Hal-Diderot
Not a member yet
3207753 research outputs found
Sort by
SSA translation is an abstract interpretation
No full textthe 50th ACM SIGPLAN Symposium on Principles of Programming Languages (POPL 2023), 15 to 21 January 2023, Boston (MA) USAInternational audienceStatic single assignment (SSA) form is a popular intermediate representation that helps implement useful static analyses, including global value numbering (GVN), sparse dataflow analyses, or SMT-based abstract interpretation or model checking. However, the precision of the SSA translation itself depends on static analyses, and a priori static analysis is even indispensable in the case of low-level input languages like machine code. To solve this chicken-and-egg problem, we propose to turn the SSA translation into a standard static analysis based on abstract interpretation. This allows the SSA translation to be combined with other static analyses in a single pass, taking advantage of the fact that it is more precise to combine analyses than applying passes in sequence. We illustrate the practicality of these results by writing a simple dataflow analysis that performs SSA translation, optimistic global value numbering, sparse conditional constant propagation, and loop-invariant code motion in a single small pass; and by presenting a multi-language static analyzer for both C and machine code that uses the SSA abstract domain as its main intermediate representation
Extracting Statistical Properties of Solar and Photovoltaic Power Production for the Scope of Building a Sophisticated Forecasting Framework
No full textInternational audienceBuilding a sophisticated forecasting framework for solar and photovoltaic power production in geographic zones with severe meteorological conditions is very challenging. This difficulty is linked to the high variability of the global solar radiation on which the energy production depends. A suitable forecasting framework might take into account this high variability and could be able to adjust/re-adjust model parameters to reduce sensitivity to estimation errors. The framework should also be able to re-adapt the model parameters whenever the atmospheric conditions change drastically or suddenly—this changes according to microscopic variations. This work presents a new methodology to analyze carefully the meaningful features of global solar radiation variability and extract some relevant information about the probabilistic laws which governs its dynamic evolution. The work establishes a framework able to identify the macroscopic variations from the solar irradiance. The different categories of variability correspond to different levels of meteorological conditions and events and can occur in different time intervals. Thereafter, the tool will be able to extract the abrupt changes, corresponding to microscopic variations, inside each level of variability. The methodology is based on a combination of probability and possibility theory. An unsupervised clustering technique based on a Gaussian mixture model is proposed to identify, first, the categories of variability and, using a hidden Markov model, we study the temporal dependency of the process to identify the dynamic evolution of the solar irradiance as different temporal states. Finally, by means of some transformations of probabilities to possibilities, we identify the abrupt changes in the solar radiation. The study is performed in Guadeloupe, where we have a long record of global solar radiation data recorded at 1 Hertz
The propagation and reduction of uncertainty left unquantified by confidence intervals, p-values, neural network predictions, posterior distributions, and other statistical results
No full textIn the use of statistical models to analyze data, there is not only the uncertainty quantified by the models but also uncertainty about which models are adequate for some purpose, such as weighing the evidence for or against a hypothesis of scientific interest. This paper provides methods for propagating such unquantified uncertainty to the results under a unified framework of adequate model averaging. Specifically, the weight of each model used in the average is the probability that it is the most useful model. To allow for the case that none of the models considered would be useful, a catch-all model is included in the model average at a different level of the hierarchy. The catch-all model is the vacuous model in imprecise probability theory, the model that puts no restrictions on the probabilities of statements about the unknown values of interest. That enables defining the proportion of the uncertainty left unquantified by a model as the probability that it is inadequate in the sense of being less useful than the catch-all model. A lower bound for the proportion of unquantified uncertainty of the averaged model decreases as more models are added to the average
Spiral Bevel Gears: nonlinear dynamic model based on accurate static stiffness evaluation
No full textInternational audienceIn the present paper non-linear dynamics of a spiral bevel gear pair with backlash are investigated in order to clarify the internal excitations of major importance from the vibration point of view: manufacturing errors in the teeth profile, teeth spacing errors, and elastic deformation of the teeth. In some conditions, like in the case of backside contact, the destructive effect of internal excitations can be intensified leading to complex dynamics; for such reasons here backside contacts and reverse rotation are investigated in detail using a nonlinear time-varying model. The effect of damping is investigated as well. A one-DOF model is developed in order to study the dynamic behavior; the resulting a nonlinear differential equation with time-varying mesh stiffness is solved via numerical integration based on an adaptive step-size implicit Runge-Kutta scheme. The dynamic response of the system is analyzed through time histories, phase portraits, bifurcation diagrams, and Poincaré maps. Results show that for small backlash values, the possibility of backside contact increases. Meanwhile, by increasing the backlash value, the amplitude vibration of the gear rotation rises as well. By comparing the dynamic response of the system with different damping ratios, the results show that higher damping effectively reduces gear vibration resonance, although the probability of unsteady response still exists
Un catalogue de modèles ouverts d'aubes de la NASA
No full textThis catalogue contains computer-Aided Design (CAD) models, finite element (FE) meshes and reduced-order models (ROM) related to 39 open NASA geometries. Most of these geometries were initially defined at NASA Lewis Research Center in the context of research programs conducted in the 70’s and 80’s. Models related to these geometries have been recently computed and are made publicly available in this catalogue to facilitate the comparison of numerical strategies focusing on nonlinear structural interactions.Ce catalogue contient des modèles CAO (Conception Assistée par Ordinateur), des maillages éléments finis et des modèles réduits associés à 39 géométries ouvertes d'aubes de la NASA. La plupart de ces géométries ont été définies à l'origine au NASA Lewis Research Center dans le cadre de programmes de recherche conduits dans les années 70 et 80. Des modèles relatifs à ces géométries ont été récemment produits et sont mis à disposition dans ce catalogue pour faciliter la comparaison de stratégies numériques centrées sur les interactions structurelles non linéaires
OpenMCAD, un générateur d’aubes ouvert : des profils définis par arcs circulaires multiples au modèle CAO
No full textOpenMCAD is an Open-source Python 3 program designed to build blade fan and compressor blades geometries from a set of parameters. More precisely, it computes point clouds describing the blade profiles from multiple-circular-arc (MCA) profile parameters and may account for sweep and lean parameters. In addition to point clouds, it generates a computer-aided design (CAD) model of the blade and a finite element (FE) mesh. This program was initially developped for the design of blades that are robust to contact interactions. It is made publicly available to ease the generation of structural blade models and thus serve as basis. Input files related to 39 open NASA blade models are provided to serve as a basis for comparative work between different research teams on blade dynamics. Output files related to NASA rotor 37 are also provided as an example.OpenMCAD un code ouvert en langage Python 3 permettant de générer des modèles d’aubes de compresseurs et de soufflantes à partir d’un ensemble de paramètres. Plus précisément, OpenMCAD calcule les coordonnées des profils de l’aube définis par arcs circulaires multiples (MCA), et peut également prendre en compte des paramètres de flèche et d’inclinaison. En plus des coordonnées, un modèle CAO au format .step et un maillage éléments finis de l’aube sont générés. Ce code a été initialement dévéloppé dans le cadre de la conception d’aubes robustes aux interactions de contact. Il est mis à disposition pour faciliter la génération de modèles structuraux d’aubes. Les fichiers d’entrée relatifs à 39 géométries ouvertes d’aubes de la NASA sont fournis afin de servir de base pour la comparaisons de travaux de recherche portant sur la dynamique des aubes. Les fichiers de sortie de l’aube NASA rotor 37 sont également fournis à titre illustratif
Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation
No full textInternational audienceThis study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. The proposed method introduces a better search space to find the optimal solution at each iteration. However, we proposed RSA-SSA to avoid the searching problem in the same area and determine the optimal multi-level thresholds. The obtained solutions by the proposed method are represented using the image histogram. The proposed RSA-SSA employed Otsu’s variance class function to get the best threshold values at each level. The performance measure for the proposed method is valid by detecting fitness function, structural similarity index, peak signal-to-noise ratio, and Friedman ranking test. Several benchmark images of COVID-19 validate the performance of the proposed RSA-SSA. The results showed that the proposed RSA-SSA outperformed other metaheuristics optimization algorithms published in the literature
