RT Journal Article
T1 Estimation of the axial behaviour of masonry walls based on Artificial Neural Networks
A1 Garzón Roca, Julio
A1 Adam, José Miguel
A1 Roca, Pere
A1 Sandoval, Cristian
AB 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.
PB Elsevier
SN 0045-7949
YR 2013
FD 2013
LK https://hdl.handle.net/20.500.14352/95250
UL https://hdl.handle.net/20.500.14352/95250
LA eng
NO Garzón-Roca, Julio, et al. «Estimation of the Axial Behaviour of Masonry Walls Based on Artificial Neural Networks». Computers & Structures, vol. 125, septiembre de 2013, pp. 145-52. https://doi.org/10.1016/j.compstruc.2013.05.006.
NO Ministerio de Ciencia e Innovación (España)
DS Docta Complutense
RD 8 abr 2025