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Stochastic dynamics and surrogate modeling for nonlinear aerospace nozzle systems with partial observations
No full textInternational audienceThe present research addresses a computational implementation of a methodology aimed at identi- fying a statistical surrogate model using a small incomplete target dataset [1]. The structure under consideration is a three-dimensional engine nozzle, composed of an elastic homogenized material and that is subjected to an internal stochastic pressure jet. It is assumed to undergo large displace- ments. A limited target dataset consisting of a subset of normal displacements located at the nozzle exit, expressed in the frequency domain, is assumed to be available.A parameterized nonlinear stochastic computational model (SCM) of the nozzle dynamics is de- veloped [2], where controlled parameters represent the spectral properties of the stochastic load, while uncontrolled parameters describe the anisotropic properties of the material. Due to the com- plexity of such a highly nonlinear SCM, significant computational resources are required to obtain one response for a given set of parameters.Initially, the nonlinear SCM is used with given control parameters, without uncontrolled parame- ters and with stiffened elastic moduli, in order to get the quantities of interest (QoI) corresponding to the small incomplete target dataset. The parameterized nonlinear SCM is also employed with random values of both controlled and uncontrolled parameters to construct a small training dataset. This latter one describes the realizations of the controlled parameters, the corresponding random responses at the nozzle exit, and the corresponding QoI that are related to the target.The PLoM algorithm, based on a purely probabilistic approach [3,4], is used and adapted to the constraint of an existing incomplete target dataset [1] in order to develop a surrogate computational model. The learning set consists of realizations of controlled parameters and their corresponding QoI. This surrogate computational model allows for updating the response, which is brought closer to the target response.[1]C. Soize, R. Ghanem, Probabilistic-learning-based stochastic surrogate model from small in- complete datasets, Computer Methods in Applied Mechanics and Engineering, 418(A), 116798, 2024.[2]E. Capiez-Lernout, O. Ezvan, C. Soize, Updating nonlinear stochastic dynamics of an uncertain nozzle model using probabilistic learning with partial observability and incomplete dataset, Journal of Computing and Information Science and Engineering, 24(6): 061006, 2024.[3]C. Soize, R. Ghanem, Data-driven probability concentration and sampling on manifold, Journal of Computational Physics, 321 242-258 (2016).[4]C. Soize, R. Ghanem, Probabilistic learning on manifolds (PLoM) with partition, International Journal for Numerical Methods in Engineering, 123(1), 268-290 (2022)
Confronting standards for a traffic safety rule: fairness and perceived legitimacy
No full textInternational audienceWhile correlational studies have shown that perceived legitimacy is positively associated with greater internalization of traffic rules and stronger intentions to respect them (Carnis et al., 2023), a more experimental approach is needed to understand the dynamics of this relationship. This research aims to investigate the role of fairness—one of the key dimensions of perceived legitimacy (i.e., the perception that a rule applies equally to all, without distinction; Varet et al., 2021)—in shaping individuals’ relationship with traffic regulations. We hypothesize that emphasizing the exceptions to the application or the enforcement of certain rules for certain types of road users will have a negative impact on their perceived legitimacy, internalization, and inten-tion to comply. This effect is expected to be more pronounced for road user groups disadvan-taged by the rule.These hypotheses were tested in two experimental studies with car drivers and cyclists (Study 1, N = 216; Study 2, N = 220), focusing on the stop-at-red-light rule. In Study 1, participants were presented with a scenario highlighting that, in France, cyclists are allowed to cross red lights under certain conditions, whereas car drivers are not. In Study 2, participants were reminded that red-light cameras are primarily calibrated to monitor car drivers, but not cyclists. Both stud-ies included a no-induction control condition.Results indicate that perceptions of fairness significantly influence the perceived legitimacy of traffic rules, with effects varying based on participants’ group membership. Specifically, high-lighting unfairness (in the rule itself, Study 1, or its enforcement, Study 2) reduced drivers’ per-ceptions of legitimacy. These findings have important implications for road safety policies, sug-gesting that perceived fairness is a crucial factor in fostering rule acceptance and compliance among road users
Problématique de l'apprentissage continu pour le passage à l'échelle de la méthode NeRF appliquée à l'imagerie satellitaire
No full textInternational audienceProblématique de l'apprentissage continu pour le passage à l'échelle de la méthode NeRF appliquée à l'imagerie satellitair
Foreign policy and place branding
No full textInternational audienceThis manuscript demonstrated the relationship between place branding and foreign policy. Integral to governmental public diplomacy initiatives to engage and persuade target audiences, place branding is one way to make a nation’s culture, economy, education, social life, and political ideas and policies more attractive. Therefore, place branding integrates public policies related to a specific region with internationalization strategies and efforts in the private sector. By mobilizing several illustrative cases, this article identified two critical roles of place branding practices in foreign policy implementation: 1) The place-industry-product nexus contributes to the international competitiveness of a specific region in terms of economy, industry, and business; 2) Place branding involves building international image and reputation of a country, promoting soft power statecraft
Données Trafic moyen journalier annuel de 2019 Description et correction des données Poids lourds
No full textThe average annual daily traffic (AADT) for a road section is obtained by calculating the annual average of the number of vehicles on the section, in all directions, over the course of a day. As the original 2019 French dataset contained errors on the ratio_PL variable, this dataset is the corrected version, accompanied by an R notebook documenting the corrective treatments applied. The tmja-2019-corrige.gpkg dataset was produced in order to be able to map heavy goods vehicle road flows in 2019.Le Ministère de la Transition écologique a publié en open data de 2018 à 2021 des données agrégées de trafic routier sur le réseau routier national français couvrant la période 2007-2019. Nous avons cherché à mobiliser les données de 2019 en vue de réaliser une cartographie du trafic routier poids lourds, mais les données concernant les poids lourds ne sont pas exploitables en l'état. Des échanges avec les services du Cerema, nous ont permis de proposer une correction. Cet article propose de présenter le jeu de données et ses failles ainsi que de détailler les corrections apportées. Nous présentons aussi de nouvelles variables de mesure de flux horaires du trafic routier Poids Lourds
Impact de la profession sur la motivation des professionnels pour la réalisation de leur vocationLe cas des interprètes de conférence
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A novel clay shrink-swell buildings damage model: From unstructured insurance data to the creation of buildings database, and the proposition of damage severity scale
No full textInternational audienceExpansive clay soils undergo seasonal moisture fluctuations, swelling when wet and shrinking during dry periods. These volumetric changes induce differential ground movements beneath buildings, often resulting in structural damage, particularly in low-rise residential buildings. In France, this phenomenon has become increasingly costly, with average annual insurance claims of 1 billion euros between 2016 and 2021, rising to 3.5 billion euros in 2022 due to severe droughts and heatwaves driven by climate change.Despite its growing impact, damage assessment remains challenging due to the scarcity of empirical data and the localized variability of soil-structure interactions. To address this, we propose a scalable, data-driven methodology that combines expert knowledge and advanced natural language processing to enable empirical risk analysis.This study introduces the Clay Shrink-Swell Damage Severity Scale, constructs a structured database of building and environmental characteristics, and identifies damageability factors based on observed damage levels. A total of 10,325 loss adjustment reports from Generali (2000–2021) were analysed. A subset of 155 reports was manually annotated and scaled to the full dataset using Large Language Models (LLMs) under a Retrieval-Augmented Generation (RAG) framework.The resulting tools provide a solid foundation for post-event assessments, support rapid field diagnostics, and enable the development of personalized prevention strategies. This work contributes to improved vulnerability modelling and more effective risk reduction in a changing climat
This is a map of 'Jardin Lecoq' - Analyzing map descriptions from LLMs
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Ces agent·es qui ne font (pas) que passer.: Les CDD de la fonction publique dans les trajectoires socioprofessionnelles
No full textInternational audiencePrenant appui sur une post-enquête à l’enquête Conditions de travail, cet article interroge l’expérience et les usages des CDD par les agent·es contractuel·les de la fonction publique. Une analyse statistique fait d’abord ressortir certains traits saillants de leurs trajectoires et situations d’emploi (expériences répétées de la précarité, durée d’emploi contractuel, temps partiel, déqualification, etc.). L’analyse qualitative d’un corpus d’entretiens conduit ensuite à identifier six expériences typiques de l’emploi contractuel dans la fonction publique. Cette typologie permet d’analyser comment cette expérience de l’emploi contractuel est vécue, en portant attention aux variations selon le genre, l’âge, la situation familiale et le niveau de qualification
Description of the Polach model compared to FASTSIM and CONTACT and a proposal for a variant dedicated to large creepages
No full textInternational audienceThe Polach model is a fast and versatile method for calculating tangential forces in railway dynamics under Hertzian conditions. Although its theoretical basis is well established in the original publications, it lacks expressions of local quantities such as tractions and relative slip velocities. They are given in this article in the absence of spin, within the frame of Kalker's original theory, and compared with CONTACT and FASTSIM with an elliptical normal pressure distribution. As for the extended Polach method dedicated to traction and braking, it is generally no longer possible to associate an expression of these local quantities with the tangential forces. In the limited cases where this is still possible, it is found that the tractions associated with the Polach model are very close to those of extensions of CONTACT and FASTSIM with an elliptical normal pressure distribution. Following this observation, a variant of the Polach method is proposed based on the extension of FASTSIM, providing insight into local quantities in the absence of spin. The principle of this modification could be applied to any approximate method based on Kalker's simplified theory in order to extend its field of application to large creepages