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Open AccessArticle

Uncertainty Propagation through a Point Model for Steady-State Two-Phase Pipe Flow

1
Department of Structural Engineering, Faculty of Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway
2
SINTEF Multiphase Flow Laboratory, 7491 Trondheim, Norway
3
Department of Mathematical Sciences, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway
*
Author to whom correspondence should be addressed.
Algorithms 2020, 13(3), 53; https://doi.org/10.3390/a13030053
Received: 31 January 2020 / Revised: 19 February 2020 / Accepted: 25 February 2020 / Published: 28 February 2020
Uncertainty propagation is used to quantify the uncertainty in model predictions in the presence of uncertain input variables. In this study, we analyze a steady-state point-model for two-phase gas-liquid flow. We present prediction intervals for holdup and pressure drop that are obtained from knowledge of the measurement error in the variables provided to the model. The analysis also uncovers which variables the predictions are most sensitive to. Sensitivity indices and prediction intervals are calculated by two different methods, Monte Carlo and polynomial chaos. The methods give similar prediction intervals, and they agree that the predictions are most sensitive to the pipe diameter and the liquid viscosity. However, the Monte Carlo simulations require fewer model evaluations and less computational time. The model predictions are also compared to experiments while accounting for uncertainty, and the holdup predictions are accurate, but there is bias in the pressure drop estimates. View Full-Text
Keywords: two-phase flow; unit cell; uncertainty quantification; sensitivity analysis; Monte Carlo; polynomial chaos two-phase flow; unit cell; uncertainty quantification; sensitivity analysis; Monte Carlo; polynomial chaos
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MDPI and ACS Style

Strand, A.; Smith, I.E.; Unander, T.E.; Steinsland, I.; Hellevik, L.R. Uncertainty Propagation through a Point Model for Steady-State Two-Phase Pipe Flow. Algorithms 2020, 13, 53. https://doi.org/10.3390/a13030053

AMA Style

Strand A, Smith IE, Unander TE, Steinsland I, Hellevik LR. Uncertainty Propagation through a Point Model for Steady-State Two-Phase Pipe Flow. Algorithms. 2020; 13(3):53. https://doi.org/10.3390/a13030053

Chicago/Turabian Style

Strand, Andreas; Smith, Ivar E.; Unander, Tor E.; Steinsland, Ingelin; Hellevik, Leif R. 2020. "Uncertainty Propagation through a Point Model for Steady-State Two-Phase Pipe Flow" Algorithms 13, no. 3: 53. https://doi.org/10.3390/a13030053

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