Parametrically homogenized constitutive models (PHCMs) from micromechanical crystal plasticity FE simulations: Part II: Thermo-elasto-plastic model with experimental validation for titanium alloys

Kotha, Shravan; Ozturk, Deniz; Ghosh, Somnath

doi:10.1016/j.ijplas.2019.05.007

Cited by 33 publications

(28 citation statements)

References 21 publications

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“…Numerical implementation and integration of the PHCMs in the UMAT have been described in details in ref. 6 . In this section, PHCM predictions are compared with micromechanical CPFE simulations under various loading conditions to demonstrate its accuracy and efficiency.…”

Section: Overviewmentioning

confidence: 99%

“…Validating PHCM with micromechanics-based CPFE simulations Experimental validation of the PHCMs for a near-α Ti6242S alloy containing~95% primary α phase has been successfully conducted in ref. 6 . However, macroscopic experiments that can be used to validate the PHCMs for dual phase α/β Ti6242S alloys are not available in the open literature, to authors' knowledge.…”

Section: Overviewmentioning

confidence: 99%

“…PHCMs for polycrystalline α-phase titanium alloys have been developed in refs. 1,6,7 . The physics-informed PHCMs differ from conventional phenomenological models in their unambiguous depiction of constitutive parameters and their dependencies.…”

Section: Introductionmentioning

confidence: 99%

“…Details of computational development and validation of the PHCMs for single phase near-α Ti alloys is given in refs. 1,6 . The present paper extends the PHCMs to two-phase polycrystalline α/β Titanium alloys like Ti-6Al-4V and Ti-6Al-2Sn-4Zr-2Mo that are widely used in aircraft engine components due to their superior mechanical, thermal and fatigue properties 8 .…”

Section: Introductionmentioning

confidence: 99%

“…The PHCMs in refs. 1,6,7 enable full-scale component analysis with explicit representation of microstructural features and characteristics. They enjoy high accuracy, while being many orders of magnitude more efficient than conventional multiscale analysis methods.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty-quantified parametrically homogenized constitutive models (UQ-PHCMs) for dual-phase α/β titanium alloys

2020

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This paper develops an uncertainty-quantified parametrically homogenized constitutive model (UQ-PHCM) for dual-phase α/β titanium alloys such as Ti6242S. Their microstructures are characterized by primary α-grains consisting of hcp crystals and transformed β-grains consisting of alternating laths of α (hcp) and β (bcc) phases. The PHCMs bridge length-scales through explicit microstructural representation in structure-scale constitutive models. The forms of equations are chosen to reflect fundamental deformation characteristics such as anisotropy, length-scale dependent flow stresses, tension-compression asymmetry, strain-rate dependency, and cyclic hardening under reversed loading conditions. Constitutive coefficients are functions of representative aggregated microstructural parameters or RAMPs that represent distributions of crystallographic orientation and morphology. The functional forms are determined by machine learning tools operating on a data-set generated by crystal plasticity FE analysis. For the dual phase alloys, an equivalent PHCM is developed from a weighted averaging rule to obtain the equivalent material response from individual PHCM responses of primary α and transformed β phases. The PHCMs are readily incorporated in FE codes like ABAQUS through user-defined material modeling windows such as UMAT. Significantly reduced number of solution variables in the PHCM simulations compared to micromechanical models, make them several orders of magnitude more efficient, but with comparable accuracy. Bayesian inference along with a Taylor-expansion based uncertainty propagation method is employed to quantify and propagate different uncertainties in PHCM such as model reduction error, data sparsity error and microstructural uncertainty. Numerical examples demonstrate the accuracy of PHCM and the relative importance of different sources of uncertainty.

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Section: Overviewmentioning

confidence: 99%

Section: Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Uncertainty-quantified parametrically homogenized constitutive models (UQ-PHCMs) for dual-phase α/β titanium alloys

2020

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Methods, progresses, and opportunities of materials informatics

Li,

Zheng

2023

InfoMat

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As an implementation tool of data intensive scientific research methods, machine learning (ML) can effectively shorten the research and development (R&D) cycle of new materials by half or even more. ML shows great potential in the combination with other scientific research technologies, especially in the processing and classification of large amounts of material data from theoretical calculation and experimental characterization. It is very important to systematically understand the research ideas of material informatics to accelerate the exploration of new materials. Here, we provide a comprehensive introduction to the most commonly used ML modeling methods in material informatics with classic cases. Then, we review the latest progresses of prediction models, which focus on new processing–structure–properties–performance (PSPP) relationships in some popular material systems, such as perovskites, catalysts, alloys, two‐dimensional materials, and polymers. In addition, we summarize the recent pioneering researches in innovation of material research technology, such as inverse design, ML interatomic potentials, and microtopography characterization assistance, as new research directions of material informatics. Finally, we comprehensively provide the most significant challenges and outlooks related to the future innovation and development in the field of material informatics. This review provides a critical and concise appraisal for the applications of material informatics, and a systematic and coherent guidance for material scientists to choose modeling methods based on required materials and technologies.

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Parametrically Upscaled Constitutive and Crack Nucleation Models for Investigating the Effects of Specimen Geometry and Microstructure on Fatigue Crack Nucleation in Ti Alloys Containing Micro-texture Regions

Tak,

Nair,

Venkatesh

et al. 2024

Metall Mater Trans A

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Parametrically homogenized constitutive models (PHCMs) from micromechanical crystal plasticity FE simulations: Part II: Thermo-elasto-plastic model with experimental validation for titanium alloys

Cited by 33 publications

References 21 publications

Uncertainty-quantified parametrically homogenized constitutive models (UQ-PHCMs) for dual-phase α/β titanium alloys

Uncertainty-quantified parametrically homogenized constitutive models (UQ-PHCMs) for dual-phase α/β titanium alloys

Methods, progresses, and opportunities of materials informatics

Parametrically Upscaled Constitutive and Crack Nucleation Models for Investigating the Effects of Specimen Geometry and Microstructure on Fatigue Crack Nucleation in Ti Alloys Containing Micro-texture Regions

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