### Abstract

This paper presents the analysis and modeling of predicting fatigue lifetime based on the Markov Chain model. Random factor is the main contributor to the prediction of fatigue lifetime. These random factors give an appropriate framework for modeling and predicting a lifetime of the structure. The Markov Chain model was used to predict the probability of fatigue lifetime based on the randomization of initial probability distribution. An approach of calculating the initial probability distribution is introduced based on the statistical distribution of initial crack length and the transition probability was formed using a classical deterministic Paris law. The classical Paris law has been used in calculating the transition probabilities matrix to represent the physical meaning of fatigue crack growth problem. The data from the experimental work under constant amplitude loading was analyzed using the Markov Chain model. The results show that the model is capable to predict the fatigue lifetime for Aluminum Alloy A7075-T6.

Original language | English |
---|---|

Pages (from-to) | 44-48 |

Number of pages | 5 |

Journal | International Journal of Integrated Engineering |

Volume | 10 |

Issue number | 5 |

DOIs | |

Publication status | Published - 1 Jan 2018 |

### Fingerprint

### Keywords

- Fatigue lifetime
- Markov Chain model
- Paris law equation
- Probability distribution

### ASJC Scopus subject areas

- Civil and Structural Engineering
- Materials Science (miscellaneous)
- Mechanics of Materials
- Mechanical Engineering
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering

### Cite this

**The analysis of initial probability distribution in Markov Chain model for lifetime estimation.** / Januri, Siti Sarah; Mohd Nopiah, Zulkifli; Mohd Ihsan, Ahmad Kamal Ariffin; Masseran, Nurulkamal; Abdullah, Shahrum.

Research output: Contribution to journal › Article

}

TY - JOUR

T1 - The analysis of initial probability distribution in Markov Chain model for lifetime estimation

AU - Januri, Siti Sarah

AU - Mohd Nopiah, Zulkifli

AU - Mohd Ihsan, Ahmad Kamal Ariffin

AU - Masseran, Nurulkamal

AU - Abdullah, Shahrum

PY - 2018/1/1

Y1 - 2018/1/1

N2 - This paper presents the analysis and modeling of predicting fatigue lifetime based on the Markov Chain model. Random factor is the main contributor to the prediction of fatigue lifetime. These random factors give an appropriate framework for modeling and predicting a lifetime of the structure. The Markov Chain model was used to predict the probability of fatigue lifetime based on the randomization of initial probability distribution. An approach of calculating the initial probability distribution is introduced based on the statistical distribution of initial crack length and the transition probability was formed using a classical deterministic Paris law. The classical Paris law has been used in calculating the transition probabilities matrix to represent the physical meaning of fatigue crack growth problem. The data from the experimental work under constant amplitude loading was analyzed using the Markov Chain model. The results show that the model is capable to predict the fatigue lifetime for Aluminum Alloy A7075-T6.

AB - This paper presents the analysis and modeling of predicting fatigue lifetime based on the Markov Chain model. Random factor is the main contributor to the prediction of fatigue lifetime. These random factors give an appropriate framework for modeling and predicting a lifetime of the structure. The Markov Chain model was used to predict the probability of fatigue lifetime based on the randomization of initial probability distribution. An approach of calculating the initial probability distribution is introduced based on the statistical distribution of initial crack length and the transition probability was formed using a classical deterministic Paris law. The classical Paris law has been used in calculating the transition probabilities matrix to represent the physical meaning of fatigue crack growth problem. The data from the experimental work under constant amplitude loading was analyzed using the Markov Chain model. The results show that the model is capable to predict the fatigue lifetime for Aluminum Alloy A7075-T6.

KW - Fatigue lifetime

KW - Markov Chain model

KW - Paris law equation

KW - Probability distribution

UR - http://www.scopus.com/inward/record.url?scp=85061651538&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85061651538&partnerID=8YFLogxK

U2 - 10.30880/ijie.2018.10.05.008

DO - 10.30880/ijie.2018.10.05.008

M3 - Article

VL - 10

SP - 44

EP - 48

JO - International Journal of Integrated Engineering

JF - International Journal of Integrated Engineering

SN - 2229-838X

IS - 5

ER -