In this paper, we present a novel approach to estimate the maximum pressure over the foot plantar surface exerted by a two-layer shoe sole for three distinct phases of the gait cycle. The proposed method is based on Artificial Neural Networks and can be utilized for the determination of the comfort that is related to the sole construction. Input parameters to the proposed neural network are the material properties and the thicknesses of the sole layers (insole and outsole). A set of simulation experiments has been conducted using analytic finite elements analysis in order to compile the necessary dataset for the training and validation of the neural network. Extensive experiments have shown that the developed method is able to provide an accurate alternative (more than 96 %) compared to the highly expensive, with respect to computational and human resources, approaches based on finite element analysis.

The main goal of the present article was to develop a methodology for the calculation of the flexural properties of a cement-based matrix with different multi-walled carbon nanotubes’ (CNTs) volume fraction as a reinforcement at early age. The homogenization tool of the ANSA^® software package was exploited for the modelling of the inclusion geometries in a cubic matrix and for mesh generation. A Representative Volume Element (RVE) was constructed with either random orientation tensor algorithm or periodic geometry algorithm tools and for different concentrations of the nano-reinforcement. Finite element modelling (FEM) of the pre-cracked specimens for flexural tests followed, and the numerical results were compared against the experimental ones. Different input parameters were considered, including the reinforcement Poisson’s ratio (ν_CNT) as well as the effective elastic modulus (E_CNT) to predict the flexural behaviour of the nano-reinforced matrices. It was found that both parameters play a pivotal role for the numerical simulation and the best simulation results were obtained for CNTs’ effective elastic modulus E_CNT = 470 GPa and Poisson’s ratio of ν_CNT = 0.10 values for the two (2) different investigated concentrations of carbon nanotubes (0.6 and 1.2%, respectively) in the cementitious matrix.