in the Evaluation of Cyclic Behaviour Under Lateral Loads," Structural Engineering and Mechanic Journal, 2005, 21.
[12] S.W. Chuang, and Y.Z. Totoev, "Seismic retrofitting of unreinforced masonry buildings," Australian Journal of Structural Engineering, 2004, 6.
[13] A.W. Hendry, "Masonry Walls: Materials and Construction," Construction and Building Materials, 2001, 15.
[14] A.W. Hendry, a.K., F. M, "Masonry Wall Construction," Spon Press:, 2000.
[15] W. Ji-Zong, N.H.-G., and H. Jin-Yun, "The Application of Automatic Acquisition of Knowledge to Mix Design of Concrete," Cement and Concrete Research, 1999, 29: p. 6.
[16] S.S. Lai, "Concrete Strength Prediction by Means of Neural Network," Construction and Building Materials, 1997, 11: p. 8.
[17] C. Jung-Huai, and J.G., "Genetic algorithm in structural damage detection," Computers & Structures, 2001, 79.
[18] J. Kasperkiewicz, J.R., and A. Dubrawski, "HPC Strength Prediction Using Artificial Neural Network," Journal Of Computing In Civil Engineering, 1995, 9.
[19] I.-C. Yeh, "Modeling of Strength of High-Performance Concrete Using Artificial Neural Networks," Cement and Concrete Research, 1998, 28.
[20] M.Y. Mansour , M.D., J.Y. Lee, and J. Zhang, "Predicting the Shear Strength of Reinforced Concrete Beams Using Artificial Neural Networks," Engineering Structures, 26.
[21] N. Hong-Guang, W.J.-Z., "Prediction of Compressive Strength of Concrete by Neural Networks," Cement and Concrete Research, 2000, 30: pp. 6.
[22] S.-C. Lee, "Prediction of Concrete Strength Using Artificial Neural Networks," Engineering Structures, 2002, 25: pp. 849–857.
[23] J. Bai, S.W., J.A. Ware, and B.B. Sabir, "Using Neural Networks To Predict Workability of Concrete Incorporating Metakaolin and Fly Ash," Advances in Engineering Software, 2003, 34: pp. 7.
[24] Q. Wu, B.Y., C. Zhang, L. Wang, G. Ning, and B. Yu, "Displacement Prediction of Tunnel Surrounding Rock: A Comparison of Support Vector Machine and Artificial Neural Network," Hindawi Publishing Corporation Mathematical Problems in Engineering Volume, 2014, pp. 6.
[25] R. Hecht-Nielsen, "Kolmogorov’s mapping neural network existence theorem," Proceedings of the IEEE 1st International Conference on Neural Networks, 1987, pp. 4.
[26] D.M.Wackerly, S. William, and L. Richard, Mathematical Statistics with Applications (7 ed.), Belmont, CA, USA: . ISBN 0-495-38508-5. 2008.
[27] D.E. Rumelhart, G.E. Hinton, and R.J. Williams, "Learning Internal Representations by Error Propagation," California Univ San Diego La Jolla Inst for Cognitive Science, 1985.