Portail des publications scientifiques IMT Mines Alès
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Event-Based Data in Prognostics and Health Management: A Systematic Review of Models, Challenges, and Applications
No full textInternational audienceIn the modern industrial context, Prognostics and Health Management (PHM) systems based on data-driven approaches have been widely and effectively developed to reduce maintenance costs. However, continuous data requires large memory capacity and high costs. Therefore, in recent years, the use of event-based data for PHM models has become prominent and increasingly attracts attention due to its cost-efficiency and effectiveness. This surge in data availability has opened new avenues for developing data-driven methods that leverage event patterns to enhance diagnostic, prognostic, and predictive maintenance capabilities. Building meaningful and interpretable patterns from raw event data is crucial for understanding system behavior, detecting faults early, forecasting future failures, and accurately estimating the Remaining Useful Life (RUL) of critical components. This review paper systematically surveys the state-of-the-art methodologies and frameworks for extracting, modeling, and utilizing event-based patterns in the context of diagnostic and prognostic applications. Furthermore, we analyze challenges related to event data heterogeneity, scalability, and interpretability, as well as the need for robust pattern extraction methods that can adapt to dynamic operating environments. The review further explores how these event-based patterns contribute to building reliable diagnostic models, enabling early fault detection, and supporting maintenance decision-making through precise prognostics.Finally, this paper identifies key research gaps and outlines future directions, emphasizing the need for explainable, adaptive, and scalable pattern mining approaches that effectively translate raw event data into actionable maintenance intelligence. To address these challenges, we propose a conceptual framework that integrates advanced pattern discovery techniques with domain knowledge and feedback loops, enabling continuous learning and decision support. This comprehensive survey aims to serve as a foundational reference for researchers and practitioners committed to leveraging event data for enhanced system reliability and the development of optimized, intelligent maintenance strategies
Assessing cardiovascular adaptations of professional football players
No full textInternational audienceProfessional football players face high physical demands throughout the season, which have been increasing steadily for many years.1 To ensure players’ health (i.e., optimize physical performance and reduce injury risk), practitioners have developed monitoring strategies based on external and/or internal indicators.2 Yet, there are several operational (i.e., schedule, staff turnover) and theoretical (i.e., non-linear relationship, multifactorial aspect of the activity) limitations hindering their daily use in elite football.3 To overcome these issues, recent sports science literature has shown interest in using machine learning models.4 Heart rate (HR), a surrogate measure of the cardiorespiratory system,5 has raised some interest to monitor training status.6 We propose to use an indicator based on the difference between predicted and measured HR during specific football drills to track player fitness (ΔHR)7,8 as well asindicators related to HR kinetics (i.e., HR acceleration and recovery)9 and their difference with their predicted value to have a complete overview of the player’s cardiovascular status. The postulate underlying the monitoring of these indicators is intuitive: any deviation from the expected normal behavior (i.e., prediction) informs the practitioner about the player’s training status (e.g., for ΔHR, a higher or lower physiological cost than expected for a given external load (i.e., improved or reduced fitness)
One Step Closer to my Heart: Cardiac Cycle is Coupled with Footsteps in Typical but not in Depersonalisation Individuals
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Boosting the reinforcing potential of flax co-products: Biomass fractionation and composite microstructure as keys
No full textInternational audienceThe growing demand for sustainable thermoplastic composites has increased interest in using agricultural co-products as reinforcements due to their low cost, wide availability, and low density. This requires an optimization of fractionation processes, i.e. milling and sieving procedures, to develop mechanically efficient composite microstructures. This study investigates the influence of flax shives (a co-product of the flax industry) fractionation on the microstructure and mechanical performance of injection-moulded polypropylene composites. A multi-scale experimental approach, including 2D particle size and shape analysis, X-ray tomography, tensile testing, and micromechanical modelling, was employed. Our results show that optimizing flax shives size and shape distribution via fractionation improves their aspect ratio and orientation in the composite, thus enhancing the composite stiffness and strength by up to 17.9 % (95 % CI: 9.6–26.2 %) and 25.2 % (95 % CI: 24.0–26.5 %), respectively, when comparing composites with the lowest and highest properties. To understand the origin of the reinforcement mechanisms, the stiffness of flax shives was back-calculated based on different micromechanical models using both analytical (Halpin-Tsai, Mori-Tanaka) and numerical finite element modelling. The findings highlight that model selection and orientation assumptions strongly influence the estimated stiffness. Based on realistic microstructural inputs, the flax shives stiffness was estimated to be in the range of 21.84–36.45 GPa using Mori-Tanaka model and 11.83–23.0 GPa using Finite Element modelling depending on the tested flax shives fractions. This integrated approach demonstrates the importance of tailoring plant-based filler morphology to optimize their reinforcing capacity while offering a transferable methodology for valorising agricultural co-products in composite materials
On Aluminum Flame Propagation in a Smooth Vertical Tube: Experimental Study and Analogies with Premixed Gaseous Flames
No full textInternational audienceAluminum dust flame propagation inside a smooth vertical tube from its closed end is studied through a joint analysis of experimental measurements and numerical simulations. In addition to the common information about flame shape and position over time, flow velocity and turbulence intensity ahead of the propagating flame front are accessed using time-resolved particle image velocimetry. Both experimental measurements and numerical simulations based on a turbulent flame-speed modeling approach are used to identify the most important features of propagation mechanisms. While the turbulent flame-speed model does not intend to be predictive owing to rather rough simplifying assumptions, the simulation results show that the G- equation modeling approach correctly predicts the flame propagation. Both experiments and numerical simulations support a mechanism where turbulence plays only a supplementary role in the flame propagation mechanism. Finally, on the basis of a geometrical model, it is highlighted that aluminum dust flame propagation in a half-open smooth tube exhibits similar behavior in comparison with gaseous flames
Exploring computational fluid dynamics to assess the role of vegetated planters in urban canyon microclimate regulation
No full textInternational audienceAccurately modelling urban microclimates is essential for developing effective mitigation strategies against urban overheating. This study assesses the potential of ANSYS Fluent to simulate an experimental urban canyon with vegetated planters, using three different simulation methods. The analysis focuses on accuracy, operational suitability, and an improved understanding of the physical mechanisms operating at the scale of an urban canyon. Numerical results related to radiative, thermal, and aerodynamic fluxes, are evaluated based on (i) experimental data obtained from a dense network of sensors and (ii) the physical consistency obtained in the spatial distribution of the variables analysed. Despite some discrepancies in spatial and temporal variations, the model demonstrated strong agreement with experimental data, with absolute errors in air temperature and relative humidity below 3 % on average (maximum 11 %). Radiation, as the most sensitive factor for daytime thermal comfort variation in the study area, highlights the importance of improving radiative exchange in the proposed models. While certain software limitations require user-defined functions, such as representation of average radiant temperature, thermal comfort indices and multiple vegetation heat source terms, the study underscores the tool’s capacity to generate detailed and high-resolution microclimate data. This rich numerical database improves our understanding of urban heat dynamics, paving the way for more efficient urban climate solutions
Manufacturing fiber reinforced recycled PET Tapes: A Capillarity-Based Approach
No full textInternational audiencePolyethylene terephthalate (PET) is one of the world's most widely used polymers, mainly in food packaging and textiles. This material lightness, transparency and mechanical properties make it indispensable [1]. However, PET waste is very common, with a very long natural degradation time. Non-recycled PET therefore contributes significantly to the pollution of both marine and terrestrial ecosystems [2]. However, current recycling methods, which are mainly mechanical, have limitations, including the degradation of material properties after several cycles and high energy consumption [3]. An original and promising alternative is to transform recycled PET into matrixes for performant composites, such as fiber-reinforced thermoplastic tapes.Polymer recycling has become a major issue in the current context of ecological transition and the development of the circular economy [4], [5]. Composite materials with thermoplastic matrices, in particular thermoplastic tapes (reinforced with fibers), offer a promising solution for reducing environmental pollution while meeting the requirements of the most demanding industrial sectors in terms of flexibility and performance. However, the manufacturing of this type of material from recycled polymers such as PET faces technological challenges, particularly in terms of homogeneous impregnation of fibrous reinforcements and control of residual porosity.The aim of this work is to develop an optimized method to manufacture thermoplastic tapes from recycled PET, based on an in-depth understanding of the physico-chemical mechanisms involved. The main objective is to minimize structural defects, such as porosity, while guaranteeing high mechanical properties compatible with demanding industrial applications. This research is part of the exploration of a methodical and innovative approach to producing high-quality recycled and recyclable thermoplastic tapes. First of all, an optimum solvent and non-solvent pair was identified [6] to effectively dissolve recycled PET and enable it to be recovered [7], [8]. This pairing was rigorously selected to ensure good interaction between the solvents and the fibrous reinforcements in order to minimize structural defects in the final composite.Optimizing the performance of tapes required in-depth study of the phenomena of dynamic wetting and spontaneous impregnation of recycled polymer into fibers. Dynamic wetting behavior is highly dependent on fiber and polymer surface properties, polymer solution viscosity and displacement speed [9], [10]. These analyses enabled us to optimize the operating parameters to maximize adhesion and uniform distribution of the polymer in the fibers. Spontaneous impregnation tests were also carried out, providing the necessary information for solution composition.Particular attention was paid to the rheological characterization of the polymer solution, in order to determine the optimum viscosity range. A solution that is too fluid may not adhere sufficiently to the fibers, while a viscosity that is too high limits penetration into the porous structure of the reinforcements [11]. In addition, the physico-chemical interactions between solvents and fibres, and particularly the roving used in the manufacture of tapes, also play an essential role in the process.These analyses allowed to define operating parameters for optimizing the manufacture of thermoplastic tapes from recycled PET. By controlling solution properties and impregnation conditions, porosities can be reduced and impregnation maximized
Modelling the impact of irrigated vegetation on urban microclimate: A review
No full textInternational audienceThe repeated occurrence, intensity and frequency of urban heatwaves pose significant challenges to urban areas. This paper critically reviews the current state of modelling the impact of irrigated vegetation on urban microclimate. It synthesizes findings from recent publications on the subject, focusing on the methodologies, challenges, and advances in numerical models that describe thermal comfort and heat mitigation strategies. Emphasizing the need for a transdisciplinary approach, the review highlights the key thermal and water-related factors influencing urban microclimates, including aerodynamic, radiative and phase change (e.g. evapotranspiration) processes, in interplay with urban geometry, materials and vegetation, especially when irrigated on purpose. The paper categorizes existing models based on their applications, physical modelling capabilities, and spatial-temporal discretization, offering guidelines for model selection tailored to specific urban planning objectives. Additionally, it provides a detailed description of the most pertinent models, especially regarding vegetation modelling for urban areas. The review underscores the necessity of validating existing models and the need for a standardized validation method for urban climate models. Future research directions are proposed to enhance the integration of vegetation effects in urban climate models, optimize irrigation strategies, and improve the predictive accuracy of these models to support sustainable urban design and policy-making
Evaluation of the potential impact of wildfires on buried natural gas pipelines
No full textInternational audienceThis study assesses the potential impact of wildfires on buried natural gas pipelines, a key concern as wildfiresbecome more frequent and intense, particularly in regions where gas infrastructure intersects with wildfire-proneareas. The aim is to evaluate the thermal effects of the incident heat flux from wildfires on the soil above pipelinesand the soil temperature distribution. A simplified approach is used for rapid analysis based on hypothesesabout flame front geometry and soil thermal properties. A parametric study shows that even under worst-caseconditions (high incident heat flux and prolonged fire exposure), soil temperatures at the depth of the pipelineremain below critical thresholds. As a result, the current burial depth standards of 0.8 m provide significantprotection against hypothetical severe thermal damage from wildfires, reinforcing their continued effectivenessin safeguarding buried gas facilities in wildland fire-prone areas. This conclusion appears to be theoreticallyvalidated in scenarios where the maintenance strip is properly maintained. Further studies will be conducted toexamine the opposite situation, i.e., where no cleared maintenance strip is present
Motivation toward physical activity and nutrition in older cancer patients: the MONAGE protocol using ecological momentary assessment and accelerometers
No full textInternational audienceBackgroundOlder adults with cancer struggle to maintain recommended levels of physical activity and nutrition during treatments. Collecting data in a real-life context provides a better understanding of the motivational and behavioral dynamics of this population, which is underrepresented in clinical trials. Ecological momentary assessment (EMA) is a frequently used approach to collect repeated measures in real time in a naturalistic environment. This approach can provide insights into the temporal dynamics of psychological processes, such as motivation toward health behaviors. The aim of this study is to identify clusters based on predictive motivational variables related to physical activity and nutritional behaviors among older patients with cancer, via repeated measures.MethodsIn this project, older patients with a cancer (≥ 70 years old) complete physical capacity assessments, malnutrition identification, and a comprehensive geriatric assessment with G-code. After that, participants engage in a 2-week data collection protocol combining EMA and sensor-based monitoring of behavior. The participants wear an ActiGraph GT3X-BT accelerometer (ActiGraph, LLC) on their nondominant waist to measure physical activity. EMA questionnaires are delivered 3 times per day - morning (between 8am and 10am), midday (between 12pm and 2pm) and evening (between 7pm and 8pm) - via smartphones or computers with the UniQ digital application. Motivational constructs based on the Theory of Planned Behavior are collected in the morning and at midday. Nutritional behavior data are collected at midday and in the evening. Fatigue is collected in the morning, at midday and in the evening. The data analysis strategy shall include Multilevel Vector Autoregressive Models with k-means clustering.DiscussionThis project seeks to identify clusters in older patients with cancer based on key motivational predictors related to physical activity and nutritional behaviors, via approaches for collecting repeated measurements in real time within a naturalistic environment. This research into the mechanisms of action between motivation and behaviors could optimize care pathways by designing appropriate intervention content, under conditions where the content will be most effective, to promote sustained behavior change among older adults with cancer.Trial registrationClinicalTrials.gov (NCT06445140). Registered on 06 June 2024