HAL Portal Cnam (French National Conservatory for Arts and Crafts)
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Data assimilation for prediction of ammonium in wastewater treatment plant: From physical to data driven models
No full textInternational audienceThis study compares various modeling approaches to predict ammonium concentration in wastewater treatment plants (WWTPs), with a focus on integrating data assimilation techniques. It explores white-box, grey-box, and black-box models, evaluating their ability to capture the complex dynamics of WWTPs and manage uncertainties associated with limited data and sensor noise. The article highlights the importance of data assimilation for simultaneously calibrating model parameters, latent variables (such as unmeasured species concentrations), and quantifying prediction uncertainty. Simulation results demonstrate that the non-parametric black box model outperforms all other models in terms of predictive accuracy and uncertainty estimation. This finding underscores the effectiveness of machine learning when integrated with data assimilation techniques to extract insights from training datasets, even in the presence of limited data. Interestingly, the addition of an extra sensor, such as an oxygen sensor, did not enhance model performance. Experiments conducted in a real system showed that the non-parametric black box model could effectively capture the general dynamics of ammonium concentration in an actual wastewater treatment plant. However, its performance was somewhat diminished compared to simulation results, likely due to variability in input concentrations that were not accounted for in the model
Who is more likely to find a job? A Person-Centered Approach to the Study of employability profile
No full textInternational audienc
Analytic solutions and numerical method for a coupled thermo-neutronic problem
No full textWe consider in this contribution a simplified idealized one-dimensional model in a nuclear core reactor coupling the diffusion equation on the neutron flux withthe enthalpy equation for the water which collects the heat produced by this idealized nuclear core. These equations are coupled through the dependency of thecoefficients of the diffusion equation in terms of the enthalpy. We propose a numerical method treating globally the coupled problem for finding its unique solution.Simultaneously, we use incomplete elliptic integrals to represent analytically the density of neutrons and the enthalpy in the fluid. Both methods lead to the samesolution with high accuracy. However, another quantity, generally used as a benchmark for comparing results, depends considerably on the approximation used forthe coefficients of the diffusion equation
Clinical phenotyping of people living with type 1 diabetes according to their levels of diabetes-related distress: results from the SFDT1 cohort
No full textInternational audienceIntroduction: Type 1 diabetes is burdensome, requiring complex daily management and making people more prone to emotional distress. To better detect diabetes-related distress (DD) and identify at-risk patients, we aimed to provide an in-depth characterization of DD in people with type 1 diabetes.Research design and methods: We included adults with type 1 diabetes from the Suivi en France des personnes avec un Diabète de Type 1 cohort who filled in the Problem Areas in Diabetes questionnaire (PAID ≥40 indicates high DD). Age and sex-adjusted multivariable logistic regression models analyzed individual characteristics, clinical indicators, diabetes-related complications and psychological factors. We further analyzed DD according to six data-driven subdimensions: emotional distress, fear of complications, social distress, eating distress, management distress, and diabetes burnout.Results: In total, 1220 participants (50.6% female, age 42 years (SD 13.9), diabetes duration 24.7 years (13.6)) had a total mean PAID score of 39.6 (21.7) and 592 (48.5%) reported high DD. Leading subdimensions of DD included fear of complications (50.1 (24.4)) and diabetes burnout (45.9 (24.5)). Females, younger age, social vulnerability, smoking, and the presence of retinopathy were positively associated with high DD (p<0.05). We observed similar DD levels across HbA1c levels and treatment modalities, including automated insulin delivery and continuous glucose monitoring use. Several psychological factors, such as anxiety/depression, poor sleep quality, and treatment burden, were strongly associated with DD (p<0.001).Conclusions: We provide a holistic clinical phenotyping approach that enables the identification of determinants and prevalence of DD, overall and according to key DD subdimensions, in a large and diverse population. Our results underscore the importance of developing DD-targeted prevention and intervention strategies focused specifically on high-risk groups and the most impactful distress subdimensions to reduce the impact of type 1 diabetes burden.Trial registration number: NCT04657783
Very high order finite volume solver for multi component two-phase flow with phase change using a posteriori Multi-dimensional Optimal Order Detection
No full textInternational audienceIn this work we propose a very high-order compressible finite volume scheme with a posteriori stabilization for the computation of multi-component two-phase flow with phase change. It is based on finite volume approach using moving least squares (MLS) reproducing kernels for high order reconstruction of the Riemann states. Increased robustness is achieved by using the multi-dimensional optimal order detection (MOOD) method to get a high-accurate and low-dissipation scheme while maintaining boundedness and preventing numerical oscillations at interfaces and strong gradient zones. The properties of the proposed framework are demonstrated on classical test problems starting with convergence order verification on simple scalar advection test cases. More complex shock and more stringent tube tests with various water, steam and air concentration are then simulated and compared with available references in the literature. Finally, the ability of the proposed approach to compute multi-component flows with phase change is illustrated with the simulation of a liquid oxygen jet in gaseous hydrogen
La théorie féministe au défi du handicap: Recueil de textes des feminist disability studies
No full textInternational audienceComment intégrer le handicap dans les réflexions féministes ? Ce recueil élaboré et préfacé par un collectif d'universitaires et de militantes handi-féministes propose de chercher les réponses dans le champ théorique méconnu des feminist disability studies, à la croisée des études sur le handicap et des études féministes. Les textes fondateurs anglo-saxons présentés, écrits entre 1981 et 2006, explorent les thèmes du care, de la prise en compte de l'intime dans la définition du handicap, des enjeux validistes du droit à l'avortement, ou encore de l'altérité des corps féminins et handicapés.Un ouvrage important pour nous aider à réfléchir théoriquement et politiquement aux rapports de pouvoir et aux luttes collectives à mener
Z-SpecNNet: A Real-Time Embedded NN-Based Parameters Estimation for WPT Systems
No full textInternational audienceThis article proposes a fully embedded real-time mutual inductance and load estimation technique (Z-SpecNNet) applicable to wireless power transfer (WPT) systems. The technique consists of a three-step process, starting with online noise injection from the supplying converter to excite the system over a wide bandwidth. During the noise injection, the voltage and current at the converter output are recorded, allowing the system impedance to be calculated by fast Fourier transform. Finally, a neural network computes an estimate of the desired parameters. In this work, the Z-SpecNNet is applied to a series--series compensated system as it is one of the most popular compensation topologies in the literature and because it is the topology for which the information of load and mutual coupling result most correlated and therefore more difficult to estimate. The proposed Z-SpecNNet offers significant advantages because impedance spectroscopy is a straightforward and model-free method for characterizing system behavior. Furthermore, the neural network can be rapidly trained on a known transfer function. The technique has been demonstrated to be effective on a low-cost microcontroller that integrates the control of the converter. Experimental results indicate a mean relative estimation error of 7.81% with a total estimation time of 85 ms
Investigation of a constitutive law for the prediction of the mechanical behavior of WEEE recycled polymer blends
No full textInternational audienceThis research focuses on a mechanical study of an acrylonitrile–butadiene–styrene (ABS)/ polycarbonate (PC) blend totally derived from Waste Electrical and Electronic Equipment (WEEE) recycling. First, an experimental work was developed in laboratory for the preparation of different mixtures of ABS/PC blend. Then, mechanical tensile tests were performed on the injected specimens and the stress/strain experimental data were gathered to be used in the modelling part. In order to enable the prediction of the mechanical response of the blend, G’Sell and Jonas constitutive law was considered for this purpose. An optimization method based on the Generalized Reduced Gradient (GRG) nonlinear algorithm was developed to identify the input parameters governing the mechanical model. In addition, an uncertainty parametric study was assessed to qualitatively and quantitatively evaluate the constitutive law sensitivity versus the parameter uncertainty. Monte Carlo simulations were performed and the convergence of the numerical model was proved in terms of means and standard deviation statistical data. The results showed an excellent agreement between the numerical approach and the experiments. Besides, it was highlighted the crucial role of coupling uncertainty parametric study with modelling for accurately describing the mechanical behavior of the blend
Erratum: Nonlinear interaction of an acoustical wave with a counter-propagating weak shock [J. Acoust. Soc. Am. 156 , 4085–4098 (2024)]
No full textInternational audienc
Ces représentations de soi qui accompagnent nos activités
No full textinnovation-pedagogique.frRepresentational activity is therefore an activity whose product is the presence to a subject-in-activity of objects that are at the same time absent from its environment. They can be defined as activities that take the place of their objects and can occur in their absence. The self-representations accompanying the activities have the same contours as the activities themselves. Self-representations correspond to the constructions of meaning that a subject makes about his or her own journey. The images that a subject “offers” to others correspond to the faces that the subject would like to show. The tension generated between these representations and images is an essential tool for understanding the dynamics of a subject's identity.L’activité de représentation est donc une activité qui a pour produit la présence à un sujet-en-activité d’objets en même temps absents de son environnement. Elles peuvent être définies comme des activités tenant lieu de leurs objets et pouvant survenir en leur absence. Les représentions de soi accompagnant les activités ont les mêmes contours que les activités elle- mêmes. Les représentations de soi à soi correspondent aux constructions de sens qu’un sujet effectue sur son propre parcours. Les propositions d’images qu’un sujet ‘offre’ à autrui correspondent aux faces que ce sujet aimerait donner à voir. La tension générée entre ces représentations et ces images constitue un outil essentiel pour comprendre les dynamiques identitaires des sujets