- Bayesian parameter estimation for the inclusion of uncertainty in progressive damage simulation of composites. Dans: Composite Structures, v. 321 (octobre 2023). (2023):
- Development of aviation industry-oriented methodology for failure predictions of brittle bonded joints using probabilistic machine learning. Dans: Composite Structures, v. 297 (octobre 2022). (2022):
- An efficient multi-scale approach for viscoelastic analysis of woven composites under bending. Dans: Composite Structures, v. 292 (juillet 2022). (2022):
- Machine learning assisted characterisation and simulation of compressive damage in composite laminates. Dans: Composite Structures, v. 273 (octobre 2021). (2021):
- Virtual Characterization of Nonlocal Continuum Damage Model Parameters using a High Fidelity Finite Element Model. Dans: Composite Structures, v. 256 (janvier 2021). (2021):
- Theory-guided machine learning for damage characterization of composites. Dans: Composite Structures, v. 246 (août 2020). (2020):
- Measuring the negative pressure during processing of advanced composites. Dans: Composite Structures, v. 203 (novembre 2018). (2018):
- Strain-Softening Response and Failure Prediction in Notched Oriented Strand Board. Dans: Journal of Materials in Civil Engineering (ASCE), v. 31, n. 6 (juin 2019). (2019):