Stinville Research Group

Materials Science and Engineering


Computational Approaches for Plastic Localization Prediction

Plastic Localization in Polycrystalline Aggregates for Computationally Designed  Metallic Materials

The relevant models/simulations for mechanical properties prediction through plastic localization simulation are two classes. The first simulations are based on crystal plasticity (CP). They readily describe the complexity of the interface network (grain boundaries, phases, cell walls, etc.) of metallic materials. However, the resulting fields are continuous gradients that fail to represent physical deformation processes at the nano-scale and, consequently, are inaccurate in predicting mechanical properties involving localization phenomena such as fatigue. The second kind of simulation is based on the physical description of the deformation processes, such as slip or deformation twin. Examples are discrete dislocation dynamics (DDD) or molecular dynamic (MD) simulations. They successfully describe the localization processes. However, they are only representative of small regions of materials and prevent predicting the binding effect of the complex interface networks of polycrystalline materials at the micro- and macro-scale due to restricted computational power. 

The present work intends to fill the gap between small-scale physics-based simulations and large-scale gradient prediction simulations by combining CP-based simulations with an explicit description of deformation processes and quantitative experimental data of plastic localization at the nano-scale over representative measurements. Taking into account the physic of plastic localization and the interface network of material will provide the missing link between small-scale deformation and macroscopic properties. Such a novel approach will guide the design of new microstructures for improved properties, reliability, and affordability of metallic materials.




Selected Publications:

M. Pinz, G. Weber, J.C. Stinville, T.M. Pollock, S. Ghosh. Data-driven Bayesian model-based prediction of fatigue crack nucleation in Ni-based superalloys. NPJ Computational Materials, 2022.

F. Wang, G.H. Balbus, Y. Su, S. Xu, J. Shin, P.F. Rottmann, J.C. Stinville, L.H. Mills, O.N. Senkov, I.J. Beyerlein, T.M. Pollock, D.S. Gianola. Multiplicity of Dislocation Pathways in a Refractory Multi-Principal Element Alloy. Science, 2020.

J.M. Hestroffer, M.I. Latypov, J.C. Stinville, M.A. Charpagne, V. Valle, M.P. Miller, T.M. Pollock, I.J. Beyerlein. Development of grain-scale slip activity and lattice rotation fields in Inconel 718. Acta Materialia, 2022.

M.I. Latypov, J.M. Hestroffer, J.C. Stinville, J.R. Mayeur, T.M. Pollock, I.J. Beyerlein. Modeling lattice rotation fields from discrete crystallographic slip bands in superalloys. Extreme Mechanics Letters, 2021.

M.A. Charpagne, J. Hestroffer, A. T. Polonsky, M.P. Echlin, D. Texier, V. Valle, I. J. Beyerlein, T. M.Pollock, J.C. Stinville. Slip localization in Inconel 718: a three-dimensional and statistical perspective. Acta Materialia, 2021.

X. Zhang, J.C. Stinville, T.M. Pollock, F.P.E. Dunne. Crystallography and elastic anisotropy in fatigue crack nucleation at nickel alloy twin boundaries. Journal of the Mechanics and Physics of Solids, 2021.

M.P. Echlin, M. Kasemer, K. Chatterjee, D. Boyce, J.C. Stinville, P.G. Callahan, E. Wielewski, J.S. Park, J.C. Williams, R.M. Suter, T.M. Pollock, M.P. Miller, P.R. Dawson. Microstructure-Based Estimation of Strength and Ductility Distributions for α + β Titanium Alloys. Metallurgical and Materials Transactions A, 2021.

P.R. Dawson, M.P. Miller, T.M. Pollock, J. Wendorf, L.H. Mills, J.C. Stinville, M.A. Charpagne, M.P. Echlin. Mechanical Metrics of Virtual Polycrystals (MechMet). Integrating Materials and Manufacturing Innovation, 2021.

J. Cappola, J.C. Stinville, M.A. Charpagne, P.G. Callahan, M.P. Echlin, T.M. Pollock, A. Pilchak, M. Kasemer. On the Localization of Plastic Strain in Microtextured Regions of Ti-6Al-4V. Acta Materialia, 2021.

M.I. Latypov, J.C. Stinville, J.R. Mayeur, J.M. Hestroffer, T.M. Pollock, I.J. Beyerlein. Insight into microstructure-sensitive elastic strain concentrations from integrated computational modeling and digital image correlation. Scripta Materialia, 2021.



Assitant Professor
201C Materials
Science and Engineering Building
217 333 1066
Mail Address
Jean-Charles Stinville
Materials Science and Engineering
1304 W. Green St.
Urbana, IL 61801
Scroll to Top