Correlation of chemical constitution and boiling point with separation behaviour during distillation of coal liquid

Yokayama, Susumu; Uchino, Hiroyuki; Tanabe, K.; Satou, Masaaki; Sanada, Yuzo

doi:10.1016/0016-2361(87)90178-5

Cited by 5 publications

(1 citation statement)

References 4 publications

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“…Difficulties also arise when the modelers face inconsistent information obtained from different analytical techniques. For instance, the distillation curves derived from gas chromatography-mass spectrometry (GC-MS) analyses differed substantially from the simulated distillations directly measured by the gas chromatography-flame ionization detector (GC-FID) D2887 (ASTM International, West Conshohocken, Pennsylvania) method (Yokayama et al, 1987). Such information has to be reconciled before being used for the development of complex models.…”

Section: Introductionmentioning

confidence: 99%

Data Reconciliation Among PIONA, GC-FIMS, and SimDis Measurements for Petroleum Fractions

Ha¹,

Ring

Liu

2008

Petroleum Science and Technology

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PIONA (paraffin, isoparaffin, olefin, naphthene, aromatic) is a widely used characterization method for petroleum fractions boiling below 200 ı C, while a gas chromatography-field ionization mass spectrometry (GC-FIMS) characterization method developed at the National Centre for Upgrading Technology (NCUT) provides a reliable hydrocarbon type distribution by carbon number (#C) for middle distillates boiling between 200 ı C-360 ı C. This article proposes an integrated approach to combine the results from both PIONA and GC-FIMS measurements, resulting in detailed hydrocarbon-type distribution between the initial and end boiling points of the middle distillate. Furthermore, summing up the mass in each boiling point (BP) interval (e.g., 10 ı C) generates an equivalent simulated distillation (SimDis) curve that needs to be reconciled with the SimDis measured by the ASTM D2887 method. This article also discusses a simple data reconciliation approach that allowed us to use the three separate pieces of information (PIONA, GC-FIMS, and SimDis) as an internally consistent basis for the derivation of molecular representation of materials characterized in such a way.

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Section: Introductionmentioning

confidence: 99%