Andrea Rovinelli
Andrea Rovinelli
Applied Materials Division, Argonne National Laboratory
Verified email at anl.gov
Title
Cited by
Cited by
Year
Using machine learning and a data-driven approach to identify the small fatigue crack driving force in polycrystalline materials
A Rovinelli, MD Sangid, H Proudhon, W Ludwig
npj Computational Materials 4 (1), 1-10, 2018
722018
Predicting the 3D fatigue crack growth rate of small cracks using multimodal data via Bayesian networks: In-situ experiments and crystal plasticity simulations
A Rovinelli, MD Sangid, H Proudhon, Y Guilhem, RA Lebensohn, ...
Journal of the Mechanics and Physics of Solids 115, 208-229, 2018
502018
Assessing reliability of fatigue indicator parameters for small crack growth via a probabilistic framework
A Rovinelli, Y Guilhem, H Proudhon, RA Lebensohn, W Ludwig, ...
Modelling and Simulation in Materials Science and Engineering 25 (4), 045010, 2017
342017
Influence of microstructure variability on short crack behavior through postulated micromechanical short crack driving force metrics
A Rovinelli, RA Lebensohn, MD Sangid
Engineering Fracture Mechanics 138, 265-288, 2015
322015
Assessing the reliability of fast Fourier transform-based crystal plasticity simulations of a polycrystalline material near a crack tip
A Rovinelli, H Proudhon, RA Lebensohn, MD Sangid
International Journal of Solids and Structures 184, 153-166, 2020
262020
Validation of microstructure-based materials modeling
M Sangid, SR Yeratapally, A Rovinelli
55th AIAA/ASMe/ASCE/AHS/SC Structures, Structural Dynamics, and Materials …, 2014
72014
Evaluation of statistical variation of microstructural properties and temperature effects on creep fracture of Grade 91
A Rovinelli, MC Messner, DM Parks, TL Sham
Argonne National Lab.(ANL), Argonne, IL (United States), 2018
42018
Acceptance Criteria for the Mechanical Integrity of Clad/Base Metal Interface for High Temperature Nuclear Reactor Cladded Components
B Barua, MC Messner, A Rovinelli, TL Sham
Pressure Vessels and Piping Conference 83815, V001T01A071, 2020
22020
Initial study of notch sensitivity of Grade 91 using mechanisms motivated crystal plasticity finite element method
A Rovinelli, MC Messner, G Ye, TL Sham
Argonne National Lab.(ANL), Argonne, IL (United States), 2019
22019
Initial microstructural model for creep-fatigue damage in Grade 91 steel
A Rovinelli, MC Messner, TL Sham
Argonne National Lab.(ANL), Argonne, IL (United States), 2020
12020
Influence of microstructure variability on short crack growth behavior
A Rovinelli, MD Sangid, RA Lebensohn
12014
A Convolutional Neural Network-based Approach to Field Reconstruction
R Ponciroli, A Rovinelli, L Ibarra
arXiv preprint arXiv:2108.13517, 2021
2021
Microstructural Model for Creep-Fatigue Interaction in Grade 91 Steel
MC Messner, A Venkataraman, A Rovinelli, TL Sham
Argonne National Lab.(ANL), Argonne, IL (United States), 2021
2021
Identify the influence of microstructure on mesoscale creep and fatigue damage
A Rovinelli, M Messner
https://doi.org/10.2172/1658575, 2020
2020
Investigating the Correlation Between Different Effective Stress Measures and the Service Life of Actual High-Temperature Structural Components
A Rovinelli, MC Messner, TL Sham
Pressure Vessels and Piping Conference 83815, V001T01A069, 2020
2020
Combining Experiments and Models via a Bayesian Network Approach to Predict Short Fatigue Crack Growth
A Rovinelli, MD Sangid, Y Guilhem, H Proudhon, R Lebensohn, ...
TMS 2018 Conference, 2018
2018
A General Probabilistic Framework Combining Experiments and Simulations to Identify the Small Crack Driving Force
A Rovinelli
Purdue University, 2017
2017
Microstructurally-Short Crack Growth Driving Force Identification: Combining DCT, PCT, Crystal Plasticity Simulations and Machine Learning Technique
A Rovinelli, MD Sangid, RA Lebensohn, W Ludwig, Y Guilhem, ...
TMS 2016 Conference, 2016
2016
A COMPREHENSIVE COMPARISON BETWEEN DIFFERENT MULTIAXIAL CYCLE COUNTING PROCEDURE
A Rovinelli, MC Messner, TL Sham
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Articles 1–19