Application of digital image processing for implementation of complex realistic particle shapes/morphologies in computer simulated heterogeneous microstructures

Singh, Harpreet; Mao, Y.; Sreeranganathan, A.; Gokhale, A.M.

doi:10.1088/0965-0393/14/3/002

Cited by 21 publications

(15 citation statements)

References 24 publications

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“…[42][43][44][45][46] A two-point correlation function can represent the probability that a particular object exists at a specific distance and along a specific direction from a chosen location. Two-point correlations of this type [46] were calculated for the relationships between the following pairs of microstructural features: (1) cavities and cavities (cavity/cavity), (2) Al 6 (Mn,Fe) particles and Al 6 (Mn,Fe) particles (Al 6 (Mn,Fe)/Al 6 (Mn,Fe)), (3) Al 6 (Mn,Fe) particles and cavities (Al 6 (Mn,Fe)/cavity), and (4) Mg-Si particles and cavities (Mg-Si/cavity).…”

Section: Methodsmentioning

confidence: 99%

Effect of Microstructure on Cavitation during Hot Deformation of a Fine-Grained Aluminum-Magnesium Alloy as Revealed through Three-Dimensional Characterization

Chang

Taleff

Krajewski

2009

Metall Mater Trans A

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The effect of microstructure on cavitation developed during hot deformation of a fine-grained AA5083 aluminum-magnesium alloy is investigated. Two-point correlation functions and threedimensional (3-D) microstructure characterization reveal that cavitation depends strongly on the mechanism that controls plastic deformation. Grain-boundary-sliding (GBS) creep produces large, interconnected cavities rapidly during plastic straining. Solute-drag (SD) creep produces isolated cavities with less total volume fraction at a given strain. The 3-D microstructure data reveal adjacency between various microstructural features. Cavities are observed to be preferentially adjacent to large Al 6 (Mn,Fe) particles and to Mg-Si particles of all observed sizes. These data suggest that cavities preferentially nucleate at Mg-Si particles and at large Al 6 (Mn,Fe) particles. This result may be applied to reduce cavitation in commercial hot-forming operations utilizing aluminum-magnesium alloys.

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Section: Methodsmentioning

confidence: 99%

Effect of Microstructure on Cavitation during Hot Deformation of a Fine-Grained Aluminum-Magnesium Alloy as Revealed through Three-Dimensional Characterization

Chang

Taleff

Krajewski

2009

Metall Mater Trans A

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“…Further details of the method are described in a prior work. 30 The particles were inserted into a simulation domain one at a time with a strict overlap control. The size distribution for each component replicated the vendorsupplied information and a uniform-random distribution of constituents was generated.…”

Section: Shock-compression Of Ti+2b Powder Mixtures: Experiments and mentioning

confidence: 99%

Meso-Scale Experimental & Numerical Studies for Predicting Macro-scale Performance of Advanced Reactive Materials (ARMs)

Thadhani¹,

Gokhale²,

Quenneville³

et al. 2015

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Distribution Statement A. Approved for public release; distribution is unlimited.Our collaborative, multi-disciplinary and multi-investigator research project, combines numerical simulations with time-resolved impact experiments, to determine the meso-scale mechanisms of impact-initiated reactions in Ti-Al-B based reactive materials in the form of compacts of powders of different sizes and morphologies. The major goal is to delineate how processes of localized deformation and flow, or fracture and fragmentation, create the dispersion and mixing of reactants and provide the thermal and mass transport resulting in highly exothermic Ti and B intermetallic reaction and/or oxidation reaction (Al or B). The time sequence of events associated with reaction initiation as well as subsequent interactions with the external environment are also being determined. More specifically, the influence of material-inherent elastic/plastic properties and reactant configuration (e.g., porosity, morphology, spacing, distribution, etc., created from a library of microstructures) on meso-scale mechanistic processes and the resulting macro-scale performance is being established.reactive materials shock compression high-strain-rate deformation meso-scale computations MESO-SCALE EXPERIMENTAL & NUMERICAL STUDIES FOR PREDICTING MACRO-SCALE PERFORMANCE OF ADVANCED REACTIVE MATERIALS (ARMS)Grant/Award #: HDTRA1-10-1-0038Jennifer Breidenich, Arun Gokhale, Manny Gonzales, Ashok Gurumurthy, and Naresh Thadhani ABSTRACTOur collaborative, multi-disciplinary and multi-investigator research project, combines numerical simulations with time-resolved impact experiments, to determine the meso-scale mechanisms of impact-initiated reactions in Ti-Al-B based reactive materials in the form of compacts of powders of different sizes and morphologies. The major goal is to delineate how processes of localized deformation and flow, or fracture and fragmentation, create the dispersion and mixing of reactants and provide the thermal and mass transport resulting in highly exothermic Ti and B intermetallic reaction and/or oxidation reaction (Al or B). The time sequence of events associated with reaction initiation as well as subsequent interactions with the external environment are also being determined. More specifically, the influence of material-inherent elastic/plastic properties and reactant configuration (e.g., porosity, morphology, spacing, distribution, etc., created from a library of microstructures) on mesoscale mechanistic processes and th...

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“…In practice, the 2 -pcf is most useful for microstructure representation (Saheli et al, 2004; Sundararaghavan and Zabaras, 2005). Recently, a digital image analysis based technique has been developed for the realistic computer simulation or reproduction of microstructure from measurements of the two-point correlation functions on 2D sections (Singh et al, 2006). …”

Section: Related Workmentioning

confidence: 99%

“…These functions efficiently characterize the microstructure in a heterogeneous substrate (Gokhale, 2004; Gokhale et al, 2005; Singh et al, 2006). The N-pcfs estimate a feature tensor at each pixel location.…”

Section: Introductionmentioning

confidence: 99%

Tensor classification of N-point correlation function features for histology tissue segmentation

Mosaliganti

Janoos

İrfanoğlu

et al. 2009

Medical Image Analysis

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In this paper, we utilize the N-point correlation functions (N-pcfs) to construct an appropriate feature space for achieving tissue segmentation in histology-stained microscopic images. The N-pcfs estimate microstructural constituent packing densities and their spatial distribution in a tissue sample. We represent the multi-phase properties estimated by the N-pcfs in a tensor structure. Using a variant of higher-order singular value decomposition (HOSVD) algorithm, we realize a robust classifier that provides a multi-linear description of the tensor feature space. Validated results of the segmentation are presented in a case-study that focuses on understanding the genetic phenotyping differences in mouse placentae.

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Application of digital image processing for implementation of complex realistic particle shapes/morphologies in computer simulated heterogeneous microstructures

Cited by 21 publications

References 24 publications

Effect of Microstructure on Cavitation during Hot Deformation of a Fine-Grained Aluminum-Magnesium Alloy as Revealed through Three-Dimensional Characterization

Effect of Microstructure on Cavitation during Hot Deformation of a Fine-Grained Aluminum-Magnesium Alloy as Revealed through Three-Dimensional Characterization

Meso-Scale Experimental & Numerical Studies for Predicting Macro-scale Performance of Advanced Reactive Materials (ARMs)

Tensor classification of N-point correlation function features for histology tissue segmentation

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