Estimation of the axial behaviour of masonry walls based on Artificial Neural Networks

被引:42
作者
Garzon-Roca, Julio [1 ]
Adam, Jose M. [1 ]
Sandoval, Cristian [2 ]
Roca, Pere [3 ]
机构
[1] Univ Politecn Valencia, ICITECH, Dept Ingn Construcc & Proyectos Ingn Civil, E-46071 Valencia, Spain
[2] Pontificia Univ Catolica Chile, Sch Architecture, Dept Struct & Geotech Engn, Santiago, Chile
[3] Univ Politecn Cataluna, Dept Construct Engn, ES-08034 Barcelona, Spain
关键词
Brick masonry wall; Load-bearing capacity; Reduction factors; Artificial Neural Networks; BOUNDED COMPRESSIVE STRENGTH; ECCENTRIC VERTICAL LOADS; LATERAL LOADS; STABILITY; DEFORMABILITY; COLUMNS;
D O I
10.1016/j.compstruc.2013.05.006
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Estimating the load-bearing capacity of brick masonry walls is a fundamental aspect of the design or retrofitting of this type of structures. This paper presents a new ANN-based proposal as an alternative to the different existing methods. The proposal takes into account load eccentricity, wall slenderness ratio and stiffness and masonry tensile strength, and is validated by a comparison with the Eurocode 6 and other formulations as well as three other experimental studies. The proposal closely agrees with the experimental results and is less conservative than Eurocode 6 and therefore more likely to provide the optimum design for masonry walls. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:145 / 152
页数:8
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