Fatigue damage of automotive LEDs: Experimental approach and thermomechanical model

International audienc

Strain Patterns With Ultrasound for Assessment of Abdominal Aortic Aneurysm Vessel Wall Biomechanics

International audienc

Coupling Variable Selection and Anomaly Detection: Record-Based Approach

International audienceThe proliferation of interconnected devices is rapidly expanding globally, and, as a result, telecommunication operators are responsible for managing intricate and expansive networks. Consequently, there is a need for advanced and efficient systems to aid network engineers in maintaining these networks. Devices, which can also be referred to as network elements, continuously transmit essential performance data known as key performance indicators. By utilizing data derived from these metrics and implementing intelligent anomaly detection models, the devices can assist in determining the optimal production maintenance schedule for the network. As anomaly detection models deal with extreme events, this study proposes a method of reducing dimensions by focusing on the behavior of the tails of underlying variables, rather than the entire distribution. In addition to that, an anomaly scoring system, also based on records theory, is proposed, which has several advantages over current state-of-the-art models. The effectiveness of this approach is demonstrated by implementing it on a real-world dataset

A Multi-Agent-based infrastructure for coupling physical and digital robotic environments

International audienceThis paper presents a multi-agent-based infrastructure achieving a seamless coupling between physical and digital environments. The goal is to simplify the design of Cyber-Physical systems (CPS) including robots. The proposed infrastructure introduces agents that act on behalf of physical and digital robots, facilitating real-time interaction and coordination between both environments. Based on the multi-agent framework Hypermedea, the infrastructure provides a solid framework for hiding the technical complexity of the designed system. Our proposal is illustrated through a motivating scenario from the Industry 4.0

Craftsman gaze data study to enhance craft material selection and facilitate Knowledge Transfer

International audienceMaterial selection methods and tools are mainly quantitative-based and cater essentially to engineering material selection requirements. However, shifts in material sourcing and manufacturing as well as data processing tend to lean towards tailored fabrication models in which the material leads the design. This highlights emerging opportunities and requirements in material selection, including the need to consider the situation of the person making the assessment, which has come to the forefront of material selection. Designers and researchers have already provided valuable research to enhance material selection on a sensorial basis. However, little has been recommended for material selection based on the different states of a material and a person’s experience with the material in those various states. Crafts offer a wealth of opportunity to study the different states of a material when interacting with a human being and offer fertile ground to conduct research into user-situation based material selection. To further the study, the eye tracker has been considered a favored tool, as it produces data sets of a user’s visual attention, revealing unfolding cognition and unaware processing while a person performs a material selection task. We present illustrations of four material selection situations to show the benefit of providing gaze data. We consider that this data, given the different areas and levels of expertise in material knowledge, can be an important contribution to the existing means and models already being used by designers in material selection. We present prospects and suggest that material selection should take place early on in the material transformation process. We also question the very notion of gaze and its many possible meanings, concluding our paper by highlighting the need for as much complementary experiential data as possible to hone into more informed and refined data sets associated with material selection experience

An advanced image processing and multivariate statistical methodology to interpret Micro-EDXRF 2D maps: Uncovering heterogeneity and spatial distribution patterns of rare earth elements in phosphogypsum

International audiencePhosphogypsum (PG), a by-product of the fertilizer industry, is a potential source of rare earth elements (REEs) such as Lanthanum (La), Cerium (Ce), Neodymium (Nd), and Yttrium (Y). These elements were efficiently detected using micro-Energy Dispersive X-Ray Fluorescence (μ-EDXRF). Although a homogeneous REE distribution was expected in μ-EDXRF 2D maps, significant heterogeneity and variations in elemental associations (EA) were observed at a micrometric scale. To enhance and better interpret μ-EDXRF mapping results, a specialized image processing methodology was developed, incorporating Principal Component Analysis (PCA), Hierarchical Clustering (HC), and Multiple Linear Regression (MLA) which were applied to process and analyse 2D RGB pixel data. Identification of spatial overlaps, and multivariate correlations among the detected elements could be achieved. Notably, distinct EA patterns were found, with Ti, Ba, Y, and K playing a key role in REEs spatial distribution. Strong positive spatial correlations were identified between La and Ti, while Ce, Nd, and Y exhibited independent spatial distributions relative to La in certain sample areas. MLA further revealed strong EA between La, Ce, Nd, Y, and K, particularly in locations where Ti or Ba were also present. Additional elemental interactions were detected with Al, Cl, Ni, and Fe, with P and Cl showing significant correlations. Multicollinearity effects suggest strong interdependencies among elements. These findings highlight distinct REE spatial distributions within PG, demonstrating that mineralogical and compositional variations within the PG matrix influence REE spatial distribution patterns. Understanding these associations can improve strategies for REEs recovery from PG waste

Investigation of [BMIM]FeCl₄ ionic liquid as an additive for carbon capture using gas hydrates with seawater

International audienceCarbon capture through gas hydrate formation represents a highly promising avenue for mitigating greenhouse gas emissions. The unique structure of gas hydrates allows for the efficient trapping of gases like CO2, potentially offering a robust solution for carbon sequestration. However, the practical implementation of this technology faces several challenges, primarily related to the kinetics of hydrate formation and the stability of hydrates under varying conditions. The use of promoters has shown potential in overcoming some of these kinetic barriers. A few years ago, iron-based ionic liquids were studied as kinetic promoters for gas hydrates. Since hydrate formation kinetics pose a well-known challenge for developing hydrate-based technologies, this study aims to evaluate the effectiveness of [BMIM]FeCl4 ionic liquid for carbon capture from seawater. The research is divided into three stages: analyzing the influence of NaCl concentration on the liquid–liquid equilibrium of brine and ionic liquids; examining the thermodynamic equilibrium of CO2 hydrates in the presence of seawater and ionic liquids; and investigating the kinetics of hydrate formation. The first stage produced a two-phase ternary diagram relevant to expected industrial conditions, and the kinetic constants for gas-to-liquid and liquid-to-hydrate mass transfer were estimated. The results demonstrated a thermodynamic inhibition effect for CO2 hydrates. However, from a kinetic perspective, no significant improvement was observed. Consequently, [BMIM]FeCl4 did not prove to be an effective overall promoter

A laser-based annealing methodology to speed-up the study of thermo-activated restoration mechanisms in metals

Cet article sera prochainement publié dans Review of Scientific Instruments (print ISSN : 0034-6748)This article will be released in Review of Scientific Instruments (print ISSN : 0034-6748)International audienceThe properties of polycrystalline materials are significantly influenced by annealing treatments. This article introduces a laser-annealing method that facilitates the investigation of high-temperature transformations, with a specific focus on tungsten restoration. The aim of this research is to establish a controlled temperature gradient in the examined sample to expedite the study of restoration at high temperatures by reducing the number of samples. To achieve this, simulations are employed to design the desired temperature profile, and a laser-based setup is adapted to generate and regulate this profile. Furthermore, uncertainties and errors associated with temperature measurements in the experimental setup are quantified. The proposed laser-annealing method enables precise temperature control during the annealing process. By heating one side of a tungsten rod using the laser system, a steady-state temperature gradient is induced. The annealing process consists of two steps: the initial heating phase to reach the desired temperature profile, followed by the maintenance of constant Temperatures at specific positions along the rod for a defined duration. The study investigates the impact of absorbed power by the sample on the temperature profile and assesses the softening of tungsten after annealing using hardness measurements. Overall, the proposed laser-annealing method offers a promising avenue for advancing material science research. Its ability to precisely control temperature gradients and observe material behaviors at high temperatures opens up new opportunities to optimize the properties of polycrystalline materials beyond tungsten, thus providing broader applications in material engineering and manufacturing

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National audienc

Gestion de la montée en puissance des services en tenant compte de la durabilité et des risques

This PhD research explores the development of service ramp-up management, a multidisciplinary concept that encompasses the processes and strategies employed to effectively introduce and rapidly scale services in today’s dynamic business environment. This research addresses the complexities associated with service ramp-up and aims to answer two simple but fundamental research questions (RQs) in this context; When and How to ramp-up a service. To achieve these objectives, the research employed a Design Science Research (DSR) methodology, beginning with a systematic literature review (SLR) on decision-making in ramp-up management (DMiRM). A conceptual framework, obtained from the SLR funding, is proposed to provide a structured approach for DMiRM and guide decision-makers in ramp-up strategies. The research then focuses on agile ramp-up concept as an emerging paradigm crucial for the successful execution of service ramp-up projects. A conceptual Framework has been proposed for agile ramp-up phase to answer the first RQ: When to ramp-up. This framework, structured around five key stages and agile stage-gate model, underscores the importance of iterative development and continuous improvement in the context of service ramp-up. As the primary contribution of this research, this PhD research proposes a comprehensive framework namely “Agile Ramp-up Framework for Escalation Stage (ARFES)” to address the second RQ: How to ramp-up. ARFES integrates structured yet flexible approaches, enabling organizations to rapidly and swiftly adapt to evolving market conditions and customer demands. Moreover, ARFES incorporates a range of concepts, techniques, and methodologies including agility and agile principles, simulation , sustainability and performance indicators, risk management, and Business Process Standardization (BPS), to facilitate systematic and iterative process performance improvements. Following the designated DSR methodology, the framework was evaluated and refined through two iterations: a content validity assessment and a detailed practical use case in a Additive Manufacturing Service.Cette thèse explore la gestion de la montée en puissance des services, un concept multidisciplinaire visant à introduire et développer rapidement des services dans un environnement dynamique. Elle répond à deux questions fondamentales : Quand et comment intensifier un service. Une méthodologie de recherche en sciences de la conception (DSR) a été employée, incluant une revue systématique de la littérature (SLR) sur la prise de décision dans ce domaine. Un cadre conceptuel structuré, basé sur le modèle agile principales et le stage-gate, a été développé pour répondre à la question quand intensifier, en mettant en avant l'importance du développement itératif et de l'amélioration continue. La contribution principale est le cadre « Agile Ramp-up Framework for Escalation Stage » (ARFES), qui répond à la question comment intensifier. ARFES intègre principes agiles, simulation, durabilité, gestion des risques et standardisation des processus pour améliorer les performances de manière systématique et itérative.Validé par une évaluation de contenu et une étude de cas pratique dans la fabrication additive, ce cadre offre aux organisations une approche flexible pour s'adapter aux marchés en constante évolution