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Mixture theory

About: Mixture theory is a research topic. Over the lifetime, 616 publications have been published within this topic receiving 19350 citations.


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Journal ArticleDOI
TL;DR: The use of composite finite element models where meshes with different granularities are allowed to share the same problem domain, is introduced and improved solutions may be obtained without increasing the computational cost of the problem or requiring postprocessing of the results.

13 citations

Journal Article
TL;DR: In this paper, a specific model derived from the mixture theory has been developed to describe the filling of injection moulds by dense pastes, containing about 60 vol% of solid particles, each constituent is characterized by its own velocity, behavior and boundary conditions, and interacts with the other consituents by exchanging momentum.
Abstract: A specific model derived from the mixture theory has been developed to describe the filling of injection moulds by dense pastes, containing about 60 vol.% of solid particles. Each constituent is characterized by its own velocity, behavior and boundary conditions, and interacts with the other consituents by exchanging momentum. Darcy's law was adopted for the momentum supply. Finally, some applications are proposed. First of all, the validity of the model is examined by comparing a numerical simulation with experimental results, for the case of capillary rheometric measurements. The model is able to predict the anomalous slippage characteristics which were shown by the tests. Furthermore, it provides a physical explanation of the phenomenon. A qualitative numerical prediction of mould obstruction is proposed by considering segregation in the blend.

13 citations

Journal ArticleDOI
TL;DR: By analyzing both volumetric and surface dissolutions, the two fundamental modes of growth are investigated within the unified framework of mixture theory.
Abstract: Growth mechanics problems require the solution of mass balance equations that include supply terms and account for mass exchanges among constituents of a mixture. Though growth may often be accompanied by a variety of concomitant phenomena that increase modeling complexity, such as solid matrix deformation, evolving traction-free configurations, cell division, and active cell contraction, it is important to distinguish these accompanying phenomena from the fundamental growth process that consists of deposition or removal of mass from the solid matrix. Therefore, the objective of this study is to present a canonical problem of growth, namely, dissolution of a rigid solid matrix in a solvent. This problem illustrates a case of negative growth (loss of mass) of the solid in a mixture framework that includes three species, a solid, a solvent, and a solute, where the solute is the product of the solid dissolution. By analyzing both volumetric and surface dissolutions, the two fundamental modes of growth are investigated within the unified framework of mixture theory.

13 citations

Proceedings ArticleDOI
TL;DR: In this paper, a parametric finite mixture model for high-resolution synthetic aperture radar (SAR) images is proposed. But the proposed model is based on a predefined dictionary of parametric probability density functions, which consists of eight state-of-the-art SAR-specific models: Nakagami, log-normal, generalized Gaussian Rayleigh, heavy-tailed Rayleigh (HRT), Weibull, K-root, Fisher and generalized Gamma.
Abstract: In the context of remotely sensed data analysis, a crucial problem is represented by the need to develop accurate models for the statistics of pixel intensities. In this work, we develop a parametric finite mixture model for the statistics of pixel intensities in high resolution synthetic aperture radar (SAR) images. This method is an extension of previously existing method for lower resolution images. The method integrates the stochastic expectation maximization (SEM) scheme and the method of log-cumulants (MoLC) with an automatic technique to select, for each mixture component, an optimal parametric model taken from a predefined dictionary of parametric probability density functions (pdf). The proposed dictionary consists of eight state-of-the-art SAR-specific pdfs: Nakagami, log-normal, generalized Gaussian Rayleigh, Heavy-tailed Rayleigh, Weibull, K-root, Fisher and generalized Gamma. The designed scheme is endowed with the novel initialization procedure and the algorithm to automatically estimate the optimal number of mixture components. The experimental results with a set of several high resolution COSMO-SkyMed images demonstrate the high accuracy of the designed algorithm, both from the viewpoint of a visual comparison of the histograms, and from the viewpoint of quantitive accuracy measures such as correlation coefficient (above 99,5%). The method proves to be effective on all the considered images, remaining accurate for multimodal and highly heterogeneous scenes.

13 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202311
20228
20219
20208
201913
201811