Results 241 to 250 of about 252,868 (269)

Uncertainty Quantification and Reduction in the Structural Analysis of Existing Concrete Gravity Dams

2020
The failure of a large gravity dam might have catastrophic effects putting at risk human lives, not counting the considerable economic consequences. Most of dams are located in natural hazard prone areas so the structural control and the evaluation of the dam fragility (in particular against to flood and earthquake) assume great importance both to ...
Anna De Falco, Giacomo Sevieri, Giovanni Marmo   +2 more
openaire   +1 more source

Uncertainty quantification in Bayesian inverse problems with model and data dimension reduction

GEOPHYSICS, 2019
The prediction of rock properties in the subsurface from geophysical data generally requires the solution of a mathematical inverse problem. Because of the large size of geophysical (seismic) data sets and subsurface models, it is common to reduce the dimension of the problem by applying dimension reduction methods and considering a reparameterization
Dario Grana, Leandro Passos de Figueiredo, Leonardo Azevedo   +2 more
openaire   +1 more source

DIMENSION REDUCTION, OPERATOR LEARNING AND UNCERTAINTY QUANTIFICATION FOR PROBLEMS OF DIFFERENTIAL EQUATIONS

2022
In this work, we mainly focus on the topic related to dimension reduction, operator learning and uncertainty quantification for problems of differential equations. The supervised machine learning methods introduced here belong to a newly booming field compared to traditional numerical methods.
openaire   +1 more source

Evidence-Based Structural Uncertainty Quantification by Dimension Reduction Decomposition and Marginal Interval Analysis

Journal of Mechanical Design, 2019
Abstract Evidence theory has the powerful feature to quantify epistemic uncertainty. However, the huge computational cost has become the main obstacle of evidence theory on engineering applications. In this paper, an efficient uncertainty quantification (UQ) method based on dimension reduction decomposition is proposed to improve the ...
Zheng Zhang, Zhantao Wu, Chao Jiang, Jie Liu, Lixiong Cao   +4 more
openaire   +1 more source

Uncertainty Quantification and Uncertainty Reduction Techniques for Large-scale Simulations

2014
Ph. D.
openaire   +1 more source

Efficient Uncertainty Quantification and History Matching of Large-Scale Fields Through Model Reduction

2017
Uncertainty quantification (UQ) and history matching (HM) have become a regular routine for reservoir management and decision-making in petroleum industry. The zonation method was widely used to reparametrize correlated fields with one lumped constant or multiplier specified for each zone such that the dimensionality of problems can be reduced and the ...
Jianlin Fu, Xian-Huan Wen, Song Du
openaire   +1 more source

Development, uncertainty quantification, and reduction of a dimethyl sulfide oxidation mechanism

Dimethyl sulfide (DMS), arising from phytoplankton, is the largest natural source of sulfur in the atmosphere. The oxidation products of DMS, such as methanesulfonic acid and sulfuric acid, can contribute to cloud condensation nuclei. Studying the oxidation mechanism of DMS will help improve our modelling of the natural processes that contribute to the
openaire   +1 more source

Recent advances in nonlinear model reduction for design and associated uncertainty quantification

2016
This lecture will be organized in two complementary parts focused on advances in the construction of parametric, nonlinear, projection-based, reduced-order models that are suitable for design and design optimization, and a corresponding nonparametric probabilistic method for quantifying their uncertainties.
Farhat, Charbel, Washabaugh, K, Chapman, T., Soize, Christian   +3 more
openaire   +1 more source

Uncertainty quantification of large-scale dynamical systems using parametric model order reduction

Mechanical Systems and Signal Processing, 2022
Dominik Hose, Peter Eberhard
exaly  

Kinetic model development and Bayesian uncertainty quantification for the complete reduction of Fe-based oxygen carriers with CH4, CO, and H2 for chemical looping combustion

Chemical Engineering Science, 2022
Anca Ostace, David S Mebane, Andrew Lee
exaly