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ASTM Selected Technical Papers
Probabilistic Aspects of Life Prediction
By
WS Johnson
WS Johnson
editor
1
School of Materials Science and Engineering George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology
?
Atlanta, GA
Search for other works by this author on:
BM Hillberry
BM Hillberry
editor
2
School of Mechanical Engineering Purdue University
?
West Lafayette, IN
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ISBN-10:
0-8031-3478-9
ISBN:
978-0-8031-3478-2
No. of Pages:
285
Publisher:
ASTM International
Publication date:
2004

This paper presents a methodology for the use of probabilistic fracture mechanics concepts to estimate the design fatigue life and reliability of structural materials used in superconducting coils and magnet intercoil components of the International Thermonuclear Experimental Reactor (ITER). The orbitally welded conductor jackets of superconducting coils are subjected to fluctuating tensile stresses. The paper uses fatigue crack growth (FCGR) data at 7K from type 316LN stainless steel, in parent and weld material conditions, to predict fatigue crack growth rates using Monte Carlo analysis. Two stages are considered in which scatter could be quantified in the analysis. Initially, the unknown in crack length is taken as a stochastic variable. Secondly, the model assumes that the scatter observed in the correlation of the FCGR data versus ΔK is directly due to factors such as testing methods, measurement, material, and geometric variability and can therefore be quantified statistically. Either a normal or lognormal distribution of the scatter is assumed depending on the parameter. The purpose of this approach is to illustrate some of the advantages over a deterministic approach that most design codes use. An example is presented that compares the design life of a conductor jacket section containing a single crack and multiple cracks. A comparison of a sensitivity analysis for multiple cracks, for failure times at probabilities of 1 % and 0.001 %, with times calculated from a deterministic analysis using appropriate safety factors, suggests that the deterministic analysis give less conservative failure times.

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