Found 31 document(s)
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The "PLoM_Python_V1_2024" package is the Python conversion of the Matlab code "PLoM_Matlab_V1_2024," which is available on GitHub. The PLoM (Probabilistic Learning on Manifolds) software is a Python-based toolbox designe...
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A novel extension of the Probabilistic Learning on Manifolds (PLoM) is presented. It makes it possible to synthesize solutions to a wide range of nonlinear stochastic boundary value problems described by partial differen...
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This paper presents a machine learning approach for detecting structural stiffness changes of civil engineering structures considered as dynamical systems, using only an experimental database constituted of a small numbe...
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This paper is devoted to the uncertainty quantification for 3D acoustic performance model of nacelle liners (acoustic treatments). Uncertainties are taken into account in order to increase the robustness of the predictio...
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The present research concerns the numerical dynamical analysis in elasto-acoustics, taking into account the geometrical non-linearities induced by the large displacements/deformations of the structure and assuming the in...
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A feasible, nonparametric, probabilistic approach for quantifying model-form uncertainties associated with a High-Dimensional computational Model (HDM) and/or a corresponding Hyperreduced Projection-based Reduced-Order M...
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À l'heure actuelle, l'atténuation des ondes acoustiques et des vibrations mécaniques en moyennes et hautes fréquences est bien connue et facilement réalisable, en particulier avec des matériaux dissipatifs. Cependant, ce...
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The influence of the track geometry on the dynamic response of the train is of great concern for the railway companies, because they have to guarantee the safety of the train passengers in ensuring the stability of the t...
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The implementation of the experimental methodology by optical measurements of mechanical fields, the development of a test bench, the specimen preparation, the experimental measurements, and the digital image correlation...
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This paper deals with the dynamical analysis and uncertainty quantification of a mistuned industrial rotating integrally bladed disk, for which the operating regime under consideration takes into account the nonlinear ge...
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This paper deals with the dynamical analysis and uncertainty quantification of a mistuned industrial rotating integrally bladed disk, for which the operating regime under consideration takes into account the nonlinear ge...
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The paper presents a complete experimental validation of an advanced computational methodology adapted to the nonlinear post-buckling analysis of geometrically nonlinear structures in presence of uncertainty. A mean nonl...
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In this paper, we present a hybrid method that combines Monte Carlo sampling and spectral methods for solving stochastic coupled problems. After partitioning the stochastic coupled problem into subsidiary subproblems, th...
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The aim of this paper is to analyze the uncertainty quantification in a voice production mechanical model and update the probability density function corresponding to the tension parameter using the bayes method and expe...
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A better understanding of the interaction between the dynamics of high speed trains and the track geometry is needed. As during its lifecycle, the train faces a great variability of track conditions, this dynamic behavio...