Novel Approach to Develop Rheological Structure-Property Relationships Using Genetic Programming

Abstract

Rheological structure-property models play a crucial role in the manufacturing and processing of polymers. Traditionally rheological models are developed by design of experiments that measure a rheological property as a function of the moments of molar mass distributions. These empirical models lack the capacity to apply to a wide range of distributions due the limited availability of experimental data. In recent years fundamental models were developed to satisfy a wider range of distributions, but they are in terms of variables not readily available during processing or manufacturing. Genetic programming can be used to bridge the gap between the practical, but limited, empirical models and the more general, but less practical, fundamental models. This is a novel approach of generating rheological models that are both practical and valid for a wide set of distributions.