Two-way multi-scaling for predicting fatigue crack nucleation in titanium alloys using parametrically homogenized constitutive models. (July 2019)

• Record Type: Journal Article
• Authors: Ozturk, Deniz; Kotha, Shravan; Pilchak, Adam L.; Ghosh, Somnath
• Is Part Of: Journal of the mechanics and physics of solids. Volume 128(2019)
• Page Start: 181
• Page End: 207
• Publication Date: 2019-07
• Subjects: Two-way multi-scale models -- Fatigue crack nucleation -- Image-based CPFE -- PHCM -- PHCNM; Mechanics, Applied -- Periodicals; Solids -- Periodicals; Mechanics -- Periodicals; Mécanique appliquée -- Périodiques; Solides -- Périodiques; Mechanics, Applied; Solids; Periodicals; 531.05
• DOI: 10.1016/j.jmps.2019.04.009
• Languages: English
• ISSNs: 0022-5096

Abstract

Highlights: Develop a bottom-up (hierarchical) and top-down multi-scale modeling framework for predicting fatigue crack nucleation in Ti alloys. Develop parametrically homogenized constitutive (PHCM) and a crack nucleation model (PHCNM) from micromechanical CPFE analyses. Micromechanical analysis data is utilized by a machine learning code to derive functional forms of PHCM and PHCNM coefficients. Macroscopic FE models created next, by matching correlation functions of the micro-texture in EBSD scans. Multi-scale simulations predict sub-surface nucleation for a majority of dwell cracks Fatigue nucleation follows experimental observations. Abstract: This paper develops a two-way ( bottom-up or hierarchical and top-down ) multi-scale modeling framework for predicting fatigue crack nucleation in structural components of Titanium alloys, e.g. Ti-7Al. Pure micromechanical analyses are deficient in this regard. A parametrically homogenized constitutive model (PHCM) and a parametrically homogenized crack nucleation model (PHCNM) are developed from computational homogenization of crystal plasticity finite element (CPFE) simulation results performed on microstructural statistically equivalent RVEs or M-SERVEs. Image-based CPFE of the M-SERVEs predict time-dependent plastic deformation, as well as location and time-dependent fatigue crack nucleation in the microstructure. Micromechanical analysis data is utilized by a machine learning code to derive functional forms of PHCM and PHCNM coefficients. Macroscopic FE models for Ti-7Al test specimens are created next, by matching correlation functions of the micro-texture and other microstructural variabilities in EBSD scans. Macroscopic simulations of dwell and cyclic loading are performed and nucleation hotspots are identified by PHCNM. Top-down simulations of the local M-SERVEs are then used to probe microstructural fatigue crack nucleation sites and cycles. The multi-scale simulations predict sub-surface nucleation for a majority of dwell cracks, which is corroborated by fractography images. The computed nucleation cycles and spatial distributions across a range of loading conditions follow experimentally observed characteristics of dwell effect in Ti alloys.