LAPSE:2023.15001v1
Published Article
LAPSE:2023.15001v1
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
March 2, 2023
Abstract
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%.
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%.
Record ID
Keywords
asphaltenes, empirical modeling, hydrocracked vacuum residue, intercriteria analysis, softening point, vacuum residue, viscosity
Subject
Suggested Citation
Stratiev D, Nenov S, Nedanovski D, Shishkova I, Dinkov R, Stratiev DD, Stratiev DD, Sotirov S, Sotirova E, Atanassova V, Ribagin S, Atanassov K, Yordanov D, Angelova NA, Todorova-Yankova L. 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. (2023). LAPSE:2023.15001v1
Author Affiliations
Stratiev D: LUKOIL Neftohim Burgas, 8104 Burgas, Bulgaria [ORCID]
Nenov S: Department of Mathematics, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Nedanovski D: Faculty of Mathematics and Informatics, University “St. Kliment Ohridski”, 15 Tsar Osvoboditel Blvd., 1504 Sofia, Bulgaria
Shishkova I: LUKOIL Neftohim Burgas, 8104 Burgas, Bulgaria [ORCID]
Dinkov R: LUKOIL Neftohim Burgas, 8104 Burgas, Bulgaria
Stratiev DD: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Academic GeorgiBonchev 105, 1113 Sofia, Bulgaria
Stratiev DD: Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Sotirov S: Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Sotirova E: Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Atanassova V: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Academic GeorgiBonchev 105, 1113 Sofia, Bulgaria [ORCID]
Ribagin S: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Academic GeorgiBonchev 105, 1113 Sofia, Bulgaria; Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and M
Atanassov K: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Academic GeorgiBonchev 105, 1113 Sofia, Bulgaria; Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and M
Yordanov D: Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Angelova NA: Faculty of Mathematics and Informatics, University “St. Kliment Ohridski”, 15 Tsar Osvoboditel Blvd., 1504 Sofia, Bulgaria [ORCID]
Todorova-Yankova L: Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Nenov S: Department of Mathematics, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Nedanovski D: Faculty of Mathematics and Informatics, University “St. Kliment Ohridski”, 15 Tsar Osvoboditel Blvd., 1504 Sofia, Bulgaria
Shishkova I: LUKOIL Neftohim Burgas, 8104 Burgas, Bulgaria [ORCID]
Dinkov R: LUKOIL Neftohim Burgas, 8104 Burgas, Bulgaria
Stratiev DD: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Academic GeorgiBonchev 105, 1113 Sofia, Bulgaria
Stratiev DD: Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Sotirov S: Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Sotirova E: Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Atanassova V: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Academic GeorgiBonchev 105, 1113 Sofia, Bulgaria [ORCID]
Ribagin S: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Academic GeorgiBonchev 105, 1113 Sofia, Bulgaria; Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and M
Atanassov K: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Academic GeorgiBonchev 105, 1113 Sofia, Bulgaria; Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and M
Yordanov D: Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Angelova NA: Faculty of Mathematics and Informatics, University “St. Kliment Ohridski”, 15 Tsar Osvoboditel Blvd., 1504 Sofia, Bulgaria [ORCID]
Todorova-Yankova L: Intelligent Systems Laboratory, Department Industrial Technologies and Management, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Journal Name
Energies
Volume
15
Issue
5
First Page
1755
Year
2022
Publication Date
2022-02-26
ISSN
1996-1073
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PII: en15051755, Publication Type: Journal Article
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LAPSE:2023.15001v1
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