Novel approach to develop rheological structure-property relationships using genetic programming

E. Jordaan, C.F.J. Den Doelder, G. Smits

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationParallel Problem Solving from Nature, PPSN IX
Subtitle of host publication9th International Conference, Reykjavik, Iceland, September 9-13, 2006, Proceedings
EditorsT.P. Runarsson, H.-G. Beyer, E. Burke, J.J. Merelo-Guervós, L.D. Whitley, X. Yao
Place of PublicationDordrecht
PublisherSpringer
Pages322-331
Number of pages10
ISBN (Print)978-3-540-38990-3
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event9th International Conference on Parallel Problem Solving from Nature, PPSN IX - Reykjavik, Iceland
Duration: 9 Sep 200613 Sep 2006

Publication series

NameLecture Notes in Computer Science
Volume4193
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Parallel Problem Solving from Nature, PPSN IX
CountryIceland
CityReykjavik
Period9/09/0613/09/06

Keywords

  • Genetic programming
  • Molar mass distribution
  • Rheology

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