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Removal of Ni2+ and Cd2+ from aqueous solutions by bionanosorbents: Isotherm, thermodynamic and mechanistic studies
No full textInternational audienceThe present work presents the efficiency and the limit in using bionanosorbents (cellulose, chitin and modified chitin nanocrystals) for the sorption of metal ions M2+ (M = Ni and Cd) in batch systems. Bionanosorbents were extracted from plants and shrimp shells, two available and low-cost materials. If cellulose and chitin nanocrystals did not efficiently remove metals in the experimental conditions of this work, the surface-modified chitin exhibited enhancement for the Ni2+ and Cd2+ adsorption capacity than original chitin nanocrystals. The Langmuir and Freundlich models fitted well to the experimental data from which the maximum adsorption capacity was 139.2 mg Ni g-1 and 38.4 mg Cd g-1. Regarding the Gibbs free energy and the Hall parameter, the sorption of Ni2+ and Cd2+ were spontaneous and favourable for pH around the neutrality. This corroborates the examination of IR spectra of oxidized chitin nanocrystals before and after the sorption process from which the metal removal mechanism was mainly attributed to the formation of complexes and ion exchanges of the bionanosorbent and metal ions. Element mappings of the bionanosorbents after sorption revealed a homogeneous distribution of Cd(II)
The Massive Open Online Course: 'Atmospheric Research Infrastructures: Sharing the Future of Our Atmosphere' as an Innovative Tool for Atmospheric Science & Climate Change Education
No full textInternational audienceAs part of the ATMO-ACCESS project, an innovative two-week Massive Open Online Course (MOOC) was hosted on the FUN (France Université Numérique) MOOC platform from January 20 to February 16, 2025. This course offered an engaging and interactive platform for learners interested in exploring critical challenges related to air pollution and climate change. The first week provided participants with in-depth knowledge about atmospheric constituents such as reactive trace gases and greenhouse gases, aerosols and clouds, their sources, impacts, and complex interactions. The MOOC emphasised the crucial importance of data sharing and collaborative networks within the research community while showcasing advanced atmospheric research methodologies. Additionally, the second week introduced three key Atmospheric Research Infrastructures (ARIs): ACTRIS, IAGOS, and ICOS, providing participants with insights into their high-quality operational workflows. To support active learning, participants could self-assess their knowledge through several quizzes and earn an open badge by successfully completing a final quiz. Feedback from participants and analysis of the MOOC's concluding survey revealed valuable insights into learner expectations, which will be presented during the session. These suggestions will guide the development of future iterations of the course, aiming at delivering a more effective, impactful and engaging learning experience
Addressing the advantages and limitations of using Aethalometer data to determine the optimal Absorption Ångström Exponents (AAEs) values for eBC source apportionment
No full textInternational audienceThe apportionment of equivalent black carbon (eBC) to combustion sources from liquid fuels (mainly fossil; eBCLF) and solid fuels (mainly non-fossil; eBCSF) is commonly performed using data from Aethalometer instruments (AE approach). This study evaluates the feasibility of using AE data to determine the absorption Ångström exponents (AAEs) for liquid fuels (AAELF) and solid fuels (AAESF), which are essential parameters for the AE approach. AAEs were calculated from Aethalometer data as the fit in a log-log space of the six absorption coefficients (470-950 nm) versus the corresponding wavelengths. Our results demonstrate that AAELF can be robustly determined as the 1st percentile (PC1) of AAE values from fits with R2>0.99. This R2-filtering was necessary to remove extremely low and noisy-driven AAE values commonly observed under clean atmospheric conditions (i.e., low absorption coefficients). Conversely, AAESF can be obtained from the 99th percentile (PC99) of unfiltered AAE values. To optimize the signal from solid fuel sources, winter data should be used to calculate PC99, while summer data should be used to calculate PC1 to maximize the signal from liquid fuel sources. The derived PC1 (AAELF) and PC99 (AAESF) values ranged from 0.79 to 1.08, and 1.45 to 1.84, respectively. The AAESF values were further compared with those constrained using the signal at mass-to-charge 60 (m/z 60), a marker for fresh biomass combustion, measured by aerosol chemical speciation monitor (ACSM) and aerosol mass spectrometry (AMS) instruments deployed at 16 sites. Overall, the AAESF values derived from the two methods showed strong agreement, with a coefficient of determination of 0.78. However, the uncertainties in both approaches can vary depending on site-specific sources, and in certain environments, such as at traffic-dominated sites, neither approach may be fully applicable
Basis restricted elastic shape analysis on the space of unregistered surfaces
No full textInternational audienceThis paper introduces a new framework for surface analysis derived from the general setting of elastic Riemannian metrics on shape spaces. Traditionally, those metrics are defined over the infinite dimensional manifold of immersed surfaces and satisfy specific invariance properties enabling the comparison of surfaces modulo shape preserving transformations such as reparametrizations. The specificity of our approach is to restrict the space of allowable transformations to predefined finite dimensional bases of deformation fields. These are estimated in a data-driven way so as to emulate specific types of surface transformations. This allows us to simplify the representation of the corresponding shape space to a finite dimensional latent space. However, in sharp contrast with methods involving e.g. mesh autoencoders, the latent space is equipped with a non-Euclidean Riemannian metric inherited from the family of elastic metrics. We demonstrate how this model can be effectively implemented to perform a variety of tasks on surface meshes which, importantly, does not assume these to be pre-registered or to even have a consistent mesh structure. We specifically validate our approach on human body shape and pose data as well as human face and hand scans for problems such as shape registration, interpolation, motion transfer or random pose generation.</div
Construction of copper, iron and manganese anthropogenic emission inventories for Europe
No full textInternational audienceTrace metal elements in atmospheric particulate matter (PM) have significant adverse health effects. However, emissions of some metals, such as copper (Cu), are notyet consistently reported to the EMEP program by European countries under the Convention on Long-range Transboundary Air Pollution (CLRTAP), as their reportingis only encouraged but not mandatory. Other unregulated metals such as iron (Fe) and manganese (Mn), are not considered at all. In this study, we improved thecurrent European Cu inventory by correcting and adjusting existing data and completing the inventory through gap-filling. In addition, we developed the firstEuropean anthropogenic inventories for Fe and Mn, considering key anthropogenic sources such as brake wear, road abrasion, engine lubricant combustion, fuelcombustion, waste incineration and rail wear. These emissions were geographically distributed based on the spatialization of PM10 emissions proposed in thereference inventories. For Cu, our new inventory shows that the heterogeneity of emissions between different countries is greatly reduced; for Fe and Mn, the inventoryconfirms the importance of abrasion processes in the rail and road traffic sectors, as well as that of combustion processes. To evaluate the emission inventory,the Fe/Cu and Mn/Cu ratios in the emissions were directly compared to ambient measurements. The results indicate an underestimation of Fe and Mn emissionscompared to Cu, potentially due to the omission of certain emission sources, such as industrial activities or resuspension by traffic, or to contributions from naturalsources such as desert mineral dust. We also compared our inventory with existing national and global inventories. This comparison suggests an underestimation ofemissions from industrial activities in our inventory but also a potential misrepresentation of road traffic (or railway) sources in other inventories. Further work,including simulations using a chemistry and transport model, and comparison with extended concentration data, is needed to better assess and improve the accuracyof these inventories
Modélisation du comportement mécanique d’un équipement en service sous endommagements progressifs : vers un jumeau numérique d’appareil à pression
No full textThis thesis focuses on the development of digital twins (DT) for the monitoring of progressive fatigue damage in pressure equipment (PE) under service conditions. The main objective is to design a hybrid approach that combines the accuracy of physics-based finite element (FE) models with the flexibility of data-driven methods, in order to provide a robust, responsive, and adaptable solution suitable for real industrial environments. To this end, two complementary models are developed and coupled: one based on an FE simulation framework, and another using Principal Component Analysis (PCA) and the Discrete Empirical Interpolation Method (DEIM), torming a dual-core digital twin.The first part of the work consists in developing a reliable FE model of the PE, according to normative codes, to simulate the mechanical behavior of critical welded zones. This model is experimentally validated using strain gauges and connected to fatigue life prediction tools based on a multiaxial S/N approach, with the maximum principal stress as the equivalent criterion.Real-time updating of the model is achieved via pressure data collected in service, enabling continuous tracking of fatigue damage.In the second part, the local data measured by strain gauges are exploited to reconstruct mechanical fields from a reduced number of inputs. A sensor placement optimization strategy is proposed by combining PCA and DEIM to minimize reconstruction errors. The algorithm is validated on laboratory specimens and on the PE itself, in both defect-free and defective configurations. The data-driven model allows for the detection of deviations from the nominal states predicted by the FE model.The resulting dual-core digital twin combines the predictive power of the physics-based model with the adaptability of the data-driven model. While the former ensures physical reliability the latter captures unmodeled deviations, especially in the presence of emerging defects. This hybrid strategy represents a promising solution for the predictive maintenance of pressure equipment under real operating conditions.Cette thèse porte sur le développement de jumeaux numériques (JN) pour la surveillance de l'endommagement progressif par fatigue mécanique d'un équipement sous pression (ESP) en service. L'objectif principal est de concevoir une approche hybride combinant la précision des modèles physiques par éléments finis (EF) et la flexibilité des modèles guidés par les données, en vue d'une solution robuste, réactive et adaptable à un environnement industriel réel. Pour cela, deux volets sont développés et couplés : un JN basé sur un modèle EF, et un autre fondé sur l'analyse en composantes principales (ACP) associée à la méthode DEIM, formant ensemble un JN bicéphale.Dans un premier temps, un modèle EF est élaboré conformément aux codes normatifs afin de simuler fidèlement le comportement mécanique de l'ESP, notamment au niveau des zones soudées critiques. Ce modèle est validé expérimentalement par des jauges de déformation, et couplé à des algorithmes de calcul de durée de vie basés sur l'approche S/N multiaxiale, avec la contrainte principale maximale comme critère équivalent. Une mise à jour dynamique du modèle est assurée par les mesures de pression collectées en service, permettant un suivi en temps réel de l'endommagement.Dans un second temps, les données issues des jauges de déformation sont exploitées pour reconstruire les champs mécaniques à partir d'un nombre réduit de mesures locales. Une stratégie d'optimisation du placement des jauges est proposée, combinant ACP et DEIM, afin de minimiser l'erreur de reconstruction. L'algorithme est validé sur éprouvettes et sur l'ESP, en présence ou non de défauts. L'approche guidée par les données permet ainsi de détecter les dérives par rapport aux états normaux simulés par le modèle EF.Le JN bicéphale combine les prédictions du modèle EF avec celles du modèle basé sur les données, permettant d'exploiter les forces des deux approches. Le premier assure la fiabilité physique des calculs, tandis que le second capte les dérives non modélisées, notamment en présence de défauts. Cette hybridation offre une solution avancée pour la maintenance prédictive des ESP en conditions de fonctionnement réelles
Heat exchange and thermal interactions of twin energy tunnels in sand
No full textInternational audienc
X-ray thermal diffuse scattering as a texture-robust temperature diagnostic for dynamically compressed solids
No full textInternational audienceWe present a model of x-ray thermal diffuse scattering (TDS) from a cubic polycrystal with an arbitrary crystallographic texture, based on the classic approach of Warren [B. E. Warren, Acta Crystallogr. 6, 803 (1953)]. We compare the predictions of our model with femtosecond x-ray diffraction patterns gathered from ambient and dynamically compressed rolled copper foils obtained at the High Energy Density instrument of the European X-Ray Free-Electron Laser facility and find that the texture-aware TDS model yields more accurate results than does theconventional powder model owed to Warren. Nevertheless, we further show: with sufficient angular detector coverage, the TDS signal is largely unchanged by sample orientation and in all cases strongly resembles the signal from a perfectly random powder; shot-to-shot fluctuations in the TDS signal resulting from grain-sampling statistics are at the percent level, in stark contrast to the fluctuations in the Bragg-peak intensities (which are over an order of magnitude greater); and TDS is largely unchanged even following texture evolution caused by compression-induced plastic deformation. We conclude that TDS is robust against texture variation, making it a flexible temperature diagnostic applicable just as well to off-the-shelf commercial foils as to ideal powders
