Title

An Efficient Method For The Optimization Of Viscoplastic Constitutive Model Constants

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 ran- dom 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. Keywords: constitutive modeling, optimization, viscoplastic. Copyright © 2010 by ASME.

Publication Date

12-1-2010

Publication Title

Proceedings of the ASME Turbo Expo

Volume

6

Issue

PARTS A AND B

Number of Pages

569-580

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1115/GT2010-23311

Socpus ID

82055189901 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/82055189901

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