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Inspection of mechanical assemblies based on 3D Deep Learning segmentation
No full textInternational audienceOur research work is being carried out within the framework of the joint research laboratory ”Inspection 4.0” between IMT Mines Albi/ICA and the company Diota specialized in the development of numerical tools for Industry 4.0. In this work, we are focused on conformity control of complex aeronautical mechanical assemblies, typically an aircraft engine at the end or in the middle of the assembly process. A 3D scanner carried by a robot arm provides acquisitions of 3D point clouds which are further processed by deep segmentation networks. Computer-Aided Design (CAD) model of the mechanical assembly to be inspected is available, which is an important asset of our approach. Our deep learning models are trained on synthetic and simulated data, generated from the CAD models. This research is a continuation of the work presented at the QCAV’2021 conference
Estimating atmospheric radiative forcings using sensitivity monte carlo methods
No full textInternational audienceOne aspect of climate change analysis is the quantification of radiative forcings, i.e., the change of top-of-atmosphere (TOA) net radiative flux induced by an isolated, instantaneous change in surface or atmospheric constitution. In this paper, we discuss recent advances in path-integral formulations for producing reference estimates of radiative forcings, in the form of partial derivatives we call "sensitivities". We present the theoretical framework and highlight the role of computer science acceleration techniques in making the computational cost insensitive to the system’s multidimensional and multiphysics complexity. The approach is demonstrated by estimating the flux sensitivity to the concentration of two greenhouse gases
Phosphorus recovery from municipal sludge-derived hydrochar: Insights into leaching mechanisms and hydroxyapatite synthesis
No full textInternational audienceHydrothermal liquefaction has the potential to exploit resources from municipal sewage sludge. It converts most organics into a liquid biofuel (biocrude), concentrates P in the solid residue (hydrochar), and consequently enables its efficient recovery. This study thoroughly evaluated the effects of extraction conditions on P and metal release from hydrochar by nitric acid. Among assessed factors, acid normality (0.02–1 N), liquid-to-solid ratio (5–100 mL/g), and contact time (0–24 h) had positive effects while decreasing eluate pH (0.5–4) improved leaching efficiencies of P and metals. Notably, eluate pH played a dominant role in P leaching and pH < 1.5 was crucial for complete extraction. P and metal leaching from hydrochar have strong interactions and their leaching mechanism was identified as product layer diffusion using the shrinking core model. This suggests that the leaching efficiency is susceptible to agitation and particle size but not temperature. Using 10 mL/g of 0.6 N HNO3 for 2 h was considered the best extraction condition for efficient P leaching (nearly 100%) and minimization of cost and contaminants (heavy metals). Following extraction, adding Ca(OH)2 at a Ca:P molar ratio of 1.7–2 precipitated most P (99–100%) at pH 5–6, while a higher pH (13) synthesized hydroxyapatite. The recovered precipitates had high plant availability (61–100%) of P and satisfactory concentrations of heavy metals as fertilizers in Canada and the US. Overall, this study established reproducible procedures for P recovery from hydrochar and advanced one step closer to wastewater biorefinery
High-Throughput High-Resolution Digital Image Correlation Measurements by Multi-Beam SEM Imaging
No full textInternational audienceBackground Recent improvements in spatial resolution and measurement sensitivity for high-resolution digital image cor-relation (HR-DIC) now provide an avenue for the quantitative measurement of deformation events and capturing the physicalnature of deformation mechanisms. However, HR-DIC measurements require significant time due to scanning electron imageacquisition; such a limitation prevents the widespread use of HR-DIC for material characterization.Objective Apply a novel SEM acquisition technology to enhance HR-DIC measurements for high throughput applications.Methods Multi-beam SEM technology is employed to image an entire gauge length at once at high resolution and at nearly ahundredfold acceleration of typical HR-DIC image acquisition, even when automated stage movement and image acquisitionare employed. These images were fed into a discontinuity-tolerant HR-DIC software to determine slip localization inducedby non-metallic inclusions and grain structure.Results Slip localization was able to be analyzed to an unprecedented level, with over 210,000 slip bands able to be investi-gated, with the most intense slip localizing near and parallel to twin boundaries and in the vicinity of non-metallic inclusionclusters. Additionally, secondary slip activation and grain boundary shearing by intense dislocation pileups are observed toreduce slip amplitude near and parallel to twin boundaries.Conclusions By performing HR-DIC in conjunction with a multi-beam SEM, high-throughput measurements of large field-of-view, high-resolution images were able to be performed in a timely manner. These measurements provided an immensenumber of slip events for statistical analysis to be performed on to relate to microstructural features
Thermo-optical coupling applied to high luminance LED used in automotive front lighting
No full textInternational audienceAutomotive front lighting evolved towards high definition beams. To create such function, up to several light source per square millimeters are involved. The current trend tends to replace multiple LED designs with only one high luminance LED. The 10W-optical power emitted by this optoelectronic source induces high energy density that requires to be thermally managed. Moreover, when this LED is integrated within its optical system, the radiation concentration can lead to the system self-heating, leading to early damage or failure. The strategy adopted in this paper to avoid the component failure consists in developing an accurate and robust multi-physics simulation to predict heat transfer in a LED lighting system. In this paper, the validation of a high luminance LED thermo-optical coupling model is achieved by comparing numerical simulations with experimental results. The full optical characterization of LED has been performed to build its opto-thermal model. Then, an experimental set-up has been designed and consists in positioning a black plate in front of the LED, to capture its self-heating induced by light energy absorption using infrared thermography. The agreement between thermo-optical simulation and IR thermography is fair, which reinforces the use of the model with an error lower than 10%
Green hydrogen from biomass towards integrated biorefinery
No full textInternational audienceThe forecast through 2050 underlines a 50% increase in world energy consumption. In parallel, the energy sector is the main source of greenhouse gas emissions. This raises interest in a complete transformation of the current energy system. The Net Zero by 2050 roadmap aims to reduce global CO2 emissions through the deployment of the available clean and efficient energy technologies. This meets A.SPIRE's (the association of European Process Industries) Strategic Research and Innovation Agenda for hydrogen integration, namely 4.2 Hydrogen integration
Organogel of Acai Oil in Cosmetics: Microstructure, Stability, Rheology and Mechanical Properties
No full textInternational audienceOrganogel (OG) is a semi-solid material composed of gelling molecules organized in the presence of an appropriate organic solvent, through physical or chemical interactions, in a continuous net. This investigation aimed at preparing and characterizing an organogel from acai oil with hyaluronic acid (HA) structured by 12-hydroxystearic acid (12-HSA), aiming at topical anti-aging application. Organogels containing or not containing HA were analyzed by Fourier-transform Infrared Spectroscopy, polarized light optical microscopy, thermal analysis, texture analysis, rheology, HA quantification and oxidative stability. The organogel containing hyaluronic acid (OG + HA) has a spherulitic texture morphology with a net-like structure and absorption bands that evidenced the presence of HA in the three-dimensional net of organogel. The thermal analysis confirmed the gelation and the insertion of HA, as well as a good thermal stability, which is also confirmed by the study of oxidative stability carried out under different temperature conditions for 90 days. The texture and rheology studies indicated a viscoelastic behavior. HA quantification shows the efficiency of the HA cross-linking process in the three-dimensional net of organogel with 11.22 µg/mL for cross-linked HA. Thus, it is concluded that OG + HA shows potentially promising physicochemical characteristics for the development of a cosmetic system
Improved model for continuous, real-time assessment and monitoring of the resilience of systems based on multiple data sources and stakeholders
No full textInternational audienceFaced with an increasing level of disruption from natural disasters, terrorist attacks or internal failures, organisations need to ensure their business continuity. Ensuring this continuity depends, among other things, on the continuous assessment, monitoring, and management of their resilience based on the variations of the functionalities. Resilience-assessment methodologies are nowadays used to (1) prepare stakeholders for future crisis management situations and (2) help stakeholders assess past levels of resilience in the aftermath of the crisis. However, continuous, real-time monitoring and assessment of resilience is generally either outside the scope of such methods or limited to raw data representation, lacking effective filtering, interpretation, or integration in the evolving context of the organisation’s activities. This paper enhances previous works on resilience assessment. The result is a complementary methodology for continuous, real-time resilience assessment and monitoring based on multiple data-sources and stakeholders. The novelty is (1) in the context of use of the methodology, (2) in the way the functionality analysis model is obtained and (3) in the way the resilience is continuously assessed
Towards a demand estimation adapted to hyperconnected transport systems in regional areas
No full textInternational audienceThe transportation sector faces challenges in meeting sustainable development goals, especially in regional areas where transportation services are limited. The concept of the physical internet offers solutions to improve the efficiency and sustainability of hyperconnected transport systems in these areas. To achieve this, it is necessary to understand and predict transportation demand while considering the geographic and temporal characteristics of regional areas. Existing research has identified several factors that influence transportation demand, but the proposed models have limitations in terms of accuracy and incorporating additional data sources. To address these limitations, this research proposes a data-driven approach to predict demand for different market segments in hyperconnected regional transport systems. This approach should contribute to the production of demand profiles capable of adapting service offerings based on operational variability, allowing hyperconnected transport systems in regional areas to increase their agility and sustainability. This research will be developed in the context of the ECOTRAIN project, which aims to propose autonomous rail shuttles for the transportation of freight and passengers in regional areas
Outil d’aide à la décision à base de jumeau numérique pour l’analyse prospective et rétrospective d’un programme de bloc opératoire soumis à des incertitudes
No full textWith healthcare demand rising worldwide, hospital services are increasingly needed. Hospitals' performance is tightly linked to their surgical suite performance. Indeed, the surgical suite is an important revenue and expense center with over 40% of the hospital's budget dedicated to it (Macario et al. 1997) and 60% of the patient coming into the hospital for surgical intervention (Fugener et al. 2017). This makes it necessary for surgical suites to be efficient. However, running a profitable surgical suite is quite hard and requires a methodological approach due to the complexity of its functioning: the diversity of patient pathways, the multiplicity of professions, the tight link with upstream and downstream wards, the synchronization of several resources and logistic flows (drug and medical devices), etc. On the other hand, durations variability and disruptions inherent in medical care like emergency cases are the main factors and events that degrade the scheduled execution and involve the staff making decisions frequently to preserve the surgical suite activity in an optimal way. Therefore, OR planning and scheduling activities are of increasing interest to the scientific community. In this PhD thesis, we focus on offline operational and online operational levels (Hans and Vanberkel 2012). This leads us to the following research questions: (1) How can we assess the robustness and the resilience of the schedule before its execution (prospective way)? (2) How can we replay the schedule to have feedback and assess the decisions made during its execution (retrospective way)? The contribution of this manuscript is threefold: (1) we propose a digital twin-based decision support system for the prospective and retrospective simulation and analysis of the operating room schedule execution, (2) we describe a standardized methodology to conceive, build and implement this tool in any surgical suite, (3) This methodology is applied to an operating room inspired by the Private Hospital of La Baie (Vivalto Santé group, France), in order to have a proof of concept allowing to simulate an operating program prospectively and retrospectively.Avec l'augmentation de la demande de soins dans le monde, les services hospitaliers sont de plus en plus sollicités. Leur performance est étroitement liée à la performance de leur bloc opératoire. En effet, le bloc opératoire est un important centre de revenus et de dépenses puisqu'il représente 40% du budget de l'hôpital (Macario et al. 1997), et que 60% des patients viennent à l'hôpital pour une intervention chirurgicale (Fugener et al. 2017). Il est donc nécessaire que les blocs opératoires soient efficients. Cependant, cela est rendu difficile par la complexité de leur organisation due à la diversité des parcours patients, la multiplicité des métiers, les liens étroits avec les services amont et aval, la synchronisation de plusieurs ressources et flux logistiques (personnels, médicaments et dispositifs médicaux), etc. D'autre part, la variabilité des durées et les perturbations inhérentes à la pratique médicale, comme les cas d'urgence, sont les principaux facteurs et événements qui dégradent le programme opératoire et impliquent que le personnel prenne de fréquentes décisions pour maintenir l'activité du bloc opératoire de manière optimale. Par conséquent, les activités de planification et d'ordonnancement du bloc opératoire intéressent de plus en plus la communauté scientifique. Dans cette thèse de doctorat, nous nous concentrons sur les niveaux opérationnels hors ligne et en ligne (Hans et Vanberkel 2012). Ceci nous amène aux questions de recherche suivantes : (1) Comment évaluer la robustesse et la résilience du programme opératoire avant son exécution (dimension prospective) ? (2) Comment rejouer le programme opératoire pour avoir un retour d'expérience et évaluer les décisions prises lors de son exécution (dimension rétrospective) ? La contribution de ce manuscrit est triple : (1) Nous proposons un système d'aide à la décision basé sur un jumeau numérique pour la simulation et l'analyse prospectives et rétrospectives de l'exécution du programme opératoire. (2) Nous décrivons une méthodologie standardisée pour concevoir, construire et mettre en œuvre cet outil dans n'importe quel bloc opératoire. (3) Cette méthodologie est appliquée à un bloc opératoire inspiré de l'Hôpital Privé de La Baie (groupe Vivalto Santé), afin de disposer d'une preuve de concept permettant de simuler un programme opératoire de façon prospective et rétrospective