The analysis of fatigue lifetime using markov chain model based on randomization paris law equation

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Abstract

The experimental data of fatigue crack growth scatter even under identical experimental conditions, including constant amplitude loading. Thus, it is important to take into account the data scatter of crack growth rates by using statistical approach analysis. In this study, the distribution of the fatigue crack growth life was estimated using Markov chain approach based on the modified Paris law equation to consider the variability in the growth of the fatigue crack. In this regard, in the Markov Chain model, the Paris law equation was integrated with the probability distribution of the initial crack length to calculate the probability transition matrix. The result shows that the initial probability distribution was represented by lognormal distribution and it can be said that the initial crack will happen only in state 1 and state 2. The consideration of probability distribution into Paris law equation to represent the physical meaning of fatigue crack growth process. The fatigue life estimation using the Markov chain model are found to be agreed well with experimental results and the value of R 2 showed the model is good. The results provide a reliable prediction and show excellent agreement between proposed model and experimental result. This indicates that the model can be an effective tool for safety analysis of structure.

Original languageEnglish
Pages (from-to)282-286
Number of pages5
JournalInternational Journal of Innovative Technology and Exploring Engineering
Volume8
Issue number5s
Publication statusPublished - 1 Jan 2019

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Markov processes
Fatigue of materials
Fatigue crack propagation
Probability distributions
Cracks
Crack propagation

Keywords

  • Fatigue crack growth
  • Markov Chain model
  • Probability distribution
  • Randomization Paris law equation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Civil and Structural Engineering
  • Mechanics of Materials
  • Computer Science(all)

Cite this

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title = "The analysis of fatigue lifetime using markov chain model based on randomization paris law equation",
abstract = "The experimental data of fatigue crack growth scatter even under identical experimental conditions, including constant amplitude loading. Thus, it is important to take into account the data scatter of crack growth rates by using statistical approach analysis. In this study, the distribution of the fatigue crack growth life was estimated using Markov chain approach based on the modified Paris law equation to consider the variability in the growth of the fatigue crack. In this regard, in the Markov Chain model, the Paris law equation was integrated with the probability distribution of the initial crack length to calculate the probability transition matrix. The result shows that the initial probability distribution was represented by lognormal distribution and it can be said that the initial crack will happen only in state 1 and state 2. The consideration of probability distribution into Paris law equation to represent the physical meaning of fatigue crack growth process. The fatigue life estimation using the Markov chain model are found to be agreed well with experimental results and the value of R 2 showed the model is good. The results provide a reliable prediction and show excellent agreement between proposed model and experimental result. This indicates that the model can be an effective tool for safety analysis of structure.",
keywords = "Fatigue crack growth, Markov Chain model, Probability distribution, Randomization Paris law equation",
author = "Januri, {Siti Sarah} and {Mohd Nopiah}, Zulkifli and {Mohd Ihsan}, {Ahmad Kamal Ariffin} and Nurulkamal Masseran and Shahrum Abdullah",
year = "2019",
month = "1",
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language = "English",
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journal = "International Journal of Innovative Technology and Exploring Engineering",
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AU - Januri, Siti Sarah

AU - Mohd Nopiah, Zulkifli

AU - Mohd Ihsan, Ahmad Kamal Ariffin

AU - Masseran, Nurulkamal

AU - Abdullah, Shahrum

PY - 2019/1/1

Y1 - 2019/1/1

N2 - The experimental data of fatigue crack growth scatter even under identical experimental conditions, including constant amplitude loading. Thus, it is important to take into account the data scatter of crack growth rates by using statistical approach analysis. In this study, the distribution of the fatigue crack growth life was estimated using Markov chain approach based on the modified Paris law equation to consider the variability in the growth of the fatigue crack. In this regard, in the Markov Chain model, the Paris law equation was integrated with the probability distribution of the initial crack length to calculate the probability transition matrix. The result shows that the initial probability distribution was represented by lognormal distribution and it can be said that the initial crack will happen only in state 1 and state 2. The consideration of probability distribution into Paris law equation to represent the physical meaning of fatigue crack growth process. The fatigue life estimation using the Markov chain model are found to be agreed well with experimental results and the value of R 2 showed the model is good. The results provide a reliable prediction and show excellent agreement between proposed model and experimental result. This indicates that the model can be an effective tool for safety analysis of structure.

AB - The experimental data of fatigue crack growth scatter even under identical experimental conditions, including constant amplitude loading. Thus, it is important to take into account the data scatter of crack growth rates by using statistical approach analysis. In this study, the distribution of the fatigue crack growth life was estimated using Markov chain approach based on the modified Paris law equation to consider the variability in the growth of the fatigue crack. In this regard, in the Markov Chain model, the Paris law equation was integrated with the probability distribution of the initial crack length to calculate the probability transition matrix. The result shows that the initial probability distribution was represented by lognormal distribution and it can be said that the initial crack will happen only in state 1 and state 2. The consideration of probability distribution into Paris law equation to represent the physical meaning of fatigue crack growth process. The fatigue life estimation using the Markov chain model are found to be agreed well with experimental results and the value of R 2 showed the model is good. The results provide a reliable prediction and show excellent agreement between proposed model and experimental result. This indicates that the model can be an effective tool for safety analysis of structure.

KW - Fatigue crack growth

KW - Markov Chain model

KW - Probability distribution

KW - Randomization Paris law equation

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