Citation

Ketabdari M, Giustozzi F, Crispino M. Safety Sci. 2018; 107: 173-187.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.ssci.2017.07.005

PMID

unavailable

Abstract

Risk assessment methods in aviation greatly rely on the knowledge of the factors influencing risk and safety during daily operations. One of the weak points of the common approaches in aerodromes is the qualitative method to support decisions respect to quantitative evaluations. In this study, three airports with diverse characteristics (i.e.; aircraft annual movements, airfield geometry, and runway features) were selected for the analysis. The RSARA© (Runway Safety Area Risk Assessment) software, which is based on the Aircraft Cooperative Research Program (ACRP) model, has been utilized as a starting point for further sensitivity analyses of probabilistic risk assessment of each airport's runway with determined casual factors, including runway geometry, traffic characteristics, and weather conditions. A comprehensive airports incident/accident database between years 2000 and 2015 was also used to perform the sensitivity analyses. By providing different independent variables as input in the frequency model of RSARA, the outputs were useful to determine the influence of each of the casual factors on the accident probability of occurrence. Selected variables include: runway length in terms of declared distances, Runway Safety Area geometry, instrumental landing system category, weather operational data and annual traffic growth rate. The sensitivity analyses showed that the weather condition and runway related factors played a major role in increasing or decreasing the probability of the accident; the probability of landing overrun (LDOR) can be increased by four times, for instance, due to specific combinations of runway length and climatic conditions. Engineered arrestor beds such as EMAS also has the potential to decrease by 50% the risk of LDOR and can be selected as an effective choice compared to other pavement materials within the RSA. Identifying critical variables on the occurrence of high-severity runway accidents could influence the aerodrome design, operating scenarios, regulations, emergency planning and risk management measures and techniques.

Language: en

Keywords

Airports; Probabilistic risk assessment; RESA; Runway Safety Area; Runway STRIP; Sensitivity analysis