Advanced engineering materials are designed to display tensile-compressive asymmetry (TCA) and anisotropy to provide unique attributes to critical components necessary in the hot section of turbines. The never-ending chase for higher efficiencies, and with them, higher temperature gradients, intrinsically leads to more and more of these complex materials, like single crystal turbine blades, embedded within the turbine environment. Mathematical models, known as yield criteria, allow engineers to visualize the mechanical behavior of these materials in various orientations under complex loading. Yield criteria are dependent on three key items in determination of their governing parameters: material test data, mathematical constraints, and knowledge about the examined materials microstructure in order to predict the materials attributes (Anisotropy, Tensile-Compressive Asymmetry). The optimization of the modeling parameters governing constitutive modeling of TCA and anisotropic material has been a semi- active area of research in the last decade. As such, there is a deficit of repeatable, robust, and more efficient techniques present within the literature surrounding determination of the yield criteria parameters surrounding nickel-base superalloys. Research is proposed to derive a novel way to identify yield surface parameters. Meshing proven algorithms with a vast material database, identifying the overall best modeling parameters, and reducing the required physical testing will be of fundamental concern. The inherent reduction of lab time, and accompanied cost of experimentation, will allow the user to make use of the test data more efficiently. Implementing the constant determination approach will be facilitated by developed MATLAB code, providing an easy and centralized environment for identifying and parameterizing a repeatable yield surface representing the user uploaded anisotropic and TCA material.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:honorstheses-2623 |
| Date | 01 January 2023 |
| Creators | Hanekom, Kevin |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Honors Undergraduate Theses |
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