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Title: Predict octane numbers using a generalized interaction method

Abstract

An interaction-based correlation using a new approach can be used to predict research and motor octane numbers of gasoline blends. An ultimately detailed analysis of the gasoline cut is not necessary. This correlation can describe blending behavior over the entire composition range of gasoline cuts. The component-oriented interaction approach is general and will accurately predict, without performing additional blending studies, blending behavior for new gasoline cuts. The proposed correlation fits the data quite closely for blends of many gasoline cuts. The regression gives realistic values for binary interaction parameters between components. A unique set of binary interaction parameters was found for the equation for predicting octane number of any gasoline blend. The binary interaction parameters between components contained in gasoline cuts have been converted to binary interaction parameters between gasoline cuts through a general equation to simplify the calculations. Because of the proposed method`s accuracy, optimum allocation of components among gasoline grades can be obtained and predicted values can be used for quality control of the octane number of marketed gasolines.

Authors:
;  [1]
  1. Simulation Sciences, Inc., Brea, CA (United States)
Publication Date:
OSTI Identifier:
194910
Resource Type:
Journal Article
Journal Name:
Hydrocarbon Processing
Additional Journal Information:
Journal Volume: 75; Journal Issue: 2; Other Information: PBD: Feb 1996
Country of Publication:
United States
Language:
English
Subject:
02 PETROLEUM; GASOLINE; ANTIKNOCK RATINGS; CALCULATION METHODS; MIXTURES; REGRESSION ANALYSIS; EQUATIONS; NUMERICAL DATA

Citation Formats

Twu, C H, and Coon, J E. Predict octane numbers using a generalized interaction method. United States: N. p., 1996. Web.
Twu, C H, & Coon, J E. Predict octane numbers using a generalized interaction method. United States.
Twu, C H, and Coon, J E. 1996. "Predict octane numbers using a generalized interaction method". United States.
@article{osti_194910,
title = {Predict octane numbers using a generalized interaction method},
author = {Twu, C H and Coon, J E},
abstractNote = {An interaction-based correlation using a new approach can be used to predict research and motor octane numbers of gasoline blends. An ultimately detailed analysis of the gasoline cut is not necessary. This correlation can describe blending behavior over the entire composition range of gasoline cuts. The component-oriented interaction approach is general and will accurately predict, without performing additional blending studies, blending behavior for new gasoline cuts. The proposed correlation fits the data quite closely for blends of many gasoline cuts. The regression gives realistic values for binary interaction parameters between components. A unique set of binary interaction parameters was found for the equation for predicting octane number of any gasoline blend. The binary interaction parameters between components contained in gasoline cuts have been converted to binary interaction parameters between gasoline cuts through a general equation to simplify the calculations. Because of the proposed method`s accuracy, optimum allocation of components among gasoline grades can be obtained and predicted values can be used for quality control of the octane number of marketed gasolines.},
doi = {},
url = {https://www.osti.gov/biblio/194910}, journal = {Hydrocarbon Processing},
number = 2,
volume = 75,
place = {United States},
year = {Thu Feb 01 00:00:00 EST 1996},
month = {Thu Feb 01 00:00:00 EST 1996}
}