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- W2978166591 abstract "We propose a reliable prediction model for the application of the heat transfer coefficient of CO₂ mixture for the design of the pipeline in CCS (Carbon Capture, Transportation & Storage) technology. Accordingly, three prediction models; the Gnielinski model, the Dittus-Boelter model, and the Churchill-Bernstein model were compared with the experimental data obtained in the previous study. The prediction models showed that the heat transfer characteristics of CO₂ mixtures were relatively well predicted with the various parameters like type of the impurities, the mole fraction of the impurity, operational pressure, and mass flux. However, all the prediction models underestimated heat transfer coefficient near the pseudo-critical temperature. The Gnielinski model showed the highest predictive ability compared to other prediction models with a mean deviation of 12.63%, but it slightly overestimated the data under pseudo-critical temperature. The Dittus-Boelter model and the Churchill-Bernstein model predicted experimental data by 16.94% and 17.82%, respectively." @default.
- W2978166591 created "2019-10-10" @default.
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- W2978166591 date "2018-09-30" @default.
- W2978166591 modified "2023-09-25" @default.
- W2978166591 title "Evaluation of Prediction Models for In-Tube Heat Transfer Coefficient of Supercritical CO₂ with Impurities" @default.
- W2978166591 doi "https://doi.org/10.6110/kjacr.2018.30.9.435" @default.
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