Global sensitivity analysis using low-rank tensor approximations
In the context of global sensitivity analysis, the Sobol'indices constitute a powerful tool for
assessing the relative significance of the uncertain input parameters of a model. We herein …
assessing the relative significance of the uncertain input parameters of a model. We herein …
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 …
Reliability analysis of high-dimensional models using low-rank tensor approximations
Engineering and applied sciences use models of increasing complexity to simulate the
behavior of manufactured and physical systems. Propagation of uncertainties from the input …
behavior of manufactured and physical systems. Propagation of uncertainties from the input …
Neural networks for computing best rank-one approximations of tensors and its applications
This paper presents the neural dynamical network to compute a best rank-one
approximation of a real-valued tensor. We implement the neural network model by the …
approximation of a real-valued tensor. We implement the neural network model by the …
Efficient design of experiments for sensitivity analysis based on polynomial chaos expansions
Global sensitivity analysis aims at quantifying respective effects of input random variables
(or combinations thereof) onto variance of a physical or mathematical model response …
(or combinations thereof) onto variance of a physical or mathematical model response …
Stochastic dosimetry based on low rank tensor approximations for the assessment of children exposure to WLAN source
In this study, the exposure of a female eight-year old child to a WLAN access point located in
an unknown position in a realistic indoor environment was investigated. A stochastic …
an unknown position in a realistic indoor environment was investigated. A stochastic …
Low-rank approximation of local strain in two-phase composites
This study presents the development of a computationally efficient mathematical framework
for predicting the meso-scale (local) strain field for two-phase composites under mechanical …
for predicting the meso-scale (local) strain field for two-phase composites under mechanical …
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 …
GAS: Generating Fast and Accurate Surrogate Models for Autonomous Vehicle Systems
Modern autonomous vehicle systems use complex perception and control components.
These components can rapidly change during development of such systems, requiring …
These components can rapidly change during development of such systems, requiring …
Children exposure to femtocell in indoor environments estimated by sparse low-rank tensor approximations
The exposure of an 8-year-old child to a femtocell operating at 2600 MHz, both (child and
source) freely located in random positions in an indoor environment, was assessed. In order …
source) freely located in random positions in an indoor environment, was assessed. In order …