Results 231 to 240 of about 252,868 (269)

Uncertainty reduction and quantification in computational thermodynamics

Computational Materials Science, 2022
Richard A Otis
exaly   +2 more sources

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

Computer Methods in Applied Mechanics and Engineering, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chen Jiang, Zhen Hu, Jie Liu
exaly   +3 more sources

Validation, Uncertainty Quantification and Uncertainty Reduction for a Shock Tube Simulation

18th AIAA Non-Deterministic Approaches Conference, 2016
While we rely on simulations to predict the response of complex systems, we recognize that the models that underlie these simulations are never perfect. Comparison of simulations with experiments is an important tool for exposing limitations of models, and providing insights into which models need improvement.
Chanyoung Park, M Giselle Fernandez-Godino, Nam Ho Kim, Raphael T. Haftka   +3 more
openaire   +1 more source

Microstructure model reduction and uncertainty quantification in multiscale deformation processes

Computational Materials Science, 2010
The quantification and propagation of uncertainty in multiscale deformation processes is considered. A reduced-order model for representing the data-driven stochastic microstructure input is presented. The multiscale random field representing the random microstructure is decomposed into few modes in different scales (the Rodrigues space for ...
Nicholas Zabaras
exaly   +2 more sources

FAST AND ACCURATE MODEL REDUCTION FOR SPECTRAL METHODS IN UNCERTAINTY QUANTIFICATION

International Journal for Uncertainty Quantification, 2016
Roland Pulch, Joost Rommes
exaly   +2 more sources

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

Applied Energy, 2019
Abstract The dual mixed refrigerant (DMR) liquefaction process is complicated and sensitive compared to the competitive propane pre-cooled mixed refrigerant liquefied natural gas (LNG) process. When any uncertainty is introduced to the process operation conditions, it is necessary for the DMR process to be re-optimized to maintain efficient operation
Muhammad Abdul Qyyum, Moonyong Lee
exaly   +2 more sources

Model Reduction and Interpolation Methods in Uncertainty Quantification

SEG Technical Program Expanded Abstracts 2012, 2012
To properly answer these questions, one must characterize and quantify the uncertainties inherent in the model and its predictions. The last decade has seen the emergence and growth of methods and procedures for uncertainty quantification for computer simulations.
openaire   +1 more source

Programming with equadratures: an open-source package for uncertainty quantification, dimension reduction, and optimisation

AIAA SCITECH 2022 Forum, 2022
This paper presents an overview of the open-source code equadratures. While originally developed to replicate polynomial chaos results seen in literature, it has since evolved to touch upon multiple aspects of computational engineering and machine learning.
Seshadri P., Wong C. Y., Scillitoe A., Ubald B. N., Hill B., Virdis I., Ghisu T., Duncan A. B.   +7 more
openaire   +1 more source

Uncertainty quantification and reduction in aircraft trajectory prediction using Bayesian-Entropy information fusion

Reliability Engineering & System Safety, 2021
Abstract Eliminating accidents while maintaining the integrity of the National Airspace System is one of the central objectives of the Next Generation Air Transportation System. This paper presents a Bayesian framework for accurate trajectory and accident prediction in National Airspace System using a high-fidelity trajectory simulation platform ...
Yuhao Wang, Yutian Pang, Oliver Chen, Hari N. Iyer, Parikshit Dutta, P.K. Menon, Yongming Liu   +6 more
openaire   +1 more source