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

• Masonry walls made of cement mortar and clay bricks are investigated.
• Artificial Neural Networks are used.
• The network is trained with around 1950 data items.
• An estimation for the bearing capacity of brick masonry is obtained.

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.