39 citations · 79 across the 19 of their papers we have counts for
19 papers
An isotropic recovery-based error estimator algorithm for mesh adaptation in a finite volume environment with application to atmospheric flows
Lander Besabe, Michele Girfoglio, Simona Perotto +2
We develop an Isotropic Recovery-based Error Estimator (IREE) to drive mesh adaptation within a finite volume framework. Recovery-based error estimators are widely used in practice…
Block encoding of sparse matrices with a periodic diagonal structure
Alessandro Andrea Zecchi, Claudio Sanavio, Luca Cappelli +3
Block encoding is a successful technique used in several powerful quantum algorithms. In this work we provide an explicit quantum circuit for block encoding a sparse matrix with a…
Level set-fitted polytopal meshes with application to structural topology optimization
Nicola Ferro, Stefano Micheletti, Nicola Parolini +3
We propose a method to modify a polygonal mesh in order to fit the zero-isoline of a level set function by extending a standard body-fitted strategy to a tessellation with arbitrar…
Advanced Modeling of Rectangular Waveguide Devices with Smooth Profiles by Hierarchical Model Reduction
Gines Garcia-Contreras, Juan Corcoles, Jorge A. Ruiz-Cruz +4
We present a new method for the analysis of smoothly varying tapers, transitions and filters in rectangular waveguides. With this aim, we apply a Hierarchical Model (HiMod) reducti…
Scalable Recovery-based Adaptation on Quadtree Meshes for Advection-Diffusion-Reaction Problems
Pasquale Claudio Africa, Simona Perotto, Carlo de Falco
We propose a mesh adaptation procedure for Cartesian quadtree meshes, to discretize scalar advection-diffusion-reaction problems. The adaptation process is driven by a recovery-bas…
A deep learning approach for detection and localization of leaf anomalies
Davide Calabrò, Massimiliano Lupo Pasini, Nicola Ferro +1
The detection and localization of possible diseases in crops are usually automated by resorting to supervised deep learning approaches. In this work, we tackle these goals with uns…
Enhancing level set-based topology optimization with anisotropic graded meshes
Davide Cortellessa, Nicola Ferro, Simona Perotto +1
We propose a new algorithm for the design of topologically optimized lightweight structures, under a minimum compliance requirement. The new process enhances a standard level set f…
A new fluid-based strategy for the connection of non-matching lattice materials
Nicola Ferro, Simona Perotto, Matteo Gavazzoni
We present a new algorithm for the design of the connection region between different lattice materials. We solve a Stokes-type topology optimization problem on a narrow morphing re…
Isogeometric Hierarchical Model Reduction for advection-diffusion process simulation in microchannels
Simona Perotto, Gloria Bellini, Francesco Ballarin +3
Microfluidics proved to be a key technology in various applications, allowing to reproduce large-scale laboratory settings at a more sustainable small-scale. The current effort is…
Hierarchical model reduction driven by machine learning for parametric advection-diffusion-reaction problems in the presence of noisy data
Massimiliano Lupo Pasini, Simona Perotto
We propose a new approach to generate a reliable reduced model for a parametric elliptic problem, in the presence of noisy data. The reference model reduction procedure is the dire…
Multi-physics inverse homogenization for the design of innovative cellular materials: application to thermo-mechanical problems
Matteo Gavazzoni, Nicola Ferro, Simona Perotto +1
We present a new algorithm to design lightweight cellular materials with required properties in a multi-physics context. In particular, we focus on a thermo-mechanical setting, by…
Anisotropic mesh adaptation for region-based segmentation accounting for image spatial information
Matteo Giacomini, Simona Perotto
A finite element-based image segmentation strategy enhanced by an anisotropic mesh adaptation procedure is presented. The methodology relies on a split Bregman algorithm for the mi…
Scalable Balanced Training of Conditional Generative Adversarial Neural Networks on Image Data
Massimiliano Lupo Pasini, Vittorio Gabbi, Junqi Yin +2
We propose a distributed approach to train deep convolutional generative adversarial neural network (DC-CGANs) models. Our method reduces the imbalance between generator and discri…
A Dimension-Reduction Model for Brittle Fractures on Thin Shells with Mesh Adaptivity
Stefano Almi, Sandro Belz, Stefano Micheletti +1
In this paper we derive a new two-dimensional brittle fracture model for thin shells via dimension reduction, where the admissible displacements are only normal to the shell surfac…
Hierarchical Model Reduction Techniques for Flow Modeling in a Parametrized Setting
Matteo Zancanaro, Francesco Ballarin, Simona Perotto +1
In this work we focus on two different methods to deal with parametrized partial differential equations in an efficient and accurate way. Starting from high fidelity approximations…
Wavelet-Fourier CORSING techniques for multi-dimensional advection-diffusion-reaction equations
Simone Brugiapaglia, Stefano Micheletti, Fabio Nobile +1
We present and analyze a novel wavelet-Fourier technique for the numerical treatment of multidimensional advection-diffusion-reaction equations based on the CORSING (COmpRessed Sol…
Model reduction by separation of variables: a comparison between Hierarchical Model reduction and Proper Generalized Decomposition
Simona Perotto, Michele Giuliano Carlino, Francesco Ballarin
Hierarchical Model reduction and Proper Generalized Decomposition both exploit separation of variables to perform a model reduction. After setting the basics, we exemplify these te…
A POD-selective inverse distance weighting method for fast parametrized shape morphing
Francesco Ballarin, Alessandro D'Amario, Simona Perotto +1
Efficient shape morphing techniques play a crucial role in the approximation of partial differential equations defined in parametrized domains, such as for fluid-structure interact…
Reconstruction of a piecewise constant conductivity on a polygonal partition via shape optimization in EIT
Elena Beretta, Stefano Micheletti, Simona Perotto +1
In this paper, we develop a shape optimization-based algorithm for the electrical impedance tomography (EIT) problem of determining a piecewise constant conductivity on a polygonal…