Probabilistic Modelling of Runway Accidents In Nigeria

Authors

  • A. Akinyemi Agricultural and Mechanical Engineering Department, Olabisi Onabanjo University, Ago-Iwoye, Nigeria Mechanical Engineering Department, Ladoke Akintola University of Technology, Ogbomoso, Nigeria
  • Kazeem A. Adebiyi Agricultural and Mechanical Engineering Department, Olabisi Onabanjo University, Ago-Iwoye, Nigeria Mechanical Engineering Department, Ladoke Akintola University of Technology, Ogbomoso, Nigeria
  • R. Raheem Agricultural and Mechanical Engineering Department, Olabisi Onabanjo University, Ago-Iwoye, Nigeria Mechanical Engineering Department, Ladoke Akintola University of Technology, Ogbomoso, Nigeria
  • A. Wasiu Agricultural and Mechanical Engineering Department, Olabisi Onabanjo University, Ago-Iwoye, Nigeria Mechanical Engineering Department, Ladoke Akintola University of Technology, Ogbomoso, Nigeria
  • O. Opetubo Agricultural and Mechanical Engineering Department, Olabisi Onabanjo University, Ago-Iwoye, Nigeria Mechanical Engineering Department, Ladoke Akintola University of Technology, Ogbomoso, Nigeria
  • O. Oriyomi Agricultural and Mechanical Engineering Department, Olabisi Onabanjo University, Ago-Iwoye, Nigeria Mechanical Engineering Department, Ladoke Akintola University of Technology, Ogbomoso, Nigeria

DOI:

https://doi.org/10.46881/ajsn.v2i1.26

Keywords:

, Runway accidents, runway safety, probability distribution, Poisson process, accident causation factor

Abstract

Aviation sector is one of the safest methods of travel; unfortunately thousands of peoples suffer extreme injury or death due to accidents. This paper applied input modelling simulation method to analyse runway accidents occurrences in Nigeria aviation sector and develops a model that will predict the probability or risk of runway accidents. Accident records for pre-safety periods (1979-1999) and safety periods (2000-2010) were analyzed using probability distribution curve. A probability distribution curve which resembled Poisson distribution was developed. A point statistic estimator was used to confirm the distribution. Hence, a probability predictive model was developed in terms of average mean time between runway accidents and number of runway operation days. The average mean time between accidents during pre-safety period was 90.54 with standard deviation of 83.36. Similarly, the average mean time between runway accidents results during safety periods was 64.82 and standard deviation of 53.48. The probability of runway accident occurrence during safety periods was 0.0154 while that of pre-safety period was 0.0111. The results of this research can be used by a broad range of civil aviation organization for risk assessment of runway operations as a means for evaluating the performance of runway safety

References

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Published

2017-06-21

Issue

Vol. 2 No. 1 (2016)

Section

Articles