|About this Abstract
||2017 TMS Annual Meeting & Exhibition
||Computational Methods and Experimental Approaches for Uncertainty Quantification and Propagation, Model Validation, and Stochastic Predictions
||Hierarchical Multiscale Modeling and Parametric Analysis of Polyvinyl Alcohol/Montmorillonite Nanocomposites
||William Lawrimore, Justin Hughes, Bhasker Paliwal, Mei Chandler, Kyle Johnson, David Francis, Mark Horstemeyer
|On-Site Speaker (Planned)
A factorial Design of Experiments (DOE) parametric study using Finite Element Analysis (FEA) of Polymer/Clay Nanocomposites (PCN) was completed to expose the most crucial parameters affecting the performance of PCNs under quasi-static tension. Three-dimensional FEA featuring a Cohesive Zone Model (CZM) based on results of Molecular Dynamics (MD) simulations was used to perform a DOE parametric study on Polyvinyl Alcohol (PVA)/Montmorillonite (MMT) nanocomposite systems. The DOE process utilized an Analysis of Variance (ANOVA) technique to analyze the relative influence of four parameters related to nanoclay particles within a polymer matrix (aspect ratio, orientation, intercalation, and gallery strength) with respect to the overall PCN mechanical performance while including uncertainty principles. Additionally a Monte Carlo (MC) routine featuring a Radial Basis Function (RBF) provided quantification for the uncertainty related to the multiscale modeling methodology used in this endeavor.