An Adaptive Neuro-Fuzzy Inference System for Modeling Mechanical Properties of Tapioca Starch-Poly(Lactic Acid) Nanocomposite Foams

Authors

Siew-Yoong Lee, University of Nebraska at LincolnFollow
Milford Hanna, University of Nebraska-LincolnFollow
David D. Jones, University of Nebraska - LincolnFollow

Date of this Version

March 2008

Comments

Published in Starch/Stärke 60 (2008), pp. 159–164; doi 10.1002/star.200700687. Copyright © 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Used by permission. http://www3.interscience.wiley.com/journal/5007532/home

Abstract

Tapioca starch, poly(lactic acid) and Cloisite 30B nanocomposites foams, with clay contents of 1, 3, 5 and 7% (w/w), were prepared by a meltintercalation method. Multiple inputs single output models were developed to predict radial expansion ratio, unit density, bulk compressibility and spring index of the nanocomposite foams. An individual ANFIS model was developed for each mechanical property using clay content, temperature, pressure and torque as input parameters. All models preformed well with R² values > 0.71. All models had very low root mean squared error values.