A Stochastic Finite Element Analysis Framework for the Multiple Physical Modeling of Filler Modified Polymers

  • Author / Creator
    Hamidreza Ahmadimoghaddamseighalani
  • Polymers have various attractive properties (e.g., low volume mass density, low cost and excellent degradation resistance), and hence, they have become essential for a wide range of applications (e.g., aerospace, oil and gas and renewable energy industries). However, due to their limited mechanical, thermal and electrical properties in comparison with typical metallic materials (e.g., steel and aluminum alloys), polymers often need to be modified with different types of fillers to meet the requirements of specific applications. A multitude of filler materials (e.g., nano silver particles, carbon nano tubes, graphene) are available with a wide range of geometries, such as spherical, fiber and platelet shapes. Therefore, developing methods for efficiently characterizing and identifying mechanical and physical properties of filler modified polymers is an important engineering task. The objective of this thesis is to create and validate a numerical modeling framework for predicting mechanical, thermal and electrical properties of particulate polymer composites. In contrast to the high cost and time consuming nature of experiments, this framework is to provide a relatively time- and cost-effective means to guide material design and elucidate experimental observations and analysis results. The first phase of this research project was focused on developing a numerical multiphysics modeling framework to predict the mechanical and thermal properties (i.e., effective modulus of elasticity, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity), of a single-phase particulate polymer composite with randomly distributed spherical particles. The second phase focus was on expanding the modeling framework to enable property predictions, specifically thermal properties (i.e., effective thermal conductivity), of randomly distributed but aligned cylindrical particulate composites fillers. In the final phase of the research, the numerical framework was extended to predict electrical properties (i.e., effective electrical conductivity, percolation threshold and piezoresistivity), of spherical shape particulate composites. Predicted data were compared against experimental values and analytical models in the different contexts, which indicated overall good agreement between the predictions from the developed modeling framework and experimental works. The developed modeling framework is a valuable contribution facilitating the study of a broad range of material properties, thus improving the material design of filler modified polymers, by comprehensively capturing random aspects of particle and composite morphology.

  • Subjects / Keywords
  • Graduation date
    Spring 2021
  • Type of Item
  • Degree
    Doctor of Philosophy
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.