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Probabilistic structural durability prediction

Authors: Xiaoming Yu; Kuang-Hua Chang; Kyung K. Choi;

Probabilistic structural durability prediction

Abstract

Anefe cientreliability analysis method fordurability of structural components subjected to external and inertial loads with time-dependent variable amplitudes is presented. This method is able to support reliability analysis of crack-initiation and crack-propagation lives of practical applications, considering uncertainties such as material properties, manufacturing tolerances, and initial crack size. Three techniques are employed to support the probabilistic durability prediction: 1 ) strain-based approach for multiaxial crack-initiation-life prediction and linear elastic fracture mechanics approach for crack-propagation-life prediction, 2 ) statistics-based approach for reliability analysis, and 3 ) sensitivity analysis and optimization methods for searching the most probable point (MPP) in the random variable space to compute the fatigue failure probability using the e rst-order reliability analysis method. A two-point approximation method is employed to speed up the MPP search. A tracked-vehicle roadarm is presented to demonstrate feasibility of the proposed method.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
47
Top 10%
Top 1%
Average
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