Journal ArticleDOI
Random texture models for material structures
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TLDR
This work considers the construction and properties of some basic random structure models (point processes, random sets and random function models) for the description and for the simulation of heterogeneous materials.Abstract:
We consider the construction and properties of some basic random structure models (point processes, random sets and random function models) for the description and for the simulation of heterogeneous materials. They can be specialized to three dimensional Euclidean space. Their implementation requires the use of image analysis tools.read more
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A Lattice Approach to Image Segmentation
TL;DR: After a formal definition of segmentation as the largest partition of the space according to a criterion σ and a function f, the notion of a morphological connection is reminded and used as an input to a central theorem of the paper, that identifies segmentation with the connections that are based on connective criteria.
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Computational microstructure characterization and reconstruction for stochastic multiscale material design
TL;DR: This work proposes a data-driven framework to address both the above components for two-phase materials (composites with two materials mixed together, each having distinct material properties) and presents the algorithmic backbone to such a framework.
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Practical Application of the Stochastic Finite Element Method
TL;DR: This review paper introduces the most commonly used techniques: direct Monte Carlo simulation, the perturbation method and the spectral stochastic finite element method and looks at the currently available software for the SFEM.
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Computational nonlinear stochastic homogenization using a nonconcurrent multiscale approach for hyperelastic heterogeneous microstructures analysis
TL;DR: This paper is devoted to the computational nonlinear stochastic homogenization of a hyperelastic heterogeneous microstructure using a nonconcurrent multiscale approach and uses a database describing the strain energy density function (potential) in both the macroscopic Cauchy green strain space and the geometrical random parameters domain.
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Some trends in microscope image processing
TL;DR: The present review tries to identify some trends among the multitude of ways followed by image processing developments in the field of microscopy.
References
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Book
Image Analysis and Mathematical Morphology
TL;DR: This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.
Book
Stochastic Geometry and Its Applications
TL;DR: Random Closed Sets I--The Boolean Model. Random Closed Sets II--The General Case.
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