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Tito Andriollo

Aarhus University

Nordre Ringgade 1

DK-8000 Aarhus C, 8000

Denmark

SCHOLARLY PAPERS

5

DOWNLOADS

204

TOTAL CITATIONS

1

Scholarly Papers (5)

1.

Solving Plane Crack Problems Via Enriched Holomorphic Neural Networks

Number of pages: 30 Posted: 25 Jan 2025
Matteo Calafà, Henrik Myhre Jensen and Tito Andriollo
Aarhus University, Aarhus University and Aarhus University
Downloads 64 (942,565)

Abstract:

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linear elastic fracture mechanics, physics-informed neural networks, Kolosov-Muskhelishvili, Holomorphic neural networks, stress intensity factor

2.

3D Strain Pattern in Additively Manufactured AlSi10Mg from Digital Volume Correlation

Number of pages: 10 Posted: 10 Nov 2023
Technical University of Denmark, Technical University of Denmark, Danish Technological Institute, Danish Technological Institute and Aarhus University
Downloads 52 (1,052,702)

Abstract:

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laser-based powder bed fusion, X-Ray Tomography, digital volume correlation, strain, AlSi10Mg, Heterogeneities

3.

Predicting plastic strain localization in porous solids using graph neural networks

Number of pages: 33 Posted: 29 Nov 2025
Aarhus University, Aarhus University, Delft University of Technology, Delft University of Technology - Faculty of Civil Engineering and Geosciences and Aarhus University
Downloads 51 (1,074,648)

Abstract:

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Surrogate modeling, Graph neural network, Plasticity, Heterogeneous material, Porous solid, Strain localisation, Multiscale

4.

Efficient Prediction of Strength and Strain Localisation in Porous Solids Via Microstructure-Based Limit Analysis

Number of pages: 20 Posted: 19 May 2024
Jonas Hund, Varvara Kouznetsova and Tito Andriollo
affiliation not provided to SSRN, Eindhoven University of Technology (TUE) - Department of Mechanical Engineering and Aarhus University
Downloads 32 (1,290,922)
Citation 1

Abstract:

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limit load, upper-bound limit analysis, heterogeneous solids, porous solids, strain localisation

5.

A holomorphic neural network framework for 3D boundary value problems governed by harmonic potentials

Number of pages: 29 Posted: 29 May 2026
affiliation not provided to SSRN, Technical University of Denmark and Aarhus University
Downloads 5 (1,579,934)

Abstract:

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Scientific machine learning, Physics-informed neural networks, Holomorphic neural networks, Complex-valued neural networks, Harmonic problems, Linear elasticity