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Detailed validation of LES for H 2 /CH 4 /Air deflagrations in an obstructed tube using PIV measurements
No full textInternational audienceThis study offers a detailed validation of Large Eddy Simulation (LES) for lean H2/CH4/Air deflagrations in an obstructed tube. An exhaustive validation is conducted against detailed measurements from Li et al. (2019), which include pressure traces, flame speeds, and especially, Particle Image Velocimetry measurements of the deflagration-induced flow field. The exercise is performed without adjusting any model parameters, so that all simulations are executed using a unique numerical setup across all test cases. This approach provides a robust and unbiased assessment of LES capabilities in capturing the complex interactions between flame propagation, turbulence, and obstacles in explosion scenarios. Results demonstrate that LES accurately predicts the detailed evolution of the flow field in the recirculation zone behind the second obstacle, and the resulting over-pressure as well as flame speed and flame qualitative shape for various deflagration severities. Such results highlight the potential of LES for improving Safety Computational Fluid Dynamics predictive capabilities in industrial applications involving explosive environments. Once validated, LES is analyzed to unravel flame propagation dynamics: It is demonstrated that the flame remains laminar-like up to the second obstacle and then transitions to the turbulent combustion regime. Independently from the mixture blend, the maximum over-pressure is correlated to flame-turbulence interactions occurring in the wake of the second obstacle. While LES effectively captures these dynamics, it is noted that usual methods to quantify flows in pipes are inadequate for fully characterizing the transition to turbulence: Developing more refined indicators to detect this transition are required
K-Means and Gaussian Mixture Models on Lie Groups: Application to Geometrical Clustering
No full textIn this article, we derive and implement two new clustering algorithms dedicated to Lie groups, adapted from the well known K-Means algorithm and Gaussian mixture models. More precisely, the K-Means algorithm is reformalized by taking into account the fact that observations belong to a Lie group (LG) with an appropriate intrinsic metric and Gaussian mixture model are defined for data living in LGs. The consistency and the performance of the resulting are numerically validated for data lying on the LG SE(2), by comparison with state-of-the-art methods for synthetic data and pseudo-real data generated using an ultra-sound sensor model
Vulnérabilité, Adaptation, Atténuation face au CHangement climatique de l'Elevage de Ruminants et de porcINs ; Scénarios d’évolution du cadre socio-économique de l’agriculture à l’horizon 2050
No full textLe naufrage de la New Keynesian Economics démontré dans un modèle révisé de Blanchard et Kyotaki
No full textInternational audienc
Improvement of the KarstMod modelling platform for a better assessment of karst groundwater resources
No full text(IF 5.7;Q2)International audienceHydrological models are fundamental tools for the characterization and management of karst systems. We propose an updated version of KarstMod, software dedicated to lumped-parameter rainfall-discharge modelling of karst aquifers. KarstMod provides a modular, user-friendly modelling environment for educational, research, and operational purposes. It also includes numerical tools for time series analysis, model evaluation, and sensitivity analysis. The modularity of the platform facilitates common operations related to lumped-parameter rainfall-discharge modelling, such as (i) setup and parameter estimation of a relevant model structure and (ii) evaluation of internal consistency, parameter sensitivity, and hydrograph characteristics. The updated version now includes (i) external routines to better consider the input data and their related uncertainties, i.e. evapotranspiration and solid precipitation; (ii) enlargement of multi-objective calibration possibilities, allowing more flexibility in terms of objective functions and observation type; and (iii) additional tools for model performance evaluation, including further performance criteria and tools for model error representation
MELINA : Une synergie maghrébine et européenne pour innover vers éclairage durable et responsable
No full textNational audienceInternational collaboration plays a crucial role in developing innovative and sustainable solutions. In this context, the PHC Maghreb MELINA project "Mastering Efficient Lighting in North Africa" was a flagship initiative between 2020 and 2022, bringing together partners from the three Maghreb countries (University of Monastir - Tunisia, Djillali Liabès University - Algeria, University of Tetouan - Morocco) and the University of Toulouse III - France. This project laid the foundations for an in-depth collaboration, which is now continuing in the European CBHE MELINA project "Capacity Building in Higher Education", launched in 2025.La collaboration internationale joue un rôle crucial dans le développement de solutions innovantes et durables. Dans ce cadre, le projet PHC Maghreb MELINA « Mastering Efficient Lighting in North Africa » a été une initiative phare entre 2020 et 2022, réunissant des partenaires des trois pays du Maghreb (Université de Monastir -Tunisie, Université Djillali Liabès - Algérie, Université de Tétouan- Maroc) et l’université de Toulouse III -France. Ce projet a posé les bases d’une collaboration approfondie, qui trouve aujourd’hui une continuité dans le projet européen CBHE MELINA «Capacity Building in Higher Education», lancé en 2025
Review on cavity-resonant integrated grating filters
No full textInternational audienceWe review the investigations that have been carried out over the past decade on waveguide Fabry-Pérot microcavities with an embedded input/output grating coupler, devices often referred as Cavity-Resonant Integrated Grating Filters (CRIGFs). We will explain how the device geometry and use of various technological platforms (SiON, LiNbO3 on insulator, GaAs) has permitted the fabrication of spatially-localized wavelength filters that can operate from the nearinfared to mid-infrared, subsequently enabling applications as laser spectral stabilization or as pixelated filter for (hyperspectral) imaging. Furthermore, we will show that the design can be adjusted to obtain critically-coupled highquality factor microresonators with a view to induce efficient second harmonic generation or, more generally, nonlinear parametric conversion. Finally, we will present our most recent investigations that have been devoted to the selective excitation of the supported higher order spatial modes and how the latter can be used to implement reconfigurable logical gates
Aboveground biomass dataset from SMOS L-band vegetation optical depth and reference maps
No full textInternational audienceAboveground biomass (AGB) is an essential component of the Earth's carbon cycle. Yet, large uncertainties remain in its spatial distribution and temporal evolution. Satellite remote sensing can help improve the accuracy of AGB estimates. In particular, the L-band (1.41 GHz) vegetation optical depth (VOD) derived from the SMOS (Soil Moisture and Ocean Salinity) mission is a good AGB proxy. Averaging the SMOS L-VOD over a year and linking it to an existing AGB map constitute a well-established method to derive a spatial relationship between the two quantities. Then, a temporal extrapolation of this spatial relation derives global and harmonized AGB time series from the L-VOD. This study refines this protocol by analyzing the impact of three factors on the AGB-VOD calibration. First, an analysis shows that ascending and descending VOD can be properly merged to estimate the AGB. Second, the use of a single global spatial relationship is preferred over several regional ones. Third, this new AGB dataset is compared with other published AGB datasets to assess the validity of the temporal extrapolation. The produced dataset provides vegetation biomass values up to 300 Mg ha -1 from 2011 onward. It shows more interannual variability than the other available time series and presents globally lower AGB estimates. In general, the resulting AGB is consistent with the AGB maps of the Climate Change Initiative (CCI) Biomass version 5 (average Pearson's correlation coefficient 0.87) and can be used in AGB studies. The AGB dataset has been produced from the Level 2 SMOS products with one global VOD-AGB relationship, mixing ascending and descending orbits. The AGB dataset, including the spatial bias, is open-access and the NetCDF files are available at https://doi.org/10.12770/95f76ff0-5d89-430d-80db-95fbdd77f543 (Boitard et al., 2024)
Factorisation QR avec pivotage et troncature en précision mixte
No full textInternational audienceLow-rank approximations are widely used to reduce the memory footprint and operational complexity of numerous linear algebra algorithms in scientific computing and data analysis. In some of our recent work we have demonstrated that low-rank approximations can be stored using multiple arithmetic precisions to further reduce the storage and execution time. In this work we present a method that can produce this mixed-precision representation directly; this relies on a mixed-precision truncated rank-revealing QR (RRQR) factorization with pivoting. We present a floating-point error analysis and provide bounds on the error of the approximation demonstrating that the use of multiple precisions does not alter the overall accuracy. Finally, we presentexperimental results showing the execution time reduction for the cases where either classical or randomized pivoting are used.Les approximations de rang faible sont couramment utilisées pour réduire la consommation de mémoire et la complexité calculatoire de nombreux algorithmes d’algèbre linéaire en calcul scientifique et analyse des données. Dans nos travaux récents, nous avons démontré que les approximations de rang faible peuvent etre stockées en utilisant de multiples précisions arithmétiques pour réduire d’avantage la mémoire et le temps d’exécution. Dans ce document, nous présentons une nouvelle méthode qui produit directement ces représentations; elle repose sur une factorisation QR en precision mixte tronquée et avec pivotage. Nous présentons une analyse des erreurs d’arrondi en virgule flottante ainsi que des bornes pour l’erreur d’approximation montrant que l’utilisation de plusieurs précisions ne dégrade pas la qualité de la solution finale. Finalement, nous présentons des résultats expérimentaux montrant la réduction du temps d’exécution obtenue avec les méthodes proposées
Unveiling Impurity Profiling of Synthetic Pathways of Organophosphorus Chlorpyrifos Through LC‐HRMS Metabolomics‐Based Approaches
No full textInternational audienceSourcing in chemical forensic science refers to the attribution of a sample to a specific source using a characteristic signature. It relies on the identification of chemical attribution signatures (CAS), including chemical markers such as residual synthetic precursors, impurities, reaction by-products and degradation products, or even metabolites. Undertaking CAS for chemical threat agents (CTA) can be used to provide an evidentiary link between the use of a given chemical and its precursor(s) to support forensic investigations. Organophosphorus compounds, a class of nerve agents, can be produced by different, more or less complex synthesis routes that can lead to specific CAS. Chlorpyrifos (CPF), an organophosphorus pesticide, was selected as model compound. To assess the specificity of impurity markers originated from a chemical synthesis, untargeted fingerprints of crude CPF from different synthesis pathways were analyzed as a first use-case using metabolomics-based trace discovery strategies. Seven different CPF synthesis routes were considered, and their crude mixtures were analyzed with a minimal sample preparation. Analyses were performed on a trapped ion mobility spectrometry (TIMS) coupled to liquid chromatography (LC) and high-resolution mass spectrometry (HRMS). Chemometrics analyses were conducted with multivariate methods to extract discriminating features (i.e., relevant impurities), annotate, and identify them. Then, unknown samples were analyzed in blind conditions without any information of the synthesis pathway employed. The aim is to validate the methodology seeking some discriminating impurities identified in the first section to attribute and classify them according to the synthesis route. | IntroductionThe reported uses of chemical threat agents (CTAs), including chemical warfare agents (CWAs) over the last decade, emphasize the need for powerful analytical tools, such as chemical approaches, to support forensic investigations not only by enabling the identification of toxic compounds, but also by enabling the samples comparison to identify the source of the</div