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RESEARCH PAPERS: Special Issue on Time-Dependent Behaviors of Polymer Matrix Composites and Polymers

Fiber Composite Strength Modeling With Extension to Life Prediction

[+] Author and Article Information
Edward M. Wu

 U.S. Naval Postgraduate School, 4151 Sunset Lane, Pebble Beach, CA 93953emwusa@hotmail.com

John L. Kardos

 Washington University, Department of Chemical Engineering, 1 Brookings Drive, Campus Box 1198, St. Louis, MO 63130kardos@wustl.edu

J. Eng. Mater. Technol 128(1), 41-49 (Sep 23, 2005) (9 pages) doi:10.1115/1.2128424 History: Received August 24, 2004; Revised September 23, 2005

This paper focuses on the probability modeling of fiber composite strength, wherein the failure modes are dominated by fiber tensile failures. The probability model is the tri-modal local load-sharing model, which is the Phoenix-Harlow local load-sharing model with the filament failure model extended from one mode to three modes. This model results in increased efficiency in the determination of fiber statistical parameters and in lower cost when applied to (i) quality control in materials (fiber) manufacturing, (ii) materials (fiber) selection and comparison, (iii) accounting for the effect of size scaling in design, and (iv) qualification and certification of critical composite structures that are too large and expensive to test statistically. In addition, possible extensions to proof testing and time-dependent life prediction are discussed and preliminary data are presented.

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Copyright © 2006 by American Society of Mechanical Engineers
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Figures

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Figure 1

Local load sharing around broken fibers culminating in flaw clustering

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Figure 2

Nonlinearity due to three dominating modes (upper tail and lower tail can only be observed by a very large number of data for a fixed sample dimension)

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Figure 3

Method for observing extreme tails: (i) for upper end, reduce sample dimension; test and fit curve, shift curve up by size effect and (ii) for lower end, increase sample dimension; test and fit curve, shift curve down by size effect

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Figure 4

Tri-modal local load-sharing (TMLLS) model is the genome that relates the strength of large composite structures to the upper tail (intrinsic fiber strength), middle (quality control of fiber process), and lower tail (large fiber-processing errors) of the entire distribution of fiber strengths

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Figure 5

High-pass filtering by prooftest (example: strength filtering by applied stress)

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Figure 6

Different post-proof-test responses to proof loading

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Figure 7

Effect of idealized proof test with truncated lower tail

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Figure 8

Effect of proof test resulting in damage to the lower tail

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Figure 9

Life of aramid-epoxy composite under sustained load (8.29kg)

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Figure 10

Life of aramid-epoxy composite under sustained load (8.29kg) after survival of preload (8.93kg) at 23°C

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Figure 11

Life of aramid-epoxy composite under sustained load (8.29kg) after survival of preload (8.73kg) at 70°C.

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Figure 12

Life of aramid-epoxy composite under sustained load (8.29kg) after survival of high preload (9.3kg) at 70°C

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Figure 13

Strength of carbon-epoxy composite compared to strength of composite preloaded at gel state during fabrication

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Figure 14

Distribution-free strength comparisons of graphite-epoxy composite compared to composite preloaded at gel state during fabrication

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