activity
20192022
most citedUncertainty quantification in timber-like beams using sparse grids: theory and examples with off-the-shelf software utilization

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

math.NA20221 cited

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…

math.NA2020

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…

math.NA2020

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…

cs.CE2019

Parametric shape optimization for combined additive-subtractive manufacturing

Christian Altenhofen, Marco Attene, Oliver Barrowclough +6

In the industrial practice, additive manufacturing processes are often followed by post-processing operations such as subtractive machining, milling, etc. to achieve the desired su…

math.NA2019

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…