Identification of the Shape of Curvilinear Beams and Fibers

François, Marc; Semin, Benoît; Auradou, Harold

doi:10.4028/www.scientific.net/amm.24-25.359

Cited by 11 publications

(23 citation statements)

References 5 publications

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“…Finite element based levelsets are used for an efficient implementation of the method. The local influence of the shape parameters due to the B-spline functions used as a basis for displacements also acts for fast and robust computation, on the contrary of former version of the VIC method [9,18] in which the series used made each parameter have a global influence. Another advantage of the B-spline basis is their high continuity order and their support in terms of element compared to those of usual finite element shape function which is larger.…”

Section: Discussionmentioning

confidence: 99%

“…The virtual image is based on a curve in the vicinity of which the gray level evolves smoothly with the distance to the curve, according to a bell-shaped function for the contour detection (or to a smooth step for the silhouette detection). In the former version of the VIC [9,18] the curve is described by a function series of the curvature (whose optimal weights are researched). However, due to a computation at any point of the (sub-pixel) grid associated to the curvilinear frame of the curve, this method requires a large amount of CPU time.…”

Section: Introductionmentioning

confidence: 99%

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Curve and boundaries measurement using B-splines and virtual images

Réthoré

François

2014

Optics and Lasers in Engineering

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This paper presents a digital image correlation method able to detect and measure a contour or silhouette in a digital image, with a sub-pixel precision. A virtual image that describes a simple contour or silhouette roughly similar to the physical object to detect is created. The matching with the physical image of the object is then performed based on digital image correlation. We look for the displacement field which transforms the physical image which is the closest to the virtual one. In order to keep a problem of finite dimension, this field is decomposed on a B-spline basis. The algorithm is close to the digital image correlation method; an efficient implementation is proposed that makes use of levelsets. The full method is tested over both synthesized and real images, one of a star shaped toy and one on an ill-defined image of a high temperature metallic specimen on which no other boundary measurement was possible. The influence of the arbitrary choice of the virtual image contour or silhouette arbitrary parameters is discussed with respect to the precision of the method. This one is shown to be sub-pixel in any case.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Curve and boundaries measurement using B-splines and virtual images

Réthoré

François

2014

Optics and Lasers in Engineering

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“…To account for the actual shape of the hole, a Virtual Image Correlation (VIC) method as first introduced in Ref. [21] and then further developed in Ref. [22], is used to capture the actual hole contour directly from the scanning electron microscope (SEM) image in Fig.…”

Section: Lithiation Of a Unit Cell Of The Patterned Si-filmmentioning

confidence: 99%

A multiphysics model that can capture crack patterns in Si thin films based on their microstructure

Réthoré

Zheng

et al. 2018

Journal of Power Sources

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Fracture in silicon anodes has fascinated the electrochemistry community for two decades, as it can result in a 80% capacity loss over the first few electrochemical cycles and is the limiting factor in commercializing such high capacity anodes. Although numerous experimental data exist illustrating severe fracture patterns and their dependence on the scale of the microstructure, no theoretical model has been able to reproduce and capture such behaviour. In this article, a multi-physics phase-field damage model is presented that can accurately capture the long standing problem of dry bed-lake crack patterns observed for Si thin film anodes. A promising aspect of the model is that, in addition to accounting for Li-ion diffusion, it can explicitly capture the microstructure, and therefore when applied to a Si film with a thickness below 100 nm no fracture was observed, which is consistent with experiments. As fracture in continuous thin films is random, micron-hole patterned Si films were also fabricated and cycled, resulting in ordered crack patterns. The proposed model was able to capture these elaborate, yet ordered, crack patterns, further validating its efficiency in predicting damage during lithiation of Si. This paves the way to using multiscale modeling for predicting the dimensions that limit and control fracture during lithiation, prolonging hence the electrode lifetime.

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“…Inspired by (author?) [26] and (author?) [27], the conservation of grey levels is written between a virtual scan f * and the reference one f .…”

Section: Contour and Crack Detectionmentioning

confidence: 99%