Failure Prediction of Fiber Reinforced Composites Using Reduced Order Multiscale Models
Bogdanor, Michael James
:
2015-11-25
Abstract
Fiber reinforced polymer (FRP) composites present a significant opportunity for increas-
ing performance and energy efficiency in a number of technology sectors, most notably the
automotive and aerospace industries. In order to reduce the development costs for FRP ma-
terials, accurate and efficient predictive methods are required which capture the evolution
of damage at the heterogeneous microscale. The goal of this dissertation is to advance the
state of the art in the failure prediction of FRP composites through new multiscale methods
both for the mechanical response and propagation of uncertainty in the material. The contin-
ued development of the eigen-deformation based homogenization method with reduced order
models (EHM) is presented, including a new approach to address the tension-compression
stiffness anisotropy in the fiber direction and a novel parameter weighting method to capture
the disparate damage evolution under uniaxial and shear loading. A blind prediction study
of laminated IM7/977-3 composites using the improved EHM approach is presented for three
composite layups ([0,45,90,-45]2S, [30,60,90,-60,-30]2S, and [60,0,-60]3S) under static tension
and compression and tension-tension fatigue with open hole and unnotched configurations.
Additionally, Bayesian parameter calibration is implemented within the EHM framework to
quantify uncertainty in the composite and is utilized to predict the probabilistic behavior of
laminated composite specimens subject to strain rate-dependent effects.