Details of Grant 

EPSRC Reference:	GR/L07727/01
Title:	ARTIFICIAL NEURAL NETWORKS FOR THE THEORY AND PREDICTION OF TRANSPORT PROPERTIES
Principal Investigator:	Homer, Professor J
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Department:	Chemical Engineering & App Chem
Organisation:	Aston University
Scheme:	Standard Research (Pre-FEC)
Starts:	07 October 1996	Ends:	06 October 1999	Value (£):	144,573
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Summary on Grant Application Form
The aim of this project is to derive a comprehensive theory of viscosity. Initially for pure liquids then, most importantly, for liquid mixtures. It is proposed that the artificial neural networks (ANN) will be used in analytical mode to enable the identification of those macroscopic properties of liquid materials that allow ANN to accurately characterise viscocity. The hierarchy of dependencies of viscosity on the macroscopic properties will be established. A similar strategy will be adopted for the investigation of mixtures of liquids. The mixing rules will be established that permit the incorporation of the properties of pure compounds in the characterisaton of viscosities of mixtures. Having identified those macroscopic properties that are essential to the ANN characterisation of viscosity, and the hierarchical importance of these, they will be analysed to reveal the molecular parameters, and features of the structures of liquids, that govern viscosity. This information will be used as the base for the derivation of a new theory of viscosity. Preliminary computer software, that has been generated during a EPSRC ROPA supported 12 month feasibility study of the subject will be further developed. In so doing, user-friendly software will be produced that will enable other workers both to predict viscosities and enable the ANN indentification of fundamental parameters that are essential to the characterisation of other macroscopic properties of matter.
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Organisation Website:	http://www.aston.ac.uk