Constitutive modeling is a method that is useful in providing precise predictions of material response in components subjected to a variety of operating conditions. A process for optimizing the material constants of the Miller constitutive model for uniaxial modeling was developed and implemented in an automated optimization routine. Generally, up to twenty experiments simulating a range of conditions are needed to identify the material parameters for the model. The research sought to minimize the amount of empirical data that is necessary for optimization, aiming to reduce the costs and time necessary to carry out this procedure for more expensive classes of materials. The ultimate goal was to develop a robust method for determining the material constants of a viscoplastic model using a minimum amount of experimental data. An automated optimization routine was implemented into a program, referred to as uSHARP, developed as part of the research to determine constitutive model parameters. Central to the method was the use of more complex stress, strain, and temperature histories than are traditionally used, allowing for the effects of all material parameters to be captured using as few tests as possible. By carrying out successive finite element simulations and comparing the results to simulated experimental test data, the material constants were determined from 75% fewer experiments. By reducing monetary costs and time required, this procedure will allow for a more widespread application of advanced constitutive models in industry, allowing for better life prediction modeling of critical components in high temperature applications.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:honorstheses1990-2015-1827 |
| Date | 01 January 2009 |
| Creators | Hogan, Erik A. |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | HIM 1990-2015 |
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