MSE Seminar: “Developments in Fatigue Resistant Microstructure Selection and Design”


3:00 pm-4:00 pm
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Rhines Hall Room 125
549 Gale Lemerand Drive
Gainesville, FL 32611


David McDowell, Ph.D.

Carter N. Paden, Jr. Distinguished Chair in Metals Processing
Georgia Institute of Technology

Dr. David McDowell, Regents’ Professor, and Carter N. Paden, Jr. Distinguished Chair in Metals Processing, joined Georgia Tech in 1983 and holds appointments in both the GWW School of Mechanical Engineering and the School of Materials Science and Engineering.

Director of the Mechanical Properties Research Laboratory from 1992-2012, he served from 2012-2020 as Executive Director of the Institute for Materials (IMat), a Georgia Tech interdisciplinary research institute charged with cultivating a campus-wide materials innovation ecosystem for research and education.

McDowell’s current research interests focus on microstructure-sensitive computational approaches to variability in fatigue of advanced alloy systems, including extreme value responses such as high cycle fatigue, novel concurrent atomistic-continuum (CAC) coarse-grained atomistic modeling for predictive materials simulation, multiscale chemo-physics modeling of point and line defect interactions with application to environmental effects, and hierarchical continuum multiscale modeling approaches including uncertainty quantification and propagation across length and time scales (cf. Uncertainty in Multiscale Materials Modeling, Eds. Y. Wang and D.L. McDowell, Elsevier, 2020, ISBN: 9780081029411).

He has pursued the development of methods that employ computational materials science and mechanics to inform the design of materials, having co-authored a related textbook (Integrated Design of Multiscale, Multifunctional Materials and Products, Elsevier, 2010, ISBN-13: 978-1-85617-662-0).

McDowell is currently a member of the editorial boards of NPJ Computational Materials and several other journals and served as co-Editor of the International Journal of Fatigue from 2008 through 2020. In 2019-2020, he was awarded the Georgia Tech Class of 1934 Distinguished Professor Award and was elected as a Fellow of TMS. He was elected as an Honorary Member of AIME in 2021.


The formation and early growth of fatigue cracks in structural alloys is a challenging rare-event phenomenon related to the statistical distributions of microstructure features. At the scale of individual grains or phases, fundamental processes such as slip band structures and associated slip irreversibility lead to the formation and growth of microstructurally small cracks. Bottom-up models for early mesoscopic fatigue crack “nucleation” processes are complicated by details of material composition, environment, and defect structures, and are largely inaccessible to predictive atomistic and discrete modeling methods. Correlations based on some decomposition of fatigue crack initiation and propagation have uncertainty associated with microstructure effects and sample size of observations, along with limitations on scale-appropriate fatigue crack growth relations.

We review our developments over the past decade in mesoscopic computational polycrystal plasticity approaches to define and compute Fatigue Indicator Parameters (FIPs) that serve as surrogate measures of driving forces for fatigue crack formation and microstructurally small crack growth. Attention is focused on constructing the extreme value distributions of FIPs as a function of microstructure, which facilitates relative rank-ordering of fatigue resistance of microstructures as a function of thermomechanical process history for a given composition. Applications considered include high cycle fatigue responses of Ni-base superalloys, Ti alloys, and Al alloys. Advanced data science correlations are considered as a means to reduce the uncertainty associated with model forms and parameters and to accelerate the assessment of FIP distributions to characterize hot spots and rank order microstructures in terms of resistance to fatigue crack formation and early growth.


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Department of Materials Science & Engineering