A statistical method for evaluation of the experimental phase equilibrium data of simple clathrate hydrates

Ali Eslamimanesh, Farhad Gharagheizi, Amir H. Mohammadi, Dominique Richon

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

We, herein, present a statistical method for diagnostics of the outliers in phase equilibrium data (dissociation data) of simple clathrate hydrates. The applied algorithm is performed on the basis of the Leverage mathematical approach, in which the statistical Hat matrix, Williams Plot, and the residuals of a selected correlation results lead to define the probable outliers. This method not only contributes to outliers diagnostics but also identifies the range of applicability of the applied model and quality of the existing experimental data. The available correlation in the literature in exponential form is used to represent/predict the hydrate dissociation pressures for three-phase equilibrium conditions (liquid water/ice–vapor-hydrate). The investigated hydrate formers are methane, ethane, propane, carbon dioxide, nitrogen, and hydrogen sulfide. It is interpreted from the obtained results that the applied correlation for calculation/estimation of the phase behavior of simple clathrate hydrate systems is statistically valid and correct, 5 hydrate dissociation data are found to be probable doubtful ones and 10 data points are out of applicability domain of the applied correlation.
Original languageEnglish
JournalChemical Engineering Science
Volume80
Pages (from-to)402-408
ISSN0009-2509
DOIs
Publication statusPublished - 2012

Bibliographical note

Highlights:
- Leverage method is applied for evaluation of experimental phase equilibrium data.
- Experimental phase equilibrium data of various simple clathrate hydrates are studied.
- 5 hydrate dissociation data are found to be probable doubtful ones.
- 10 data points are designated as out of applicability domain of the correlation.

Keywords

  • Evaluation of data
  • Gas hydrate
  • Leverage approach
  • Hat matrix
  • Williams plot
  • Outlier diagnostics

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