1 citations · 1 across the 5 of their papers we have counts for
5 papers
A comparison of matrix-free isogeometric Galerkin and collocation methods for Karhunen--Loève expansion
Michal Lukasz Mika, René Rinke Hiemstra, Thomas Joseph Robert Hughes +1
Numerical computation of the Karhunen--Loève expansion is computationally challenging in terms of both memory requirements and computing time. We compare two state-of-the-art metho…
A matrix-free isogeometric Galerkin method for Karhunen-Loève approximation of random fields using tensor product splines, tensor contraction and interpolation based quadrature
Michal Lukasz Mika, Thomas Joseph Robert Hughes, Dominik Schillinger +2
The Karhunen-Loève series expansion (KLE) decomposes a stochastic process into an infinite series of pairwise uncorrelated random variables and pairwise -orthogonal functions.…
Unification of variational multiscale analysis and Nitsche's method, and a resulting boundary layer fine-scale model
Stein K. F. Stoter, Marco F. P. ten Eikelder, Frits de Prenter +4
We show that in the variational multiscale framework, the weak enforcement of essential boundary conditions via Nitsche's method corresponds directly to a particular choice of proj…
A Framework for Data-Driven Computational Dynamics Based on Nonlinear Optimization
Cristian Guillermo Gebhardt, Marc Christian Steinbach, Dominik Schillinger +1
In this article, we present an extension of the formulation recently developed by the authors (A Framework for Data-Driven Computational Mechanics Based on Nonlinear Optimization,…
A Framework for Data-Driven Computational Mechanics Based on Nonlinear Optimization
Cristian Guillermo Gebhardt, Dominik Schillinger, Marc Christian Steinbach +1
Data-Driven Computational Mechanics is a novel computing paradigm that enables the transition from standard data-starved approaches to modern data-rich approaches. At this early st…