STRUCTURAL ANALYSIS WITH THE FINITE ELEMENT METHOD Linear Statics Volume 1:
The Basis and Solids Eugenio Oñate The two volumes of this book cover most of the …

Physics-informed neural networks (PINNs) are an emerging method for solving partial
differential equations (PDEs) and have been widely applied in the field of scientific …

This paper aims to provide a machine learning framework to simulate two-phase flow in
porous media. The proposed algorithm is based on Physics-informed neural networks …

Mechanical engineering, an engineering discipline forged and shaped by the needs of the
industrial revolution, is once again asked to do its substantial share in the call for industrial …

Computational modeling remains key to the acoustic design of various applications, but it is
constrained by the cost of solving large Helmholtz problems at high frequencies. This paper …

This article is a review of basic concepts and tools devoted to a posteriori error estimation for
problems solved with the finite element method. For the sake of simplicity and clarity, we …

Upper and lower bounds of the collapse load factor are here obtained as the optimum
values of two discrete constrained optimization problems. The membership constraints for …

This work is devoted to the description of an algorithm for automatic quadrilateral mesh
generation. The technique is based on a recursive decomposition of the domain into …

A degree adaptive Hybridizable Discontinuous Galerkin (HDG) method for the solution of the
incompressible Navier–Stokes equations is presented. The key ingredient is an accurate …

SUMMARY A p‐adaptive hybridizable discontinuous Galerkin method for the solution of
wave problems is presented in a challenging engineering problem. Moreover, its …