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Augmented Lagrangian and Operator-Splitting Methods in Nonlinear Mechanics

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TLDR
In this article, an augmented Lagrangian method for the solution of variational problems is proposed. But this method is not suitable for continuous media and their mathematical modeling, such as viscoplasticity and elastoviscasticity.
Abstract
1. Some continuous media and their mathematical modeling 2. Variational formulations of the mechanical problems 3. Augmented Lagrangian methods for the solution of variational problems 4. Viscoplasticity and elastoviscoplasticity in small strains 5. Limit load analysis 6. Two-dimensional flow of incompressible viscoplastic fluids 7. Finite elasticity 8. Large displacement calculations of flexible rods References Index.

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A New System of Generalized Nonlinear Mixed Variational Inequalities in Hilbert Spaces

TL;DR: In this paper, a new generalized nonlinear mixed variational inequalities in Hilbert spaces were introduced and studied, and the convergence of the Mann iterative sequences with errors for this system was shown.
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An Inexact Alternating Directions Algorithm for Constrained Total Variation Regularized Compressive Sensing Problems

TL;DR: Numerical comparisons with the sate-of-the-art method TVLA3 illustrate that the proposed method for solving the TV regularized minimization problems with linear constraints is effective and promising.
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A damped Newton algorithm for computing viscoplastic fluid flows

TL;DR: For the first time, a Newton method was proposed for the unregularized viscoplastic fluid flow problem as discussed by the authors, which leads to a superlinear convergence for Herschel-Bulkley fluids.
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A combined segmentation and registration framework with a nonlinear elasticity smoother

TL;DR: In this article, a non-parametric combined segmentation and registration method is presented, where the shapes to be registered are implicitly modeled with level set functions and the problem is cast as an optimization one, combining a matching criterion based on the active contours without edges for segmentation (Chan and Vese, 2001) and a nonlinear-elasticity-based smoother on the displacement vector field.
Proceedings ArticleDOI

Latent fingerprint segmentation with adaptive total variation model

TL;DR: This work presents an adaptive total variation (TV) model, which can remove various types of structured noise existing in a single latent image and automatically locate the region of interest (ROI), which contains primarily the latent fingerprint.
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