209 Multiscale Analysis of Damage and Failure, Process Induced Defects and Uncertainty Quantification in Heterogeneous Materials

Mahesh Bailakanavar, Thornton Tomasetti
Abilash Nair, Thornton Tomasetti
Sergey Kuznetsov, North Carolina State University
Multiscale Analysis of Damage and Failure, Process Induced Defects and Uncertainty Quantification in Heterogeneous Materials

We aim to address some of the challenges associated with multiscale-multiphysics based predictive modeling of damage and failure in heterogeneous material systems, which is at the forefront of engineering research.

1. The manufacturing process of complex composite parts (for example hot path components in turbine engines) necessitates ply drops or curved plies to transition between regions of varying thicknesses and curvatures. This process inadvertently results in manufacturing defects such as porosity and matrix rich regions in the vicinity of the ply drops and ply wrinkling. Under the action of service loads, these defects act as potential sources for intra-laminar damage and delamination. At temperatures above 1500 °F, factors such as composition, grain size, impurity content, and prior thermo-structural history have a significant impact on rate of fiber strength degradation with time and temperature. Hence, accounting for the effects of process-induced defects at crossover points, matrix voids, shrinkage cracks and interlaminar separation is necessary for accurate and consistent characterization of the material in service environment.

2. Unlike materials with periodic microstructure, generation of morphological details of materials with randomly distributed inclusions, such as defects in ceramics, hard and soft domains in polymers and chopped fiber composites pose various challenges such as:
a) Accurate representation of the inclusion shape, size, volume fraction and spatial orientation to minimize geometric approximation errors
b) Generation of microstructures with packing fraction as high as 45%, typically found in industrial grade composite materials
c) Determination of the unit cell size that constitutes a macroscopically homogeneous material
d) Generation of unit cells in quick succession with maximum computational efficiency for utilization in a stochastic multiscale framework

3. The next challenge in the multiscale framework of numerical analyses is computational efficiency. The objective is to strike a balance between modeling of fine scale physics and tractable analyses runtimes without compromising on the emerging phenomena during mathematical upscaling and downscaling including localization.

4. One other challenge that we aim to address is the quantification of uncertainty due to the randomness and heterogeneity in material microstructures and the fine scale physics. Fine scale models account for variations in geometry, topology and physical and mechanical properties and propagate them across length scales to make probabilistic predictions at engineering length scales. However, availability of data about material microstructure like grain size, shape and orientation and the variation is fine scale constituent properties is vital for verification and validation of these probabilistic models.

These challenges intend to derive the programming of this symposium. All aspects of computational analysis of composite materials will be within the scope.