João B. Cardoso

TL;DR: In this article, the authors present a survey on the development and use of Artificial Neural Network (ANN) models in structural reliability analysis, identifying the different types of ANNs, the methods of structural reliability assessment that are typically used, the techniques proposed for ANN training set improvement and also some applications of ANN approximations to structural design and optimization problems.

TL;DR: This paper examines a methodology for computing the probability of structural failure by combining neural networks (NN) and Monte Carlo simulation (MCS), making use of the capability of a NN to approximate a function for reproducing structural behavior, allowing the computation of performance measures at a much lower cost.

TL;DR: A three-dimensional model for bone remodeling is presented, taking into account the hierarchical structure of bone, which concludes that bone tissue arrangement is not a simple stiffness maximization issue but biological factors also play an important role.

TL;DR: In this article, a review of the main theoretical aspects that constitute the basis for most of the constitutive models described is also presented and the main features of each model are thoroughly discussed.

TL;DR: A computational procedure for two-scale topology optimization problem using parallel computing techniques is developed and the applicability of the proposed methodology is demonstrated solving a grand challenge problem that is the simulation of trabecular bone adaptation.