2012
DOI: 10.1016/j.engstruct.2012.06.012
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Bayesian model updating and prognosis of fatigue crack growth

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Cited by 50 publications
(30 citation statements)
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“…For components and structures undergoing FCG, several researchers [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] have developed methodologies to ascertain the fatigue life. Karandikar et al 4 have applied Bayesian inference using a random walk method to predict the remaining useful life of an aircraft fuselage panel.…”
Section: A Brief Review Of the Related Literaturementioning
confidence: 99%
See 1 more Smart Citation
“…For components and structures undergoing FCG, several researchers [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] have developed methodologies to ascertain the fatigue life. Karandikar et al 4 have applied Bayesian inference using a random walk method to predict the remaining useful life of an aircraft fuselage panel.…”
Section: A Brief Review Of the Related Literaturementioning
confidence: 99%
“…Markov chains Monte Carlo-based methods have also been proposed in the literature [14][15][16][17][18] to address the uncertainty in FCG estimation. An et al 19 in their paper have estimated the distribution of the fatigue lifetime of turbine blades using the MCMC method.…”
Section: A Brief Review Of the Related Literaturementioning
confidence: 99%
“…Similarly, inspection scheduling and short-term routing have also been optimized using updated reliability frameworks [9,10]. In a similar vein, Zrate et al [11] presented a framework to update and predict crack length as a function of the number of cycles in structural elements subjected to fatigue. Meulen and Hageman [12] used Bayesian analysis to predict fatigue accumulation using data from Fatigue Damage Sensors (FDS) a notched sensing foil which records site-specific fatigue damage.…”
Section: Introductionmentioning
confidence: 99%
“…Many investigations were conducted to reduce the uncertainties of the deterioration process in structure reliability analysis and health monitoring [34,35]. An et al [36] studied the influence of noise and bias in updating the parameters of Paris law based model.…”
Section: Introductionmentioning
confidence: 99%