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Fourier Analysis on the Boolean Hypercube via Hoeffding Functional Decomposition
No full textFourier analysis on the Boolean hypercube is fundamentally defined as the orthogonal decomposition of the space of pseudo-Boolean functions with respect to the uniform probability measure. In this work, we propose an ANOVA-based generalization of the Fourier decomposition on the Boolean hypercube endowed with any arbitrary probability measure. We provide an \emph{explicit} decomposition basis which generalizes the Walsh-Hadamard (or parity functions) basis under any \emph{arbitrary} probability measure on the Boolean hypercube. We formulate the computation of the entire functional decomposition as a least squares problem and also provide a method to address the classical \emph{curse of dimensionality} challenge. We provide a comprehensive generalization of Fourier analysis on the Boolean hypercube, enabling the handling of non-uniform configuration spaces inherent to real-world machine learning tasks, \textit{e.g.} when dealing with \emph{one-hot encoded} features. Finally, we demonstrate its practical impact in the field of explainable AI, by conducting comparative studies with feature attribution methods such as SHAP or TreeHFD.</div
Assessing soil health at former thermal power plant sites through a functional approach
No full textInternational audiencePurposeSoils resulting from industrial activities are often perceived as severely degraded. However, they can exhibit unexpected and largely unexplored diversity in terms of soil health. This study aimed to assess soil health at two former thermal power plants based on soil characteristics (physical, chemical and biological properties) using a functional approach and a semi-quantitative rating method.MethodAt each site, areas corresponding to different previous industrial uses were identified, with the selection of twelve 100 m2 plots that were homogeneous in terms of vegetation and soil and distinct from each other. Within each plot, a soil profile was dug, described, sampled and analysed for bio-physico-chemical parameters. A dedicated model was applied to score soil functions from a selection of explicit parameters.ResultsEvaluation of the twelve soil profiles highlighted a strong heterogeneity, reflecting contrasted past land uses and soil modifications. Even soils sharing similar land uses differed markedly in terms of soil morphology, physicochemical and biological properties. Functional scores ranged from 0.25/5 to 3.96/5, revealing different potentials as far as carbon storage, biodiversity reservoir, water regulation and plant support functions are concerned. Overall soil health ranged from “strongly degraded” to “good”, with no soil reaching the “very good” class.ConclusionA soil health assessment, based on a multi-parameters functional approach, was conducted on two former thermal power plant sites. An original scoring method was developed that revealed a wide diversity in soil health levels that was explained by: i) pedoclimatic conditions, ii) past land uses and iii) management practices. Despite human impact, some Technosols showed relatively good soil health, confirming the hypothesis that high anthropization is not straightforwardly correlated to the level of soil functions
Review of "Asymptotic approaches for dealing with distorted crack geometries"
No full textThis is the open review or article https://doi.org/10.46298/jtcam.15907 published in JTCA
Bayesian optimization for re-analysis and calibration of extreme sea state events simulated with a spectral third-generation wave model
No full textAccurate hindcasting of extreme sea state events is essential for coastal engineering, risk assessment, and climate studies. However, the reliability of numerical wave models remains limited by uncertainties in physical parameterizations and model inputs. This study presents a novel calibration framework based on Bayesian Optimization (BO), leveraging the Tree structured Parzen Estimator (TPE) to efficiently estimate uncertain sink term parameters, specifically bottom friction dissipation, depth induced breaking, and wave dissipation from strong opposing currents, in the ANEMOC-3 hindcast wave model. The proposed method enables joint optimization of continuous parameters and discrete model structures, significantly reducing discrepancies between model outputs and observations. Applied to a one month period encompassing multiple intense storm events along the French Atlantic coast, the calibrated model demonstrates improved agreement with buoy measurements, achieving lower bias, RMSE, and scatter index relative to the default sea-state solver configuration. The results highlight the potential of BO to automate and enhance wave model calibration, offering a scalable and flexible approach applicable to a wide range of geophysical modeling problems. Future extensions include multi-objective optimization, uncertainty quantification, and integration of additional observational datasets
A Soil–Plant–Atmosphere Continuum model coupled to CFD to simulate plant energy and water exchanges in heterogeneous microclimates
No full textInternational audienceEstimating plant growth conditions in agrivoltaic, agroforestry, or urban environments are applied examples exhibiting the need to consider the intricate relationships between spatially heterogeneous microclimate conditions (short-wave and long-wave radiation, wind, turbulence, and air temperature), plant and soil energy balances with air and water exchanges. To capture these connections, the Soil–Plant–Atmosphere Continuum model from A. Tuzet has been implemented in the computational fluid dynamics software code_saturne, which simulates spatially heterogeneous and time-varying fluid flows, along with short-wave and long-wave radiation. This coupling is compared to experimental measurements from two French sites of the Integrated Carbon Observatory System (ICOS). Our model achieves significant outcomes in assessing energy exchanges, maintaining a relative error of less than 20% compared to ICOS measurements. In addition to accurately reproducing variations of latent and sensible heat fluxes due to radiation, the coupling of the water balance and stomatal conductance models demonstrates its capability to predict the evolution of soil water content over several days. Finally, an extrapolative study of fictive environments with plants beneath obstacles reveals promising opportunities to understand how obstacle-induced shadows and wakes affect plant temperature. This leads the way for further research in agrivoltaic, agroforestry, or urban configurations with spatial scales from approximatively 10m2 up to 1000m2 and temporal scales ranging from single moments to several consecutive days
Wave overtopping of rock-armored breakwaters in bimodal long-crested sea state conditions
No full textInternational audienceThe mean wave overtopping rate is an essential parameter to design coastal protections. Estimating it with a high precision is primordial to find a balance between a satisfactory safety level and a limited impact on the environment and construction costs. A series of laboratory experiments was conducted in a wave flume to estimate the wave overtopping discharge over a rock-armored breakwater in bimodal sea state conditions (combining swell and wind waves). Both simulated swell and wind wave systems were long-crested and colinear. Preliminary tests were performed on a smooth breakwater to validate the experimental set-up. Some trends in the results with the smooth slope can be characterized by the representative wave steepness. These trends are confirmed and amplified in the presence of the armor rubble slope. In that case, the measured wave overtopping rate can be significantly overestimated by existing prediction formulas, especially for sea state conditions with a high representative wave steepness, corresponding to a high wind-wave proportion in the sea state energy. We suggest two methods to take into account the effect of sea-state bimodality via the representative wave steepness to improve the wave overtopping rate estimations for smooth and armored rubble breakwaters
Multi-pollutant contribution of wood heating to emissions, concentrations and population exposure during winter time down to the street levels
No full textThis study is part of the work done by the Anses working group on residential wood heating, air pollution and health whose members are Delva F., Achard S., Cazier F., Collet S., Detournay A., Kimmerlin C., Le Dreff C., Leyssens G., Sartelet K., Thevenet F. and Tiakoulou C. The analyses, interpretations and conclusions in the present study are those of the authors and do not necessarily reflect those of the mentioned institutions.International audienceThis study quantifies the impact of residential wood heating on winter air quality in France, including street-level analysis in Paris. It applies a multi-scale model to simulate regulated and emerging pollutants, such as organic matter (OM), black carbon (BC), and ultrafine particles (UFP), associated with health risks. Wood-burning emissions in Île-de-France and Paris were estimated using detailed local surveys, a new classification of appliances and emission factors accounting for condensable compounds. Over France, emissions were quantified from the EMEP top-down emission inventory, with post-estimated condensables. Wood burning is a major contributor to particulate pollution: in France, it accounts for 39.9% of PM2.5, 72.4% of BC, and 76.7% of OM. In Paris, contributions are similar, except for BC (27.2% at street level), influenced by other sources, as road traffic. Contributions to UFP are lower, ranging from 7% in Parisian streets to 15.5% over France. Wood burning significantly contributes to outdoor population exposure in Paris (33% for PM2.5, 20% for BC, and 70% for OM), with heating emissions mostly from auxiliary and comfort use (98%). Two 2030 scenarios were evaluated: business-as-usual (BAU) and a national emission-reduction objective. Under BAU, PM2.5 emissions and concentrations decline by 32.6% and 13.4% over France, and by 18.1% and 14.2% in Paris. Concentration reductions are smaller than emission reductions because some PM2.5 components (e.g. inorganics) are unaffected by wood-burning controls. The national objective scenario achieves larger impacts, typically 50%-70% greater than BAU, reducing PM2.5 concentrations of about 22%-24% in urban and street environments. Environmental Implications Health risks of fine particles depend on their composition and size, with black carbon, organics, and ultrafine particles emerging as key indicators. Our results indicate that reducing residential wood heating is an effective policy lever to mitigate wintertime particulate pollution in urban areas. In Paris, a large share of emissions arises from auxiliary and comfort heating, suggesting that targeted measures addressing non-essential wood use could deliver substantial air-quality benefits. The transition to newer heating technologies should be carefully evaluated to ensure that improvements in mass-based air quality are not offset by increased ultrafine particle emissions, which are not covered by current regulations but may have important health implications
Plastic pollution in Leeward, Moorea and Cook islands (South Pacific): A baseline study
No full textInternational audiencePlastic pollution is increasingly affecting the South Pacific, including remote islands and coastal regions of Small Island Developing States (SIDS), yet data remain sparse in many areas. This baseline study presents original data on beach macrolitter and microplastics in surface waters and sediments across six islands of French Polynesia (Moorea, Bora Bora, Tahaa) and the Cook Islands (Aitutaki, Rarotonga), collected during a cruise in 2024. Beach surveys revealed high plastic contamination on most sites, with macroplastics (size >2.5 cm) densities ranging from 18 to 58 items/100 m, exceeding European threshold values (e.g. 22 items/100 m) on majority of sampled beaches. Single-use plastics and plastic fragments dominated litter, with local sources such as tourism and coastal activities clearly identifiable. Surface microplastics (315 μm–5 mm) were found at low densities, ranging from 0 to 4668 particles/km2, confirming relatively low contamination in surface waters. Only 17 particles were detected from 8 manta net tows. Sediment and beach microplastic analysis yielded very limited results, with microplastics found at only two sites (Huahine and Rarotonga), dominated by fragments and colored fibers. These results suggest localized contamination linked to urbanization and tourism rather than widespread oceanic inputs. Despite methodological limitations due to the cruise format, this study contributes rare data from undersampled regions, supporting long-term monitoring efforts and informing future policy and mitigation actions. The results underline the need to improve regional waste management, which will be beneficial for local societies largely based on touris
Second-moment turbulent models for incompressible flows : some recent -and less recent- results
No full textInternational audienc
Determination of the Effective Permeabilities in Partially Saturated Porous Media, Using the Periodic Homogenization Technique
No full textInternational audienceAbstract In this study, we address determination of the effective permeabilities in rigid, partially saturated porous media for an immiscible two-phase Newtonian fluid flow. The periodic homogenization technique is applied to derive macroscopic flow laws for two-phase systems from the pore-scale Navier–Stokes equations governing immiscible fluids. Two distinguished cases are considered: two incompressible fluids (case 1) and an incompressible fluid with a compressible one (case 2). In both cases, the homogenized result shows the independence of the macroscopic laws and the closure problems on the fluid compressibility, except for the macroscopic mass conservation equation. Finally, numerical simulations are performed by solving the closure problems for a given interface position determined from the phase-field simulations, in order to analyze the role of each effective permeability in the generalized Darcy’s law for several fluid mixtures and different porosity. The numerical results offer insights into the influence of microstructure, fluid properties, and capillary bridge distribution on the effective permeabilities