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Les défis de collecte de données dans la conception d’un jumeau numérique de territoire : le cas des paysages de mégalithes du Morbihan, future labellisation UNESCO
No full textInternational audienceThis paper explores the challenges of data collection in the design of a territorial digital twin, based on the case of the megalithic landscapes of Morbihan, which are currently candidates for UNESCO World Heritage status. In anticipation of increased tourist numbers, the JUNITER project aims to develop a digital twin capable of simulating and managing visitor flows, while addressing the site’s heritage and environmental constraints. The approach relies on the integration of heterogeneous, multi-source data and the use of simulation tools (AnyLogic) combined with multi-criteria optimization algorithms. This methodology offers an adaptable framework for other territories facing similar challenges, contributing to a more sustainable and efficient management of heritage and tourism resources.Ce papier explore les défis liés à la collecte de données dans la conception d’un jumeau numérique de territoire, en s’appuyant sur le cas des paysages mégalithiques du Morbihan, candidats à la labellisation UNESCO. Face à l’augmentation attendue de la fréquentation touristique, le projet JUNITER vise à développer un jumeau numérique capable de modéliser et anticiper les flux de visiteurs tout en respectant les contraintes patrimoniales et environnementales. L’approche repose sur une intégration multi-sources de données hétérogènes et l’utilisation d’outils de simulation (AnyLogic) couplés à des algorithmes d’optimisation multi-critères. Cette méthodologie propose un cadre adaptable à d’autres territoires confrontés à des enjeux similaires, dans une perspective de gestion durable des sites patrimoniaux
Mechanical behaviour of 3D printed and textile-reinforced eco-friendly composites
No full textInternational audience3D printing has revolutionised construction with rapid, cost-effective production of complex designs. However, the growing literature focuses on cementitious mixtures with high energy requirements, neglecting eco-friendly alternatives. Additionally, integrating reinforcement is challenging due to complex geometries and anisotropic nature of printed material. This study explores textile materials as reinforcement, offering shaping ease, strength, and design freedom. Two sustainable mixes were formulated: earth-based and lime-based. Composites of 3D-printed earth reinforced with jute fabric and 3D-printed lime reinforced with jute and glass fibre grids were produced. Flexural, compression, and splitting tensile tests were carried out to assess the impact of textile reinforcement. Results showed improved textile-matrix bonding enhanced load distribution and structural integrity. A second mixing, reducing torque value by about six times from its initial unprintable state, is crucial for lime-based mortar printability. Textile reinforcement increased strength by 142.8% and ductility by 1130.3%, demonstrating its effectiveness for sustainable 3D printing construction
Volatolomics for Anticipated Diagnosis of Cancers with Chemoresistive Vapour Sensors: A Review
No full textInternational audienceThe anticipated diagnosis of cancers and other fatal diseases from the simple analysis of the volatiles emitted by the body (volatolome) is getting closer and closer from becoming reality. The promises of vapour sensor arrays are to provide a rapid, reliable, non-invasive and ready-to-use method for clinical applications by making an olfactive fingerprint characteristic of people’s health state, to increase their chance of early recovery. However, the different steps of this complex and ambitious process are still paved with difficulties needing innovative answers. The purpose of this review is to provide a statement of the blocs composing the diagnostic chain to identify the improvements still needed. Nanocomposite chemo-resistive transducers have unique prospects to enhance both the selectivity and sensitivity to volatile biomarkers. The variety of their formulations offers multiple possibilities to chemical functionalization and conductive architectures that should provide solutions to discriminations and stability issues. A focus will be made on the protocols for the collection of organic volatile compounds (VOC) from the body, the choice of vapour sensors assembled into an array (e-nose), in particular, chemo-resistive vapour sensors, their principle, fabrication and characteristics, and the way to extract pertinent features and analyse them with suitable algorithms that are able to find and produce a health diagnosis
Goal-Oriented Projection Based Reduced Order Model
No full textIn this paper we investigate the use of a correction to enhance the measurements accuracy provided by a reduced model. This correction is based on a coefficient expansion into the reduced basis, obtained by a non-orthogonal projection, that ensure the exact modelling of the measurements. Then a simple regression step allows to increase the measurements accuracy of the reduced model by one or multiple order of magnitude, without adding any extra-cost. This method propose an alternative to the adjoint approach to use reduced model in an inverse problem context where the number of measurements is relatively large
Modélisation du comportement en vue de la prédiction du succès des démarches d'accompagnement du changement et de l'automatisation des diagnostics
No full textInternational audienc
Conservative polynomial approximations and applications to Fokker-Planck equations
No full text24 pages, 14 figures, 7 tablesInternational audienceWe address the problem of constructing approximations based on orthogonal polynomials that preserve an arbitrary set of moments of a given function without loosing the spectral convergence property. To this aim, we compute the constrained polynomial of best approximation for a generic basis of orthogonal polynomials. The construction is entirely general and allows us to derive structure preserving numerical methods for partial differential equations that require the conservation of some moments of the solution, typically representing relevant physical quantities of the problem. These properties are essential to capture with high accuracy the long-time behavior of the solution. We illustrate with the aid of several numerical applications to Fokker-Planck equations the generality and the performances of the present approach
Feature selection strategy optimization for lithium-ion battery state of health estimation under impedance uncertainties
No full textInternational audienceBattery health evaluation and management are vital for the long-term reliability and optimal performance of lithium-ion batteries in electric vehicles. Electrochemical impedance spectroscopy (EIS) offers valuable insights into battery degradation analysis and modeling. However, previous studies have not adequately addressed the impedance uncertainties, particularly during battery operating conditions, which can substantially impact the robustness and accuracy of state of health (SOH) estimation. Motivated by this, this paper proposes a comprehensive feature optimization scheme that integrates impedance validity assessment with correlation analysis. By utilizing metrics such as impedance residuals and correlation coefficients, the proposed method effectively filters out invalid and insignificant impedance data, thereby enhancing the reliability of the input features. Subsequently, the extreme gradient boosting (XGBoost) modeling framework is constructed for estimating the battery degradation trajectories. The XGBoost model incorporates a diverse range of hyperparameters, optimized by a genetic algorithm to improve its adaptability and generalization performance. Experimental validation confirms the effectiveness of the proposed feature optimization scheme, demonstrating the superior estimation performance of the proposed method in comparison with four baseline techniques
A useful subdifferential in the Calculus of Variations
No full textInternational audienceConsider the basic problem in the Calculus of Variations of minimizing an energy functional depending on absolutely continuous functions Under suitable assumptions on the Lagrangian, a well-known result establishes that the minimizers satisfy the Du Bois-Reymond equation. Recent work (cf. Bettiol and Mariconda, 2020 [1], 2023; Mariconda, 2023 [2], 2021, 2024) highlights not only that a Du Bois-Reymond condition for minimizers can be broadened to cover the case of nonsmooth extended valued Lagrangians, but also that a particular subdifferential (associated with the generalized Du Bois-Reymond condition) plays an important role in the approximation of the energy via its values along Lispchitz functions, no matter minimizers exist. A crucial point is establishing boundedness properties of this subdifferential, based on weak local boundedness properties of the Lagrangian. This is the main objective of this paper. Our approach is based on a refined analysis of the metric that can be employed to evaluate the distance from the complementary of the effective domain of the reference Lagrangian. As an application of our findings we show how it is possible to deduce the non-occurrence of the Lavrentiev phenomenon, providing a new general result