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Effect of oxygen content on the sub-grain nanoindentation response in titanium affected by high temperature oxidation
No full textInternational audiencePre-oxidation tests were performed on a commercially pure titanium (CP-40) at 700 °C for 100 h under air in order to introduce a gradient of oxygen content within the metal, also called the oxygen-rich layer (ORL). The chemical profile of oxygen was measured using microprobe analyses (EPMA) on cross-sectional observations. Large but highly resolved nanoindentation maps using continuous stiffness measurement techniques were performed on the specimen cross-section to document the local mechanical response within the oxygen-rich layer (ORL) as a function of the oxygen content and the grain orientation using statistical and multi-modal analyses. The oxygen was found to greatly increase the hardness and elastic modulus in titanium and was correlated to orientation of the c axis of the α-Ti
Detection and characterization of defects on mechanical structures by using 3D vision
No full textInternational audienceThis paper deals with the detection and characterization of surface damages (a dent, a crack, etc.) on mechanical surfaces using 2D/3D vision (3D scanner and/or 2D RGB camera). The main innovative aspect lies in the exploitation of the Computer Aided Design model, when it is available, with two possible scenarios: ”manual control” via a hand-held 3D scanner carried by an operator, or ”automated control” via a 3D scanner carried by a cobot. This research work has been carried out within the joint research laboratory ”Inspection 4.0” between IMT Mines Albi/ICA and the DIOTA company, specialized in the development of numerical tools for Industry 4.0
Visual inspection of complex mechanical assemblies based on Siamese networks for 3D point clouds
No full textInternational audienceThis paper proposes a solution for the problem of visual mechanical assembly inspection by processing point cloud data acquired via a 3D scanner. The approach is based on deep Siamese neural networks for 3D point clouds. To overcome the requirement for a large amount of labeled training data, only synthetically generated data is used for training and validation. Real-acquired point clouds are used only in testing phase
A Cooperative Rh/Co‐catalyzed Hydroaminomethylation Reaction for the Synthesis of Terpene Amine
No full textInternational audienceAn original bimetallic catalytic system based on Rh(I) and Co(0) in glycerol is described for the synthesis of biomass-derived amines through the tandem hydroaminomethylation reaction of terpenes, such as (R)-limonene, b-pinene and camphene. Under optimized conditions, this multicatalytic system is highly chemoselective (avoiding hydrogenations of substrates and aldehyde-based intermediates, and aldol condensations), exhibiting good-to-excellent regioselectivity towards linear amines. From a mechanistic viewpoint, cobalt mainly boosts the reductive amination, while rhodium shows a foremost role in the hydroformylation step. Regarding the nature of the organometallic species, catalytically inactive metal nanoparticles have been identified at the end of the reaction, proving the homogeneous nature of the bimetallic catalytic system
Decision Support in uncertain contexts: Physics of Decision and Virtual Reality
No full textInternational audienceVirtual Reality (VR) is often used for its ability to mimic reality. However, VR can also be used for its ability to escape reality. In that case, on the one hand VR provides a visualization environment where the user’s senses are still in a familiar context (one can see if something is in front, behind, up, down, far or close), yet on the other hand, VR allows to escape the usual limits of reality by providing a way to turn abstract concepts into concrete and interactive objects. In this paper, the dynamic management of a complex industrial system (a supply chain) is enabled in a VR prototypical environment, through the management of a physical trajectory that can be deflected by the impact of any potentialities such as risks or opportunities, seen as physical objects in the performance space
MedWGAN Based Synthetic Dataset Generation for Uveitis Pathology
No full textInternational audienceClinical decision support based on artificial intelligence (AI) methods have increasingly been employed in medical applications to support medical diagnosis. Developing efficient AI methods, however, depends necessarily on the availability of sufficiently large amount of data to provide reliable results. But, in medicine, it is not always possible to find sufficient amount of real data on all pathologies, particularly, for rare diseases. This paper proposes a methodological framework for generating synthetic data using data augmentation techniques combined with epidemiological profiles. It focuses on Uveitis, a rare disease in ophthalmology, which is difficult to diagnose because of the disparity in prevalence of its etiologies. The generated synthetic data have been qualitatively validated by specialist ophthalmologists and quantitatively tested using machine learning methods. Results show that, of a randomly selected sample of the generated data, more than 55% were assessed as good or excellent, which is very promising for generating synthetic, validated as near-real, medical data for rare diseases. They also show that the proposed framework is consistent in generating synthetic data, for Uveitis pathology, of different dataset sizes, achieving more than than 80% diagnosis prediction accuracy for 2000 patient records or larger
Balancing the satisfaction of stakeholders in home health care coordination: a novel OptaPlanner CSP model
No full textInternational audienceHome Health Care Routing and Scheduling Problem (HHCRSP) has been widely investigated in operations research. In this paper, a model based on the Constraint Satisfaction Problem (CSP) is proposed, which is able to deal with daily HHCRSPs. Human factors are considered in our formulation of the problem and we seek a balance between the different stakeholders’ satisfaction criteria. The considered temporal constraints are soft and controlled by the stakeholders’ personalised tolerance and satisfaction rates. We will explain how this new Satisfaction-Oriented HHCRSP (SOH2CRSP) model is built and solved by using an open-source solver: the OptaPlanner. In order to examine the impact of human factors, a study will estimate the added value provided when satisfaction is considered in the problem formulation. The comparison is based on a use case derived from the dataset of an existing HHC organisation. The numerical results will show the benefits of our approach
A microscopy study of nickel-based superalloys performance in type I hot corrosion conditions
No full textInternational audienceAlloy material selection for sustainable, efficient, and cost-effective use in components is a key requirement for both power generation and aerospace sectors. Superalloys are manufactured using a combination of different elements, selected carefully to balance mechanical performance and environmental resistance to be used in a variety of different service conditions. Therefore, a fundamental understanding of each element is critical to alloy design. In this paper, the interaction of alloy chemistry, particularly chromium as a corrosion-resistant element along with titanium and molybdenum, and their effect on alloys performance for the relevant gas turbine industries were discussed. Based on the findings, the single-crystal alloy is found to be a better corrosion resistant alloy exhibited higher corrosion resistance in comparison to polycrystal alloys and proved that microstructure has a significant impact on alloy performance. This study also established that molybdenum level in chromia former alloys can significantly enhance the corrosion damage
Iron Nanoparticles to Catalyze Graphitization of Cellulose for Energy Storage Applications
No full textInternational audienceThe production of highly graphitic carbon from bioresources is an environmentally friendly approach to synthesize graphene for energy storage applications. Iron catalytic graphitization of cellulose, the most abundant biopolymer on earth, is an alternative approach as until now, cellulose has been classified as poorly graphitizable material. In this study, the impact of processing temperature and iron impregnation on the extent of graphitization of the cellulose-derived graphitic carbon nanostructure is uncovered by combining Raman spectroscopy, X-ray diffraction, transmission electron microscopy, and X-ray pair distributionfunction analysis. Raman spectroscopy is used in an innovative way to describe the evolution of the average graphitic phase sizewhere the ash content misguides the X-ray diffraction analysis. A correlation was established between (i) the in-plane crystallite sizeLa and the ID′′/IG first-order ratio, (ii) the out-of-plane Lc crystallite size and the IG/Itot′ second-order ratio, and (iii) the second-orderRaman IG′/Itot′ ratio and the average number of carbon layers per carbon crystallite. For iron-impregnated cellulose, phase quantification and analysis of the spatial distribution reveal highly crystalline rhombohedral graphite surrounded by a nanocrystalline carbon matrix. We explicitly show that traditionally non-graphitizable carbons can be used to form a graphite-like structure with multilayers of graphene sheets by careful addition of widely available nontoxic metal as catalysts. The study also shows that the impact of the catalyst is much more effective than the temperature in the nanostructure transformation. The proposed approach and the results obtained provide interesting insights that should stimulate further works aimed at extending the knowledge in the field
A Framework for virtual training in a crisis context and a focus on the animation component: the gamemaster workshop
No full textInternational audienceCritical infrastructures, historical places, and sensitive buildings are vulnerable to crises, from natural to man-made disasters. Public institutions and practitioners have to train, before the occurrence of a major event, to be prepared to respond to the crisis. These sites are difficult to vacate just to perform exercises. To propose training adapted to the needs the trainer have to create an exercise dedicated to the aimed skills. Stakeholders responding to high-risk situations are asking for new ways to train and compensate for the weaknesses of existing training approaches. The research work presented in this paper concerns the design of immersive environments that can be used to create, implement and simulate crisis scenarios to improve collaborative training