Results 131 to 140 of about 44,636 (300)
Stochastic Dimension Reduction Techniques for Uncertainty Quantification of Multiphysics Systems
, 2012 Uncertainty quantification of multiphysics systems represents numerous mathematical and computational challenges. Indeed, uncertainties that arise in each physics in a fully coupled system must be captured throughout the whole system, the so-called curse
Ghanem, Roger +4 more
core
Arthritis Care &Research, EarlyView.Objective To investigate the association between rheumatoid arthritis (RA) and coronary artery calcium (CAC) prevalence, incidence, and progression over four years in adults without prior cardiovascular disease. Methods A case‐cohort study within the Brazilian Longitudinal Study of Adult Health (ELSA‐Brasil) included 585 participants (86 patients with ...
Patrícia Fonseca Estrada +7 more
wiley +1 more source
LandWith the intensification of global climate change, the frequent occurrence of typhoon disaster events has become a great challenge to the sustainable development of cities around the world; thus, it is of great significance to carry out the assessment of
Siyi Zhou +4 more
doaj +1 more source
Dimensionality Reduction and Uncertainty Quantification for Inverse Problems
, 2015 Many inverse problems in science and engineering involve multi-experiment data and thus require a large number of forward simulations. Dimensionality reduction techniques aim at reducing the number of forward solves by (randomly) subsampling the data. In the special case of non-linear least-squares estimation, we can interpret this compression of the ...
openaire +1 more source
Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
International Journal of Adaptive Control and Signal Processing, EarlyView.This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
Quantification and reduction of the uncertainty in mass balance models by Monte Carlo analysis of prior data [PDF]
, 1991 The general objective of this workshop is to investigate and discuss methods by which uncertainties in mass balance models for toxics in the Great Lakes may be reduced.
Lesht, B. M., Lesht, B.M.
core
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
EnergiesThis study introduces an adaptive robust approach for optimally sizing hybrid renewable energy systems (HRESs) comprising solar panels, wind turbines, batteries, and a diesel generator.
Ali Keyvandarian +2 more
doaj +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Multiscale Methods and Uncertainty Quantification
, 2015 In this thesis we consider two great challenges in computer simulations of partial differential equations: multiscale data, varying over multiple scales in space and time, and data uncertainty, due to lack of or inexact measurements.
Elfverson, Daniel, Daniel Elfverson
core