Готові списки джерел за темами / UQ forward analyses

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Добірка наукової літератури з теми "UQ forward analyses"

Автор: Grafiati
Опубліковано: 11 березня 2023

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Статті в журналах з теми "UQ forward analyses"

1

Bulthuis, Kevin, and Eric Larour. "Implementation of a Gaussian Markov random field sampler for forward uncertainty quantification in the Ice-sheet and Sea-level System Model v4.19." Geoscientific Model Development 15, no. 3 (2022): 1195–217. http://dx.doi.org/10.5194/gmd-15-1195-2022.

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Анотація:
Abstract. Assessing the impact of uncertainties in ice-sheet models is a major and challenging issue that needs to be faced by the ice-sheet community to provide more robust and reliable model-based projections of ice-sheet mass balance. In recent years, uncertainty quantification (UQ) has been increasingly used to characterize and explore uncertainty in ice-sheet models and improve the robustness of their projections. A typical UQ analysis first involves the (probabilistic) characterization of the sources of uncertainty, followed by the propagation and sensitivity analysis of these sources of
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2

Yuan, Ye, Douglas Thomson, and David Anderson. "Aerodynamic Uncertainty Quantification for Tiltrotor Aircraft." Aerospace 9, no. 5 (2022): 271. http://dx.doi.org/10.3390/aerospace9050271.

Повний текст джерела
Анотація:
The tiltrotor has unique flight dynamics due to the aerodynamic interference characteristics. Multiple aerodynamics calculation approaches, such as the CFD method, are utilised to characterise this feature. The calculation process is usually time-consuming, and the obtained results are generally varied from each other. Thus, the uncertainty quantification (UQ) method will be utilised in this research to identify the aerodynamic inaccuracy effect on the handling qualities of the tiltrotor aircraft. The study aims to quantify the influence of the aerodynamic interference on the tiltrotor flight
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3

Wang, Ziqi, and Marco Broccardo. "A novel active learning-based Gaussian process metamodelling strategy for estimating the full probability distribution in forward UQ analysis." Structural Safety 84 (May 2020): 101937. http://dx.doi.org/10.1016/j.strusafe.2020.101937.

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4

Lazarus, Alan, David Dalton, Dirk Husmeier, and Hao Gao. "Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics." Biomechanics and Modeling in Mechanobiology, April 4, 2022. http://dx.doi.org/10.1007/s10237-022-01571-8.

Повний текст джерела
Анотація:
AbstractPersonalized computational cardiac models are considered to be a unique and powerful tool in modern cardiology, integrating the knowledge of physiology, pathology and fundamental laws of mechanics in one framework. They have the potential to improve risk prediction in cardiac patients and assist in the development of new treatments. However, in order to use these models for clinical decision support, it is important that both the impact of model parameter perturbations on the predicted quantities of interest as well as the uncertainty of parameter estimation are properly quantified, wh
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5

Yousefian, Sajjad, Gilles Bourque, and Rory F. D. Monaghan. "Uncertainty Quantification of NOx Emission Due to Operating Conditions and Chemical Kinetic Parameters in a Premixed Burner." Journal of Engineering for Gas Turbines and Power 140, no. 12 (2018). http://dx.doi.org/10.1115/1.4040897.

Повний текст джерела
Анотація:
Many sources of uncertainty exist when emissions are modeled for a gas turbine combustion system. They originate from uncertain inputs, boundary conditions, calibration, or lack of sufficient fidelity in a model. In this paper, a nonintrusive polynomial chaos expansion (NIPCE) method is coupled with a chemical reactor network (CRN) model using Python to quantify uncertainties of NOx emission in a premixed burner. The first objective of uncertainty quantification (UQ) in this study is development of a global sensitivity analysis method based on the NIPCE method to capture aleatory uncertainty o
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6

Hao, Mingyang, Bo Bai, Yuanyuan Li, Zhigang Li, and Jun Li. "Uncertainty Quantification on the Cooling Performance of a Transonic Turbine Vane with Upstream Endwall Misalignment." Journal of Turbomachinery, August 17, 2022, 1–24. http://dx.doi.org/10.1115/1.4055269.

Повний текст джерела
Анотація:
Abstract With increasing aerodynamic and thermal loads, film cooling has been a popular technology integrated into the design of the modern gas turbine vane endwall, especially for the first-stage vane endwall. A staggering amount of research has been completed to quantify the effect of operating conditions and cooling hole geometrical properties. However, most of these investigations did not address the influence of the manufacturing tolerances, assembly errors and operation degradations on the endwall misalignment. In this paper, uncertainty quantification (UQ) analysis was performed to quan
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Дисертації з теми "UQ forward analyses"

1

Nardin, Chiara. "Seismic experimental analyses and surrogate models of multi-component systems in special-risk industrial facilities." Doctoral thesis, Università degli studi di Trento, 2022. https://hdl.handle.net/11572/362462.

Повний текст джерела
Анотація:
Nowadays, earthquakes are one of the most catastrophic natural events that have a significant human, socio-economic and environmental impact. Besides, based on both observations of damage following recent major/moderate seismic events and numerical/experimental studies, it clearly emerges that critical non-structural components (NSCs) that are ubiquitous to most industrial facilities are particularly and even disproportionately vulnerable to those events. Nonetheless and despite their great importance, seismic provisions for industrial facilities and their process equipment are still based on
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Тези доповідей конференцій з теми "UQ forward analyses"

1

Yousefian, Sajjad, Gilles Bourque, and Rory F. D. Monaghan. "Uncertainty Quantification of NOx Emission due to Operating Conditions and Chemical Kinetic Parameters in a Premixed Burner." In ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/gt2018-75337.

Повний текст джерела
Анотація:
Many sources of uncertainty exist when emissions are modelled for a gas turbine combustion system. They originate from uncertain inputs, boundary conditions, calibration, or lack of sufficient fidelity in the model. In this paper, a non-intrusive polynomial chaos expansion (NIPCE) method is coupled with a chemical reactor network (CRN) model using Python to rigorously quantify uncertainties of NOx emission in a premixed burner. The first objective of the uncertainty quantification (UQ) in this study is development of a global sensitivity analysis method based on NIPCE to capture aleatory uncer
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Hao, Mingyang, Yuanyuan Li, Zhigang Li, and Jun Li. "Uncertainty Quantification on the Cooling Performance of a Transonic Turbine Vane With Upstream Endwall Misalignment." In ASME Turbo Expo 2022: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/gt2022-82555.

Повний текст джерела
Анотація:
Abstract With increasing aerodynamic and thermal loads, film cooling has been a popular technology integrated into the design of the modern gas turbine vane endwall, especially for the first-stage vane endwall. A staggering amount of research has been completed to quantify the effect of operating conditions and cooling hole geometrical properties. However, most of these investigations did not address the influence of the manufacturing tolerances, assembly errors and operation degradations on the endwall misalignment. In this paper, therefore, uncertainty quantification (UQ) analysis was perfor
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3

Ndiaye, A., M. Bauerheim, S. Moreau, and F. Nicoud. "Uncertainty Quantification of Thermoacoustic Instabilities in a Swirled Stabilized Combustor." In ASME Turbo Expo 2015: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/gt2015-44133.

Повний текст джерела
Анотація:
Combustion instabilities can develop in modern gas-turbines as large amplitude pressure oscillations coupled with heat release fluctuations. In extreme cases, they lead to irreversible damage which can destroy the combustor. Prediction and control of all acoustic modes of the configuration at the design stage are therefore required to avoid these instabilities. This is a challenging task because of the large number of parameters involved. This situation becomes even more complex when considering uncertainties of the underlying models and input parameters. The forward uncertainty quantification
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