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An Efficient Method for the Optimization of Viscoplastic Constitutive Model Constants

[+] Author Affiliations
James P. DeMarco, Erik A. Hogan, Calvin M. Stewart, Ali P. Gordon

University of Central Florida, Orlando, FL

Paper No. GT2010-23311, pp. 569-580; 12 pages
doi:10.1115/GT2010-23311
From:
  • ASME Turbo Expo 2010: Power for Land, Sea, and Air
  • Volume 6: Structures and Dynamics, Parts A and B
  • Glasgow, UK, June 14–18, 2010
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-4401-4 | eISBN: 978-0-7918-3872-3
  • Copyright © 2010 by ASME

abstract

Constitutive modeling has proven useful in providing accurate predictions of material response in components subjected to a variety of operating conditions; however, the high number of experiments necessary to determine appropriate constants for a model can be prohibitive, especially for more expensive materials. Generally, up to twenty experiments simulating a range of conditions are needed to identify the material parameters for a model. In this paper, an automated process for optimizing the material constants of the Miller constitutive model for uniaxial modeling is introduced. The use of more complex stress, strain, and temperature histories than are traditionally used allows for the effects of all material parameters to be captured using significantly fewer tests. A graphical user interface known as uSHARP was created to implement the resulting method, which determines the material constants of a viscoplastic model using a minimum amount of experimental data. By carrying out successive finite element simulations and comparing the results to simulated experimental test data, both with and without random noise, the material constants were determined from 75% fewer experiments. The optimization method introduced here reduces the cost and time necessary to determine constitutive model constants through experimentation. Thus it allows for a more widespread application of advanced constitutive models in industry and for better life prediction modeling of critical components in high-temperature applications.

Copyright © 2010 by ASME

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