Literature DB >> 9860903

Modeling the chemistry of complex petroleum mixtures.

R J Quann1.   

Abstract

Determining the complete molecular composition of petroleum and its refined products is not feasible with current analytical techniques because of the astronomical number of molecular components. Modeling the composition and behavior of such complex mixtures in refinery processes has accordingly evolved along a simplifying concept called lumping. Lumping reduces the complexity of the problem to a manageable form by grouping the entire set of molecular components into a handful of lumps. This traditional approach does not have a molecular basis and therefore excludes important aspects of process chemistry and molecular property fundamentals from the model's formulation. A new approach called structure-oriented lumping has been developed to model the composition and chemistry of complex mixtures at a molecular level. The central concept is to represent an individual molecular or a set of closely related isomers as a mathematical construct of certain specific and repeating structural groups. A complex mixture such as petroleum can then be represented as thousands of distinct molecular components, each having a mathematical identity. This enables the automated construction of large complex reaction networks with tens of thousands of specific reactions for simulating the chemistry of complex mixtures. Further, the method provides a convenient framework for incorporating molecular physical property correlations, existing group contribution methods, molecular thermodynamic properties, and the structure--activity relationships of chemical kinetics in the development of models.

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Year:  1998        PMID: 9860903      PMCID: PMC1533469          DOI: 10.1289/ehp.98106s61441

Source DB:  PubMed          Journal:  Environ Health Perspect        ISSN: 0091-6765            Impact factor:   9.031


  5 in total

1.  Grouping of Petroleum Substances as Example UVCBs by Ion Mobility-Mass Spectrometry to Enable Chemical Composition-Based Read-Across.

Authors:  Fabian A Grimm; William K Russell; Yu-Syuan Luo; Yasuhiro Iwata; Weihsueh A Chiu; Tim Roy; Peter J Boogaard; Hans B Ketelslegers; Ivan Rusyn
Journal:  Environ Sci Technol       Date:  2017-05-26       Impact factor: 9.028

2.  A Predictive Approach towards Using PC-SAFT for Modeling the Properties of Shale Oil.

Authors:  Parsa Mozaffari; Zachariah Steven Baird; Oliver Järvik
Journal:  Materials (Basel)       Date:  2022-06-14       Impact factor: 3.748

Review 3.  Approaches to developing alternative and predictive toxicology based on PBPK/PD and QSAR modeling.

Authors:  R S Yang; R S Thomas; D L Gustafson; J Campain; S A Benjamin; H J Verhaar; M M Mumtaz
Journal:  Environ Health Perspect       Date:  1998-12       Impact factor: 9.031

Review 4.  Advances in the field of high-molecular-weight polycyclic aromatic hydrocarbon biodegradation by bacteria.

Authors:  Robert A Kanaly; Shigeaki Harayama
Journal:  Microb Biotechnol       Date:  2009-06-22       Impact factor: 5.813

5.  Application of the Target Lipid Model to Assess Toxicity of Heterocyclic Aromatic Compounds to Aquatic Organisms.

Authors:  Joy McGrath; Gordon Getzinger; Aaron D Redman; Melanie Edwards; Alberto Martin Aparicio; Eleni Vaiopoulou
Journal:  Environ Toxicol Chem       Date:  2021-09-21       Impact factor: 4.218

  5 in total

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