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TECHNICAL PAPERS

Determination of Poisson’s Ratio by Spherical Indentation Using Neural Networks—Part II: Identification Method

[+] Author and Article Information
N. Huber

Forschungszentrum Karlsruhe, Institut für Materialforschung II (IMF II), Postfach 3640, D-76021 Karlsruhe, Germany   e-mail: norbert.huber@imf.fzk.de

Ch. Tsakmakis

Technische Universität Darmstadt, Institut für Mechanik 1, Hochschulstrasse 1, D-64289 Darmstadt, Germanye-mail: tsakmakis@mechanik.tu-darmstadt.de

J. Appl. Mech 68(2), 224-229 (Nov 01, 2000) (6 pages) doi:10.1115/1.1355032 History: Received March 26, 1999; Revised November 01, 2000
Copyright © 2001 by ASME
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References

Figures

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Sketch of a spherical indentation depth-load response for elastic-plastic deformation
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Accuracy of the identified slope mid
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Comparison of the P̃l(h) distribution with the Pl(h) finite element method (FEM) data
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Comparison of the smooth m̃*(ht)-distribution with the m*(ht) finite element method (FEM) data
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Simultaneous identification of Poisson’s ratio ν and hy* as intersection of Set 2 and Set 3
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Accuracy of the identified Poisson’s ration ν
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Accuracy of the identified yield depth hy*
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Stress-strain curves for linear hardening and different nonlinear hardening rules
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Depth-load trajectories according to the hardening rules displayed in Fig. 8

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