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Les demandes de savoir adressées aux chercheurs en éducation par les acteurs sociaux de la haute performance : vers un renversement du processus de production et de diffusion de résultats
No full text[Colloque international organisé en 2023 par l’unité mixte de recherche Éducation, Formation, Travail, Savoirs (EFTS) : Faire résultat(s) dans les recherches en éducation. Pour quoi ? Avec qui ? Comment ?] Nathalie de BelerFacteurs organisationnels et humains (FOH), groupe Électricité de France (EDF).International audienceThe aim of this article is to report on original collaborations between social actors of high sporting and industrial performance and educational researchers, based on the hypothesis according to which the particularity of these actors induces certain reversals in the process of producing results. After presenting the dynamics of the meeting between actors from different worlds, we explain the logics of reversal that we were able to identify within these collaborations, through the filter of several implemented systems and which seem to us to open original heuristic paths for educational research.L’objet de cet article est de rendre compte de collaborations originales entre des acteurs sociaux de la haute performance sportive et industrielle et des chercheurs en éducation, à partir de l’hypothèse selon laquelle la particularité de ces acteurs induit certains renversements dans le processus de production de résultats. Après avoir présenté la dynamique de rencontre d’acteurs issus de mondes différents, nous explicitons les logiques du renversement que nous avons pu identifier au sein de ces collaborations, au filtre de plusieurs dispositifs mis en œuvre et qui nous semblent ouvrir des voies heuristiques originales pour la recherche en éducation.Plan -- Demande de savoir, performance et recherche en éducation -- Une rencontre inattendue pour les sciences de l’éducation et de la formation -- Coopérations, performance et renversements : quelques dispositifs pour la recherche en éducatio
Solving stochastic inverse problems for cfd using data-consistent inversion and an adaptive stochastic collocation method
No full textInternational audienceThe inverse problem we consider takes a given model and an observed (or target) output probability density function (pdf) on quantities of interest and builds a new model input pdf which is consistent with both the model and the data in the sense that the push-forward of this pdf through the model matches the given observed pdf. However, model evaluations in computational fluid dynamics (CFD) tend to require significant computational resources, which makes solving stochastic inverse problems in CFD is very costly. To address this issue, we present a nonintrusive adaptive stochastic collocation method coupled with a data-consistent inference framework to efficiently solve stochastic inverse problems in CFD. This surrogate model is built using an adaptive stochastic collocation approach based on a stochastic error estimator and simplex elements in the parameter space. The efficiency of the proposed method is evaluated on analytical test cases and two CFD configurations. The metamodel inference results are shown to be as accurate as crude Monte Carlo inferences while performing 103 less deterministic computations for smooth and discontinuous response surfaces. Moreover, the proposed method is shown to be able to reconstruct both an observed pdf on the data and key components of a data-generating distribution in the uncertain parameter space
Web of Simulation ontology (WoSO): Integration of Building Performance Simulations in IoT Systems
No full textInternational audienceBuildings are the single largest energy consumer in Europe. therefore, it’s crucial to increase their energy efficiency. In this context, however, building performance simulations (BPSs) can play an important role in supporting energy-efficient design and operations of buildings. Furthermore, the integration of Internet of Things (IoT) systems into building management can enable significant improvement in energy efficiency strategies. The synergy between BPSs and IoT systems holds great potential for optimizing energy management in buildings, paving the way for a significant reduction in energy consumption. For this vision to come true, BPSs and IoT systems need to interoperate as part of a smart building management system. This paper addresses this interoperability challenge at the semantic level, by introducing the Web of Simulations Ontology (WoSO) as a high-level description of BPSs and IoT system. WoSO focuses on capturing interaction between simulations and IoT systems by extending a referenceIoT ontology (SAREF) to include simulations as a component of the extended IoT system. Simulation modeling builds upon the Functional Mock-up Interface (FMI) specification, a widely adopted standard for describing simulation functionalities
Nonzero-sum stochastic impulse games with an application in competitive retail energy markets
No full textInternational audienceWe study a nonzero-sum stochastic differential game with both players adopting impulse controls, on a finite time horizon. The objective of each player is to maximize her total expected discounted profits. The resolution methodology relies on the connection between Nash equilibrium and the corresponding system of quasi-variational inequalities (QVIs in short). We prove, by means of the weak dynamic programming principle for the stochastic differential game, that the equilibrium expected payoff of each player is a constrained viscosity solution to the associated QVIs system in the class of linear growth functions. We also introduce a family of equilibrium expected payoffs converging to our equilibrium expected payoff of each player, and which is characterized as the unique constrained viscosity solutions of an approximation of our QVIs system. This convergence result is useful for numerical purpose. We apply a probabilistic numerical scheme which approximates the solution of the QVIs system to the case of the competition between two electricity retailers. We show how our model reproduces the qualitative behavior of electricity retail competition
Learning in Stackelberg Games with Application to Strategic Bidding in the Electricity Market
No full textInternational audienceWe formulate a two-stage electricity market involving conventional and renewable producers strategically bidding in the day-ahead market, to maximize their profits while anticipating the market clearing performed by an Independent System Operator (ISO), as a multi-leader single follower Stackelberg game. In this game, producers are interpreted as leaders, while the ISO acts as a follower.To compute an equilibrium, the classical approach is to cast the Stackelberg game as a Generalized Nash Game (GNG), replacing the ISO's optimization problem by its KKT constraints. To solve this reformulated problem, we can either rely on the Gauss-Seidel Best-Response method (GS-BR), or, on the Alternating Direction Method of Multipliers (ADMM). However, both approaches are implemented in a centralized setting since they require the existence of a coordinator which keeps track of the history of agents' strategies and sequential updates, or, is responsible for the Lagrange multiplier updates following the augmented Lagrangian.To allow the agents to selfishly optimize their utility functions in a decentralized setting, we introduce a variant of an actor-critic Multi-Agent deep Reinforcement Learning (MARL) algorithm with provable convergence.Our algorithm is innovative in that it allows different levels of coordination among the actors and the critic, thus capturing different information structures of the Stackelberg game. We conclude this work by comparing GS-BR and ADMM, both used as benchmark, to the MARL, on a dataset from the French electricity market, relying on metrics such as the efficiency loss and the accuracy of the solution
Handling polyhedral symmetries with a dedicated Branch&Cut: application to a knapsack variant
No full textIn this paper, we define a new variant of the knapsack problem, the Symmetric-weight Chain Precedence Knapsack problem (SCPKP). The (SCPKP) is the core structure of the Hydro Unit Commitment problem, the latter being a production scheduling problem relative to hydroelectric plants. The (SCPKP) is shown to be NP-hard. Polyhedral symmetries, featured by the (SCPKP), are introduced as a generalization of the classical symmetries applying only on the constraints without restricting the values of two symmetric solutions to be equal. A polyhedral study focuses on inequalities with 0-1 coefficients. Necessary facet defining conditions are described through a new structure, called pattern, encoding the polyhedral symmetries of the (SCPKP). A dedicated two-phase Branch & Cut scheme is defined to exploit the symmetries on the pattern inequalities. Experimental results demonstrate the efficiency of the proposed scheme in particular with respect to default CPLEX and a family of cover inequalities related to the Precedence Knapsack Problem
Structure and stability of small self-interstitials clusters in zirconium
No full textInternational audienceDensity Functional Theory and Embedded Atom Method potential calculations of small self-interstitials clusters in the hexagonal close packed (hcp) structure of zirconium have been performed. It is shown that by adding two self-interstitials in the lattice, the most stable configuration is triangular and contained into the basal plane. This particular configuration has been found in density functional theory and embedded atom method potential simulations. The same work is done by inserting three self-interstitials and the triangular configuration is again found as the most stable one. The study continues by adding self-interstitials to the planar structure and by reaching seven in density functional theory and thirty in embedded atom method potential calculations. The planar defect keeps a triangular configuration until seven self-interstitials, and beyond this amount, the triangle collapses by its summits into a hexagonal configuration. By considering it, an energetic model is proposed to describe the planar defect from two to seven self-interstitials. The stability of the identified configurations and the energetic model proposed constitute an important element to take into account when predicting the microstructural evolution of zirconium-based materials under irradiation
Probabilistic surrogate modeling by Gaussian process: A review on recent insights in estimation and validation
No full textInternational audienceIn the framework of risk assessment, computer codes are increasingly used to understand, model and predict physical phenomena. As these codes can be very time-consuming to run, which severely limit the number of possible simulations, a widely accepted approach consists in approximating the CPU-time expensive computer model by a so-called "surrogate model". In this context, the Gaussian Process regression (also called kriging) is one of the most popular technique. It offers the advantage of providing a predictive distribution for all new evaluation points. An uncertainty associated with any quantity of interest (e.g., a probability of failure in reliability studies) to be estimated can thus be deduced and adaptive strategies for choosing new points to run with respect to this quantity can be developed. This paper focuses on the estimation of the Gaussian process covariance parameters by reviewing recent works on the analysis of the advantages and disadvantages of usual estimation methods, the most relevant validation criteria (for detecting poor estimation) and recent robust and corrective methods
LE PRIX DE LA RÉNOVATION PERFORMANTE : UNE ESTIMATION DE L'AMPLITUDE DES COÛTS POUR LES LOGEMENTS RÉSIDENTIELS PRIVÉS ENSEIGNEMENTS-CLÉS
No full textÉnergétique (DPE) sert, entre autres, à fixer les cibles de performance énergétique du parc de bâtiments résidentiels ainsi que la nature des subventions possibles pour les ménages. Cependant, ces objectifs ne permettent pas de décrire les bouquets de travaux de rénovation énergétique nécessaires à l'atteinte concrète des classes du DPE visées. Une étude menée par EDF R&D s'est donné pour objectif d'expliciter la nature et le coût des travaux de rénovation énergétique permettant des sauts de classe du DPE. L'étude procède à deux explicitations : l'une sur le versant technique (nature des gestes), l'autre sur le versant économique (coût des gestes). Dans une approche statistique, les possibilités de bouquets de travaux combinés aux 2 300 logements de l'enquête PHEBUS conduisent à plus de 800 000 simulations. De manière globale, l'étude montre que le coût médian de la rénovation performante est de l'ordre de 200 à 350 €/m² de surface habitable suivant le type de logement, la classe DPE de départ et le niveau final atteint. La distribution des coûts des travaux est asymétrique et tournée vers les prix élevés. On observe donc des coûts très élevés (>500 €/m² de surface habitable) pour des combinaisons particulières « logement-bouquet » mais celles-ci sont statistiquement peu fréquentes. Nous montrons que moins le logement est performant au départ, plus le coût des travaux pour une rénovation performante est élevé. Cependant, cet écart de coût avec des logements plus performants reste faible au regard de la largeur des distributions
Lignes directrices pour assurer le contrôle humain d'un simulateur par apprentissage machine profond nécessitant une hybridation entre l'explication et la compréhension de ses spécifications formalisées par la théorie de la modélisation et de la simulation
No full textThe aim of our contribution is to share the guidelines of our work aimed at defining a formal specification framework for systems based on deep machine learning, in order to ensure rigorous and systematic control of these systems. Our work is in line with the theme of hybridisation between deep machine learning and formal representation methods. Our approach is based on a necessarily interdisciplinary hybridisation: in philosophy, more specifically regarding a perspective on philosophical concepts in epistemology, hermeneutics and technology in the light of this technology, and in computer science, regarding the modelling of complex phenomena.Notre contribution a pour objectif de partager les lignes directrices de nos travaux visant à définir un cadre de spécification formelle de systèmes basés sur de l'apprentissage machine profond afin d'assurer un contrôle rigoureux et systématique de ces systèmes. Nos travaux s'inscrivent dans la thématique d'hybridation entre l'apprentissage machine profond et des méthodes de représentation formelle. Notre approche est basée sur une hybridation nécessairement interdisciplinaire : en philosophie, plus précisément concernant une mise en perspective à l'aune de cette technologie des concepts philosophiques en épistémologie, en herméneutique et sur la technique, et en informatique, concernant la modélisation des phénomènes complexes