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    Description

    This paper is describing the preliminary results of an effort to validate a methodology developed for composite material constitutive characterization. This methodology involves using massive amounts of data produced from multiaxially tested coupons via a 6-DoF robotic system called NRL66.3 developed at the Naval Research Laboratory. The testing is followed by the employment of energy based design optimization principles to solve the inverse problem that determines the unknown parameters of the constitutive model under consideration. In order to validate identified constitutive models, finite element simulations using these models were exercised for three distinct specimen geometries. The first geometry was that of the characterization coupon under multiaxial loading. The second was that of open hole specimens in tension. The final one was that of stiffened panel substructures under tension. Actual experimental data from testing all these specimens were collected by the use of load cells, full field displacement and strain methods and strain gauges. Finally, the theoretical predictions were compared with the experimental ones in terms of strain field distributions and load-strain responses. The comparisons demonstrated excellent predictability of the determined constitutive responses with the predictions always within the error band of the methods used to collect the experimental data.

    Publication Notes

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    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

    Citation

    Michopoulos, John G.; lliopoulos, Athanasios; Hermanson, John C.; Orifici, Adrian C.; Thomson, Rodney S. 2012. Preliminary Validation of Composite Material Constitutive Characterization. In: Proceedings of the ASME 2012 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, August 12-15, 2012, Chicago, IL, IDETC/CIE 2012; 10 p.

    Keywords

    multiaxial testing, open-hole specimen, stiffened panel substructure, data-driven methodology

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https://www.fs.usda.gov/treesearch/pubs/49491