A KNOWLEDGE-BASED EXPERT SYSTEM FOR THE PREDICTION OF TERNARY AZEOTROPE FORMATION IN ORGANIC MIXTURES : (Knowledge-based Prediction of Ternary Azeotrope Formation)

다국어 초록 (Multilingual Abstract)

New functions of AZEOPERT [Kim and Simmrock, 1997] were investigated to predict the occurrence of ternary azeotropes and their azeotropic compositions in an organic mixture and its new problem-solving strategy is described in this study. The knowledge base of AZEOPERT for ternary azeotropes is hierarchically structured with the several levels of domain-specific knowledge on ternary azeotropy. First of all, the azeotropic data bank including ternary azeotropic experimentl data was implemented in AZEOPERT as the lowest level. It may be used in order to determine whether or not ternary azeotropic experimental data for the consulted organic mixture is already available. Moreover, compiled heuristic knowledge as the second level and class-oriented model-based knowledge as the highest level were implemented in the knowlege base. The problem-solving strategy through the integration of model-based reasoning into compiled reasoning gives a very efficient, general wqy for the prediction of ternary azeotrope formation in a wide varitey of organic mixtures, and especially, in unknown mixture systems.

목차 (Table of Contents)

• Abstract
• 1.Introducion
• 2.Thenary Azeotropy
• 3.The Prediction of Ternary Azeotrope pormation
• 4.Conclusions
• References