1 citations · 1 across the 2 of their papers we have counts for
5 papers · 1 filter
Noise-robust multi-fidelity surrogate modelling for parametric partial differential equations
Benjamin M. Kent, Lorenzo Tamellini, Matteo Giacomini +1
We address the challenge of constructing noise-robust surrogate models for quantities of interest (QoIs) arising from parametric partial differential equations (PDEs), using multi-…
Uncertainty quantification in timber-like beams using sparse grids: theory and examples with off-the-shelf software utilization
Balduzzi Giuseppe, Bonizzoni Francesca, Tamellini Lorenzo
When dealing with timber structures, the characteristic strength and stiffness of the material are made highly variable and uncertain by the unavoidable, yet hardly predictable, pr…
Uncertainty Quantification of Ship Resistance via Multi-Index Stochastic Collocation and Radial Basis Function Surrogates: A Comparison
Chiara Piazzola, Lorenzo Tamellini, Riccardo Pellegrini +3
This paper presents a comparison of two methods for the forward uncertainty quantification (UQ) of complex industrial problems. Specifically, the performance of Multi-Index Stochas…
Compressive Isogeometric Analysis
Simone Brugiapaglia, Lorenzo Tamellini, Mattia Tani
This work is motivated by the difficulty in assembling the Galerkin matrix when solving Partial Differential Equations (PDEs) with Isogeometric Analysis (IGA) using B-splines of mo…
On Expansions and Nodes for Sparse Grid Collocation of Lognormal Elliptic PDEs
Oliver G. Ernst, Björn Sprungk, Lorenzo Tamellini
This work is a follow-up to our previous contribution ("Convergence of sparse collocation for functions of countably many Gaussian random variables (with application to elliptic PD…