scholarly journals Determination of distributions of fatigue crack length by Monte Carlo method

Mechanik ◽  
2017 ◽  
Vol 90 (7) ◽  
pp. 568-570
Author(s):  
Józef Drewniak ◽  
Leszek Hojdys
Keyword(s):  
Monte Carlo ◽  
Fatigue Crack ◽  
Monte Carlo Method ◽  
Fatigue Crack Growth ◽  
Crack Length ◽  
Crack Growth ◽  
Input Data ◽  
The Monte Carlo Method ◽  
Random Distributions

Described is the determination of random distributions of the fatigue crack length by the Monte Carlo method and the Bogdanov–Kozin model. Input data needed to determine the distributor were obtained by simulation of fatigue crack growth using the Paris–Erdogan model.

scholarly journals THE INFLUENCE OF CORROSION ON RELIABILITY AND INSPECTION PROGRAM FOR FATIGUE‐PRONE AIRFRAME STRUCTURES

Aviation ◽  
2004 ◽  
Vol 8 (3) ◽  
pp. 10-17 ◽  
Author(s):  
M. Shujauddin Wahab ◽  
Yuri M. Paramonov
Keyword(s):  
Monte Carlo ◽  
Fatigue Crack ◽  
Monte Carlo Method ◽  
Fatigue Crack Growth ◽  
Fatigue Failure ◽  
Mean Value ◽  
The Monte Carlo Method ◽  
Special Programs ◽  
Crack Growth Model

This paper is devoted to a discussion and solution of the following problems: Determination of mean value and variance of estimates of parameters of fatigue crack growth model for both the corroded and non‐corroded types of specimens; Inspection modeling with the use of the Monte Carlo method for calculation of probability of fatigue failure as a function of inspection number; Determination of the number of inspections required for the limitation of fatigue failure probability; Comparison of required reliability for corroded and non‐corroded cases. Special programs have been developed for necessary calculations. It was confirmed that the influence of corrosion has a great impact on the required number of inspections.

Monte Carlo method for the reduction of measurement errors in the material parameter estimation with cavities

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ronny Peter ◽  
Luca Bifano ◽  
Gerhard Fischerauer
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Measurement Errors ◽  
Input Data ◽  
Material Parameter ◽  
Cavity Resonator ◽  
Calculation Algorithm ◽  
The Monte Carlo Method ◽  
Electromagnetic Resonances

Abstract The quantitative determination of material parameter distributions in resonant cavities is a relatively new method for the real-time monitoring of chemical processes. For this purpose, electromagnetic resonances of the cavity resonator are used as input data for the reverse calculation (inversion). However, the reverse calculation algorithm is sensitive to disturbances of the input data, which produces measurement errors and tends to diverge, which leads to no measurement result at all. In this work a correction algorithm based on the Monte Carlo method is presented which ensures a convergent behavior of the reverse calculation algorithm.

scholarly journals Crack-Length Estimation for Structural Health Monitoring Using the High-Frequency Resonances Excited by the Energy Release during Fatigue-Crack Growth

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4221
Author(s):  
Roshan Joseph ◽  
Hanfei Mei ◽  
Asaad Migot ◽  
Victor Giurgiutiu
Keyword(s):  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Crack Length ◽  
Crack Growth ◽  
Health Monitoring ◽  
Acoustic Waves ◽  
High Frequency ◽  
Fem Analysis ◽  
Signal Frequency ◽  
Propagation Pattern

Acoustic waves are widely used in structural health monitoring (SHM) for detecting fatigue cracking. The strain energy released when a fatigue crack advances has the effect of exciting acoustic waves, which travel through the structures and are picked up by the sensors. Piezoelectric wafer active sensors (PWAS) can effectively sense acoustic waves due to fatigue-crack growth. Conventional acoustic-wave passive SHM, which relies on counting the number of acoustic events, cannot precisely estimate the crack length. In the present research, a novel method for estimating the crack length was proposed based on the high-frequency resonances excited in the crack by the energy released when a crack advances. In this method, a PWAS sensor was used to sense the acoustic wave signal and predict the length of the crack that generated the acoustic event. First, FEM analysis was undertaken of acoustic waves generated due to a fatigue-crack growth event on an aluminum-2024 plate. The FEM analysis was used to predict the wave propagation pattern and the acoustic signal received by the PWAS mounted at a distance of 25 mm from the crack. The analysis was carried out for crack lengths of 4 and 8 mm. The presence of the crack produced scattering of the waves generated at the crack tip; this phenomenon was observable in the wave propagation pattern and in the acoustic signals recorded at the PWAS. A study of the signal frequency spectrum revealed peaks and valleys in the spectrum that changed in frequency and amplitude as the crack length was changed from 4 to 8 mm. The number of peaks and valleys was observed to increase as the crack length increased. We suggest this peak–valley pattern in the signal frequency spectrum can be used to determine the crack length from the acoustic signal alone. An experimental investigation was performed to record the acoustic signals in crack lengths of 4 and 8 mm, and the results were found to match well with the FEM predictions.

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