Joseph Jette - Masters Thesis Defense 8/25@10am in Roberts 301
- Friday, August 25, 2017 at 10:00am
- Roberts Hall, Room 301 - view map
Damage Characterization of Fiber Reinforced Composite Materials By Means of Mulitaxial Testing and Digital Image Correlation
Composite materials offer a unique quality to improve structural designs. Now, not only can a structure’s geometry be designed, composite materials offer the engineer the ability to design the layup of the material and, in turn, control some of its structural properties. While this feature of composite materials is appealing, it also poses issues for all processes involved in its design. One of the primary issues is that characterization of these materials in different orientations is often difficult and expensive. Due to composite materials’ anisotropy, heterogeneity, and variability, their constitutive and damage behavior remain poorly understood.
Often due to this misunderstanding, designs that use composite materials undergo a lengthy, difficult, and expensive procedures to produce the final product. Part of these procedures is the finite element modeling and simulation of designed components which requires accurate material response data. As modeling capabilities improve, provided the proper material damage response modeling data, damage models offer the ability to predict the damage response of designs. The ability to accurately predict damage responses in structures is a primary contributor to a design’s development time and its overall success.
In this study, multiaxial testing via the Montana State University In-Plane Loader was performed on two carbon fiber epoxy prepreg material systems. This testing was performed to determine the usefulness of digital image correlation and multiaxial testing as a means of characterizing composite materials’ damage responses and to produce data capable of informing and validating damage models. The combination of digital image correlation and multiaxial testing provided dense experimental results that may prove useful to qualitatively and quantitatively inform, validate, and enhance computer finite element modeling and analysis.
- Department of Mechanical & Industrial Engineering