Results 281 to 290 of about 44,636 (300)

Efficient Uncertainty Quantification Using Dimension Reduction Technology

AIAA SCITECH 2023 Forum, 2023
Wataru Yamazaki, Kyohei Hanazaki
openaire   +1 more source

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

Mechanical Systems and Signal Processing, 2022
Dominik Hose, Michael Hanss, Peter Eberhard   +2 more
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, Yu-Yen Chen, David S Mebane   +2 more
exaly  

A generalized active subspace for dimension reduction in mixed aleatory-epistemic uncertainty quantification

Computer Methods in Applied Mechanics and Engineering, 2020
Xiong Jiang, Xingzhi Hu, Ruili Wang
exaly  

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

Journal of Mechanical Design, Transactions of the ASME, 2020
Lixiong Cao, C Jiang, Cao Lixiong
exaly  

Dual mixed refrigerant LNG process: Uncertainty quantification and dimensional reduction sensitivity analysis

Applied Energy, 2019
Muhammad Abdul Qyyum, Pham Luu Trung Duong, Le Quang Minh   +2 more
exaly  

A sequential calibration and validation framework for model uncertainty quantification and reduction

Computer Methods in Applied Mechanics and Engineering, 2020
Chen Jiang, Zhen Hu, Jie Liu
exaly  

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

A dimension-reduction metamodeling approach to simulation-based uncertainty quantification problems with high dimensionalities

Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2022
exaly  

Model Order Reduction Methods in Computational Uncertainty Quantification

2015
Peng Chen, Christoph Schwab
openaire   +1 more source