Pontificia Universidad Católica de Chile Pontificia Universidad Católica de Chile
Garzón-Roca J., Adam J., Sandoval C. and Roca P. (2013)

Estimation of the axial behaviour of masonry walls based on artificial neural networks. http://dx.doi.org/10.1016/j.compstruc.2013.05.006

Revista : Computers & Structures
Volumen : 125
Páginas : 145-152
Tipo de publicación : ISI Ir a publicación


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.