16 citations · 23 across the 4 of their papers we have counts for
5 papers
A Massively Parallel Implementation of Multilevel Monte Carlo for Finite Element Models
Santiago Badia, Jerrad Hampton, Javier Principe
The Multilevel Monte Carlo (MLMC) method has proven to be an effective variance-reduction statistical method for Uncertainty Quantification (UQ) in Partial Differential Equation (P…
A robust and scalable unfitted adaptive finite element framework for nonlinear solid mechanics
Santiago Badia, Manuel Caicedo, Alberto F. Martín +1
In this work, we bridge standard adaptive mesh refinement and coarsening on scalable octree background meshes and robust unfitted finite element formulations for the automatic and…
Embedded multilevel Monte Carlo for uncertainty quantification in random domains
Santiago Badia, Jerrad Hampton, Javier Principe
The multilevel Monte Carlo (MLMC) method has proven to be an effective variance-reduction statistical method for Uncertainty quantification in PDE models. It combines approximation…
FEMPAR: An object-oriented parallel finite element framework
Santiago Badia, Alberto F. Martín, Javier Principe
FEMPAR is an open source object oriented Fortran200X scientific software library for the high-performance scalable simulation of complex multiphysics problems governed by partial d…
Driving mechanisms and streamwise homogeneity in molecular dynamics simulations of nanochannel flows
Vicente Bitrián, Javier Principe
In molecular dynamics simulations, nanochannel flows are usually driven by a constant force, that aims to represent a pressure difference between inlet and outlet, and periodic bou…