Andrea Rovinelli

Using machine learning and a data-driven approach to identify the small fatigue crack driving force in polycrystalline materials

Wolfgang Ludwig, Henry Proudhon, Michael D. Sangid, 2018, npj Computational Materials.

Investigating the Correlation Between Different Effective Stress Measures and the Service Life of Actual High-Temperature Structural Components

Mark C. Messner, T.-L. Sham, Andrea Rovinelli, 2020 .

Validation of Microstructure-Based Materials Modeling

Saikumar R. Yeratapally, Michael D. Sangid, Andrea Rovinelli, 2014 .

A Convolutional Neural Network-based Approach to Field Reconstruction pdf

Roberto Ponciroli, Andrea Rovinelli, Lander Ibarra, 2021, ArXiv.

Influence of microstructure variability on short crack behavior through postulated micromechanical short crack driving force metrics

Ricardo A. Lebensohn, Michael D. Sangid, Andrea Rovinelli, 2015 .

Assessing the reliability of fast Fourier transform-based crystal plasticity simulations of a polycrystalline material near a crack tip

Ricardo A. Lebensohn, Henry Proudhon, Michael D. Sangid, 2020 .

Assessing reliability of fatigue indicator parameters for small crack growth via a probabilistic framework

Ricardo A. Lebensohn, Henry Proudhon, Michael D. Sangid, 2017 .