Results 261 to 270 of about 49,270 (307)

Markov models for fatigue crack growth

Engineering Fracture Mechanics, 1987
Abstract A review of several statistical and probabilistic approaches to the problem of fatigue crack growth shows that many Markov models are equivalent in that they express the probability density of the crack length at time t as solutions of the Kolmogorov, or Fokker-Plank, equations.
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Stochastic modeling of fatigue crack growth

Engineering Fracture Mechanics, 1988
Abstract A stochastic model for the variations of a material's resistance to fatigue crack growth along the path of a crack is integrated for fatigue life. The results are compared against a well known data set and against the predictions of a more conventional probabilistic model. It is shown that it is important to model the statistical correlation
Keith Ortiz, Anne S. Kiremidjian
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One model of fatigue crack growth

Journal of Applied Mechanics and Technical Physics, 2009
A model for crack growth is proposed based on studies of the variation in the curvature radius at the crack tip during cyclic loading. Relations are obtained between mechanical material characteristics, crack geometry, and the rate of crack growth in a structure under cyclic loading.
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A model for fatigue crack closure

Engineering Fracture Mechanics, 1984
Abstract The phenomenon of fatigue crack closure has attracted continued interest over recent years. This paper concerns itself with one aspect of the phenomenon namely the effects of a single asperity on the crack face close to the crack tip and under dominantly plane strain Mode 1 loading conditions.
C.J. Beevers, K. Bell, R.L. Carlson, E.A. Starke   +3 more
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Modeling of Random Fatigue Crack Propagation

Advanced Materials Research, 2013
A statistical model is proposed for the analysis of fatigue crack propagation, based on the theory of fracture mechanics and stochastic process. The fatigue growth process is approximated as a diffusive Markov process. The associated backward Fokker-Plank equation and boundary conditions are written, and the distribution of crack propagation time under
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Bayesian Modeling For Fatigue Crack Curves

1992
An accurate assessment of the propagation of cracks in materials (“metal fatigue”) is important to the structural design and the development of preventive maintenance programs for many engineering structures, including critical aerospace components. Interest is centered on modeling the lifetime process, N(a), which represents the number of load cycles ...
Panickos N. Palettas, Prem K. Goel, Purushottam W. Laud   +2 more
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Probabilistic Mesomechanical Fatigue Crack Nucleation Model

Journal of Engineering Materials and Technology, 1997
A probabilistic mesomechanical crack nucleation model is proposed to link the microstructural material heterogeneities to the statistical scatter in the macro structural response. The macrostructure is modeled as an ensemble of microelements. Cracks nucleate within the microelements and grow from the microelements to final fracture.
R. G. Tryon, T. A. Cruse
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Fatigue Crack Initiation—Propagation Reliability Model

Journal of Materials in Civil Engineering, 1991
The paper presents a probabilistic model for fatigue strength that includes both the initiation and propagation phases, and is suitable for inclusion of formal reliability analyses. This method is most useful for fatigue in a fabricated structure that is expected to have a small crack initiation life and may apply to a significant body of welded joint ...
W. Scott Martin, Paul H. Wirsching
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Modelling plasticity-induced fatigue crack closure

Engineering Fracture Mechanics, 1990
Abstract A numerical analysis of plasticity-induced fatigue crack closure based upon the finite difference method is presented. This new method permits modelling easily fatigue crack growth as well as contacts between fracture faces, without requiring sophisticated algorithms.
J. Llorca, V. Sánchez Gálvez
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Stochastic Modeling of Fatigue Crack Propagation

1985
Deterministic fatigue crack propagation models, such as the Paris-Erdogan model, cannot account for random variability of time-histories observed in experiments. Therefore, more realistic models are proposed in which a random process is introduced as a multiplicative factor to deterministic laws.
Y. K. Lin, W. F. Wu, J. N. Yang
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