Multivariate dependent interval finite element analysis via convex hull pair constructions and the extended transformation method

DOI10.1016/j.cma.2018.12.021zbMath1440.65201OpenAlexW2906634427MaRDI QIDQ1987793

Matthias Faes, David Moens

Publication date: 16 April 2020

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://lirias.kuleuven.be/handle/123456789/630790

zbMATH Keywords

interval analysisimprecise probabilitytransformation methodcopula pair constructionsdependent intervalsnon-probabilistic analysis

Mathematics Subject Classification ID

Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) General methods in interval analysis (65G40)

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Cites Work

• Unnamed Item
• Pair-copula constructions of multiple dependence
• Static response bounds of Timoshenko beams with spatially varying interval uncertainties
• An interdependency index for the outputs of uncertain systems
• Hybrid theoretical, experimental and numerical study of vibration and buckling of composite shells with scatter in elastic moduli
• Derivation of multi-dimensional ellipsoid convex model for experimental data
• Vines -- a new graphical model for dependent random variables.
• The transformation method for the simulation and analysis of systems with uncertain parameters
• A novel interval finite element method based on the improved interval analysis
• Hybrid uncertain static analysis with random and interval fields
• Identification and quantification of multivariate interval uncertainty in finite element models
• Probability density decomposition for conditionally dependent random variables modeled by vines
• Interval fields to represent uncertainty on the output side of a static FE analysis
• Copulas in Machine Learning
• An efficient response surface based optimisation method for non-deterministic harmonic and transient dynamic analysis
• Copula–Based Models for Financial Time Series
• Numerical Optimization
• Maximum likelihood estimation of mixed C-vines with application to exchange rates
• Simulating Copulas

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