A combined three-dimensional digitisation and subsurface defect detection data using active infrared thermography

International audienceIn recent years, NonDestructive Testing (NDT) systems have been upgraded with three-dimensional information. Indeed, combine the three-dimensional and thermal information allows a more meaningful analysis. In the literature, the data for NDT and three-dimensional (3D) reconstruction analysis are commonly acquired from independent systems. However, the use of two such systems leads to error analysis during the data registration. In an attempt to overcome such problems, we propose a single system based on active thermography approach using heat point-source stimulation to get the 3D digitization as well as subsurface defect detection. The experiments are conducted on steel and aluminum objects, and a combined 3D / thermal-information is presented

Automatic measurement of wood fiber orientation and knot detection using an optical system based on heating conduction

In this paper, a new approach to computing the deviation of wood grain is proposed. To do this, the thermal conduction properties of timber are used (higher conduction in the fiber direction). Exciting the surface of the wood with a laser and capturing the thermal conduction using a thermal camera, an ellipse can be observed. Using a method similar to the tracheid effect, it is possible to extract information from this ellipse, such as the slope of grain and the presence of knots. With this method it is therefore possible to extend the mechanical model (assessing the mechanical properties of timber) to take certain singularities into account. Using this approach, the slope of grain can be estimated for any wood species, either hardwood or softwood, which was not possible with the existing tracheid effect.- Conseil Régional de Bourgogne (PARI II) - Projet ANR CLAMEB (ANR-11-RMNP-0015

Wood fiber orientation assessment based on punctual laser beam excitation: A preliminary study

International audienceThe EU imposes standards for the use of wood in structural applications. Local singularities such as knots affect the wood mechanical properties. They can be revealed by looking at the wood fiber orientation. For this reason, many methods were proposed to estimate the orientation of wood fiber using optical means, X-rays, or scattering measurement techniques. In this paper, an approach to assess the wood fiber orientation based on thermal ellipsometry is developed. The wood part is punctually heated with a Nd-YAG Laser and the thermal response is acquired by an infrared camera. The thermal response is elliptical due to the propagation of the heat through and along the wood fibers. An experiment is presented to show the capacity of such techniques to assess fiber orientation on wood specimen. In addition, an appropriate algorithm is given to extract the orientation of the ellipse

Bivariate models and dependence measures for overall survival and progression-free survival in cancer clinical trials

L'analyse de survie constitue bien souvent l'objectif principal des études cliniques en cancérologie. Les données de survie découlent d'un événement subi par les sujets de l'étude, événement qui correspond par exemple au décès pour la survie globale et à la progression tumorale pour la survie sans progression. Les méthodes non-paramétriques de Kaplan-Meier et semi-paramétriques de Cox représentent les modèles standards les plus utilisés pour modéliser ces données de survie, mais ne s'appliquent que dans le cas d'un seul événement temporel. La survie globale est considérée comme le critère clinique optimal pour juger de l'efficacité d'un traitement. La survie sans progression est un critère intermédiaire, qui représente un critère potentiel de substitution pour la survie globale. Depuis plusieurs années, un intérêt croissant s'est porté sur la validation statistique de critères intermédiaires. Cette validation passe par la mesure de la corrélation entre le critère clinique principal et le critère intermédiaire. Ainsi, une modélisation bivariée apparait intéressante afin de décrire la structure de dépendance entre les survies sans progression et globale. L'objectif de cette thèse concerne la modélisation de la structure d'association entre les survies sans progression et globale ainsi que la quantification de cette association via des mesures de dépendance. Pour cela, nous étudions en premier lieu les extensions du modèle de Cox qui peuvent traiter la dépendance statistique entre les données. Nous proposons ensuite une nouvelle modélisation paramétrique de la survie globale basée sur une distribution conditionnelle et sur les survies sans progression et post-progression. De plus, nous examinons différents modèles paramétriques de survie bivariée en termes de mesures de corrélation. Ces modèles sont fondés sur deux approches : les distributions marginales et l'indépendance conditionnelle. Enfin, nous appliquons et comparons les modèles étudiés en utilisant les données d'un essai clinique randomisé de phase III, impliquant des patients atteints de cancer du poumon non à petites cellules localement avancé.Analysis of survival often represents the main aim in cancer clinical studies. Survival data arise from an event experienced by the study subjects. This event corresponds for example to the death for overall survival and to tumor progression for progression-free survival. The Kaplan-Meier nonparametric estimator and the Cox semiparametric model are the most used standard methods for modeling survival data, although they are applied only in the case of unique temporal event. Overall survival is the optimal clinical endpoint for assessing the efficiency of treatment. Progression-free survival is an intermediate endpoint considered as a potential surrogate of overall survival. For the past few years, we observed an increasing focus on statistical validation of intermediate endpoints and this through measurement of the correlation between the principal clinical endpoint and the intermediate one. Thus, bivariate modeling could be of interest for describing the dependence structure between progression-free survival and overall survival. The aim of this thesis is the modeling of the structure of association between progression-free survival and overall survival as well as the quantification of this association using dependence measures. For this, we study at first extensions of Cox model able to address the topic concerning the statistical dependence between data. Next, we propose a new parametric modeling of overall survival based on two survival times : progression-free survival and post-progression survival, assumed to be linked by a conditional distribution. Moreover, we examine different parametric models for bivariate survival data concerning correlation measurement. These models are based on the marginal distributions and the conditional independence. Finally, we apply and compare these models using data from a phase III randomized clinical trial, involving patients with locally advanced non-small cell lung cancer

Investigating the Influence of Cold Rolling on Precipitation in Industrial AA2024 using Advanced Microscopy Techniques

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Effect of cold rolling on nucleation, growth and coarsening of S-phase precipitates in Al- Cu- Mg alloy (AA2024): From heterogeneous nucleation to homogeneous spatial distribution

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Investigating the Influence of Cold Rolling on Precipitation in Industrial AA2024 using Advanced Microscopy Techniques

Precipitation hardened aluminium alloys are widely used for various applications due to their properties, such as low density to strength ratio and high corrosion resistance. AA2024 is a commonly used aluminium alloy in the aerospace industry with a quite simple precipitation sequence including co-cluster and Guinier-Preston-Baragyatski (GPB) zone formation during natural ageing and precipitation of the equilibrium S-phase (Al2CuMg) during artificial ageing [1]. This study aims to investigate the influence of pre-deformation by cold rolling (CR) on subsequent precipitation during artificial ageing in industrial AA2024. Electron backscatter diffraction (EBSD) was used to analyse the deformation microstructure focusing on the arrangement of dislocation substructures. Atom probe tomography (APT) and differential scanning calorimetry (DSC) were used to characterize co-clusters in naturally aged AA2024-T3, showing that they are destroyed during cold rolling and not reconstituted during subsequent natural ageing. Precipitates evolution during artificial ageing of cold-rolled (CR) samples was investigated by transmission electron microscopy (TEM). Hence, although heteregenous nucleation on dislocation was observed, the precipitates appear with a spacially homogeneous distribution at peak hardness (Fig. 1). Dark-field imaging and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) tomography were performed to study the size distribution and three-dimensional arrangement of the S-phase precipitates. A refinement of precipitates in the preveously cold-rolled samples was observed, connected to changes in the aspect ratio of precipiates. The study demonstrates how advanced microscopy techniques contribute to understanding of microstructural changes and precipitation behaviour in aluminium alloys and therefore contribute to the development of novel production processes

Non Destructive Testing based on a Scanning-From-Heating approach: Application to non-through defect detection and fiber orientation assessment

International audienceNowadays, industries ensure the quality of their manufactured products through computer vision techniques and non-conventional imaging. 3D scanners and Non-Destructive Testing (NDT) systems are commonly used independently for such applications. Furthermore, these approaches combined together constitute a hybrid systems providing a 3D reconstruction and NDT analysis. These systems, however, suffer from drawback such as errors during the data fusion and higher cost for manufacturers. In an attempt to solve those problems, a single active thermography system based on Scanning-From-Heating (SFH) is proposed in this paper. Besides 3D digitization of the object, our contributions are twofold: (i) the non-through defect detection for homogeneous metallic object and (ii) fiber orientation assessment for long fiber composite material. The experiments on steel and aluminum plates show that our method achieves to detect non-through defects. Additionally, the estimation of the fiber orientation is evaluated on carbon-fiber composite material