Asphalt Study by Neuronal Networks. Correlation between Chemical and Rheological Properties

In this paper we investigate the prediction of rheological properties of bitumens using some structural parameters calculated from 13C NMR data. This study was carried out using methods of quantitative structure properties relationships (QSPR) and more particularly neural networks (NN). Such a mathe...

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Bibliographic Details
Published in:Energy & fuels 1997-11, Vol.11 (6), p.1188-1193
Main Authors: Michon, Laurent, Hanquet, Bernard, Diawara, Boubakar, Martin, Didier, Planche, Jean-Pascal
Format: Article
Language:English
Subjects:
Applied sciences
Constitution and properties of crude oils, shale oils, natural gas and bitumens. Analysis and characteristics
Crude oil, natural gas and petroleum products
Energy
Exact sciences and technology
Fuels
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Summary:In this paper we investigate the prediction of rheological properties of bitumens using some structural parameters calculated from 13C NMR data. This study was carried out using methods of quantitative structure properties relationships (QSPR) and more particularly neural networks (NN). Such a mathematical tool can find out non linear relations between descriptors and properties. Two asphalt rheological properties, m (creep slope at low temperature) and G*/sin δ (stiffness at high temperature) were selected, whereas the descriptors are the average molecular parameters which characterize the hydrocarbon skeleton of bitumens. This work permitted to prove that the skeleton information contained in the average molecular parameters could be correlated to the m value but not to the G*/sin δ. Thus, the low-temperature rheological behavior appears to be highly dependent on the aliphatic part of the bitumens.
ISSN:0887-0624
1520-5029
DOI:10.1021/ef9700386