31 citations · 43 across the 7 of their papers we have counts for
9 papers
The Role of Bifurcations in Parameter Estimation: A UQ Analysis of the Non-spatial Klausmeier Model
Lisa Beer, Christian Kuehn, Chiara Piazzola
We employ uncertainty quantification methods to investigate how parameter identifiability changes in the vicinity of a bifurcation point. We perform numerical experiments on the no…
Global Sensitivity Analysis of Spatial Sets: Finite-Element-Based Estimation and the Role of Observation Windows
Farbod Chamanian, Chiara Piazzola, Elisabeth Ullmann
In this work we consider numerical models with random input parameters, where the model output is a spatially distributed random field. We carry out a statistical sensitivity analy…
Uncertainty quantification analysis of bifurcations of the Allen--Cahn equation with random coefficients
Christian Kuehn, Chiara Piazzola, Elisabeth Ullmann
In this work we consider the Allen--Cahn equation, a prototypical model problem in nonlinear dynamics that exhibits bifurcations corresponding to variations of a deterministic bifu…
Data-informed uncertainty quantification for laser-based powder bed fusion additive manufacturing
Mihaela Chiappetta, Chiara Piazzola, Lorenzo Tamellini +3
We present an efficient approach to quantify the uncertainties associated with the numerical simulations of the laser-based powder bed fusion of metals processes. Our study focuses…
Sparse-grids uncertainty quantification of part-scale additive manufacturing processes
Mihaela Chiappetta, Chiara Piazzola, Massimo Carraturo +3
The present paper aims at applying uncertainty quantification methodologies to process simulations of powder bed fusion of metal. In particular, for a part-scale thermomechanical m…
The Sparse Grids Matlab kit -- a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification
Chiara Piazzola, Lorenzo Tamellini
The Sparse Grids Matlab Kit provides a Matlab implementation of sparse grids, and can be used for approximating high-dimensional functions and, in particular, for surrogate-model-b…
Comparing Multi-Index Stochastic Collocation and Multi-Fidelity Stochastic Radial Basis Functions for Forward Uncertainty Quantification of Ship Resistance
Chiara Piazzola, Lorenzo Tamellini, Riccardo Pellegrini +3
This paper presents a comparison of two multi-fidelity methods for the forward uncertainty quantification of a naval engineering problem. Specifically, we consider the problem of q…
A note on tools for prediction under uncertainty and identifiability of SIR-like dynamical systems for epidemiology
Chiara Piazzola, Lorenzo Tamellini, Raúl Tempone
We provide an overview of the methods that can be used for prediction under uncertainty and data fitting of dynamical systems, and of the fundamental challenges that arise in this…
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…