Novel correlations for prediction of SARA contents of vacuum residues

Samie, Mohammad Sadegh; Mortaheb, Hamid Reza

doi:10.1016/j.fuel.2021.121609

Cited by 4 publications

(5 citation statements)

References 44 publications

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“…In order to avoid inconsistency in the measured viscosities of the distinct studied VRs, a dilution with 30% fluid catalytic cracking (FCC) heavy cycle oil (HCO) was applied. This method, as shown in the research of Samie and Mortaheb [37], can provide a reliable basis for VR property modeling.…”

Section: Maximal Molecular Weight G/molmentioning

confidence: 90%

“…It was observed from these data that Models 1 and 2 and the data for the MW and SG of the SRVRs outperformed the correlation of Samie and Mortaheb [37], with an average absolute relative error = 20.9% for the new method relative to AARE = 32.6% for the correlation of Samie and Mortaheb [37].…”

Section: Validation Of the Developed Models To Simulate Viscosities A...mentioning

confidence: 91%

“…The inconsistency of the measured viscosities makes data interpretation very difficult. Moreover, Samie and Mortaheb [37] developed correlations to predict VR SARA composition from the VR properties: density, Conradson carbon content, and viscosity, and an incorrect viscosity measurement will lead to an incorrect SARA analysis prediction. In order to avoid inconsistency in the measured viscosities of the distinct studied VRs, a dilution with 30% fluid catalytic cracking (FCC) heavy cycle oil (HCO) was applied.…”

Section: Maximal Molecular Weight G/molmentioning

confidence: 99%

“…Figure 2a presents a graph of agreement between the measured and predicted C 7 -asphaltene content of 40 SRVRs through the use of MW, SG, and Models 1 and 2. For comparison purposes, Figure 2b shows a graph of agreement between the measured and predicted C 7 -asphaltene content of 40 SRVRs using the SRVR data for density, viscosity of blends of 70% SRVR/30% FCC HCO, and Conradson carbon content, and the correlation of Samie and Mortaheb [37].…”

Section: Validation Of the Developed Models To Simulate Viscosities A...mentioning

confidence: 99%

“…In addition to the model of Samie and Mortaheb [37], which predicted C7-asphaltene content with an average absolute relative error of 32.6% and used the density, Conradson carbon content, and viscosity of the primary vacuum residue, the C7-asphaltene…”

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confidence: 99%

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Empirical Modeling of Viscosities and Softening Points of Straight-Run Vacuum Residues from Different Origins and of Hydrocracked Unconverted Vacuum Residues Obtained in Different Conversions

et al. 2022

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The use of hydrocracked and straight-run vacuum residues in the production of road pavement bitumen requires a good understanding of how the viscosity and softening point can be modeled and controlled. Scientific reports on modeling of these rheological properties for hydrocracked and straight-run vacuum residues are scarce. For that reason, 30 straight-run vacuum residues and 33 hydrocracked vacuum residues obtained in a conversion range of 55–93% were investigated, and the characterization data were employed for modeling purposes. An intercriteria analysis was applied to investigate the statistically meaningful relations between the studied vacuum residue properties. It revealed that the straight-run and hydrocracked vacuum residues were completely different, and therefore their viscosity and softening point should be separately modeled. Through the use of nonlinear regression by applying CAS Maple and NLPSolve with the modified Newton iterative method and the vacuum residue bulk properties the viscosity and softening point were modeled. It was found that the straight-run vacuum residue viscosity was best modeled from the molecular weight and specific gravity, whereas the softening point was found to be best modeled from the molecular weight and C7-asphaltene content. The hydrocracked vacuum residue viscosity and softening point were modeled from a single property: the Conradson carbon content. The vacuum residue viscosity models developed in this work were found to allow prediction of the asphaltene content from the molecular weight and specific gravity with an average absolute relative error of 20.9%, which was lower of that of the model of Samie and Mortaheb (Fuel. 2021, 305, 121609)—32.6%.

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Section: Maximal Molecular Weight G/molmentioning

confidence: 90%

Section: Validation Of the Developed Models To Simulate Viscosities A...mentioning

confidence: 91%

Section: Maximal Molecular Weight G/molmentioning

confidence: 99%

Section: Validation Of the Developed Models To Simulate Viscosities A...mentioning

confidence: 99%

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confidence: 99%

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