V. Plevris and P. Asteris, "Modeling of Masonry Failure Surface under Biaxial Compressive Stress Using Neural Networks", Construction and Building Materials, 55, pp. 447-461, 2014.

Abstract:
Masonry is a brittle anisotropic material that exhibits distinct directional properties because the mortar joints act as planes of weakness. To define failure under biaxial stress, a 3D surface in terms of the two principal stresses and their orientation to the bed joints, is required. In the present study, a novel method is proposed on applying Neural Networks (NNs) to approximate the failure surface for such brittle anisotropic materials. The method comprises a series of NNs that are trained with available experimental data. The results demonstrate the great potential of using NNs for the approximation of masonry failure surface under biaxial compressive stress.

Keywords:
Masonry; Anisotropy; Failure criterion; Failure surface; Biaxial stress; Neural Network; NN; Approximation.