Polynomial meta-models with canonical low-rank approximations: Numerical insights and comparison to sparse polynomial chaos expansions
The growing need for uncertainty analysis of complex computational models has led to an
expanding use of meta-models across engineering and sciences. The efficiency of meta …
expanding use of meta-models across engineering and sciences. The efficiency of meta …
A Review of Recent Advances in Surrogate Models for Uncertainty Quantification of High-Dimensional Engineering Applications
Z Azarhoosh, MI Ghazaan - Computer Methods in Applied Mechanics and …, 2025 - Elsevier
In fields where predictions may have vital consequences, uncertainty quantification (UQ)
plays a crucial role, as it enables more accurate forecasts and mitigates the potential risks …
plays a crucial role, as it enables more accurate forecasts and mitigates the potential risks …
Numerical investigations into the value of information in lifecycle analysis of structural systems
Preposterior analysis can be used to assess the potential of an experiment to enhance
decision-making by providing information on parameters of the decision problem that are …
decision-making by providing information on parameters of the decision problem that are …
Multi-Fidelity Low-Rank Approximations for Uncertainty Quantification of a Supersonic Aircraft Design
Uncertainty quantification has proven to be an indispensable study for enhancing reliability
and robustness of engineering systems in the early design phase. Single and multi-fidelity …
and robustness of engineering systems in the early design phase. Single and multi-fidelity …
Tensor algorithms for advanced sensitivity metrics
R Ballester-Ripoll, EG Paredes, R Pajarola - SIAM/ASA Journal on …, 2018 - SIAM
Following up on the success of the analysis of variance (ANOVA) decomposition and the
Sobol indices (SI) for global sensitivity analysis, various related quantities of interest have …
Sobol indices (SI) for global sensitivity analysis, various related quantities of interest have …
[PDF][PDF] Low-rank tensor approximations versus polynomial chaos expansions for meta-modeling in high-dimensional spaces
Meta-models developed with low-rank tensor approximations are investigated for
propagating uncertainty through computational models with high-dimensional input. Of …
propagating uncertainty through computational models with high-dimensional input. Of …
[PDF][PDF] Développement de méthodes fiabilistes dépendant du temps pour l'analyse de durabilité des structures
JD SØRENSEN, Y LI, M CHEVREUIL - researchgate.net
In the last few decades, the civil engineering field witnessed a remarkable progress in
conception strategies and the industrial techniques. This allowed to carry out ingenious and …
conception strategies and the industrial techniques. This allowed to carry out ingenious and …
Tensor Approximation of Advanced Metrics for Sensitivity Analysis
R Ballester-Ripoll, EG Paredes, R Pajarola - arXiv preprint arXiv …, 2017 - arxiv.org
Following up on the success of the analysis of variance (ANOVA) decomposition and the
Sobol indices (SI) for global sensitivity analysis, various related quantities of interest have …
Sobol indices (SI) for global sensitivity analysis, various related quantities of interest have …
[图书][B] Stochastic Methods for Emulation, Calibration and Reliability Analysis of Engineering Models
AG Inigo - 2018 - search.proquest.com
This dissertation examines the use of non-parametric Bayesian methods and advanced
Monte Carlo algorithms for the emulation and reliability analysis of complex engineering …
Monte Carlo algorithms for the emulation and reliability analysis of complex engineering …
Tensor methods for high-dimensional analysis and visualization
R Ballester-Ripoll - 2017 - zora.uzh.ch
Most visual computing domains are witnessing a steady growth in sheer data set size,
complexity, and dimensionality. Flexible and scalable mathematical models that can …
complexity, and dimensionality. Flexible and scalable mathematical models that can …