Uncertainty quantification in ICME workflows for fatigue critical computational modeling G Whelan, DL McDowell Engineering Fracture Mechanics 220, 106673, 2019 | 19 | 2019 |
Electrochemical and microstructural analysis of FeS films from acidic chemical bath at varying temperatures, pH, and immersion time L Khaksar, G Whelan, J Shirokoff International Journal of Corrosion 2016, 2016 | 19 | 2016 |
Machine learning-enabled uncertainty quantification for modeling structure–property linkages for fatigue critical engineering alloys using an ICME workflow G Whelan, DL McDowell Integrating Materials and Manufacturing Innovation 9 (4), 376-393, 2020 | 10 | 2020 |
Uncertainty informed integrated computational materials engineering for design and development of fatigue critical alloys GF Whelan Georgia Institute of Technology, 2020 | 3 | 2020 |
Microstructure-Sensitive ICME Workflows for Fatigue Critical Applications KS Stopka, G Whelan, DL McDowell SAMPE 2019-Charlotte, NC, May 2019, 2019 | 2 | 2019 |
Using Integrated Computational Materials Engineering for Oil and Gas Applications G Whelan Offshore Technology Conference, D031S033R007, 2024 | | 2024 |
Interpretable machine learning for microstructure-dependent models of fatigue indicator parameters CK Hansen, GF Whelan, JD Hochhalter International Journal of Fatigue 178, 108019, 2024 | | 2024 |
Using digital twins to accelerate qualification and certification of fatigue critical components G Whelan, J Gong, GB Olson 31st Symposium of the International Committee of Aeronautical Fatigue, 2023 | | 2023 |