Author:
Pei Binbin,Xu Haojun,Xue Yuan,Chen Wei,Shen Anwei
Abstract
Purpose
The purpose of this work is to develop an in-flight icing risk assessment methodology by quantification of changing flight dynamic characteristics under icing conditions.
Design/methodology/approach
This paper develops an approach for the quantitative assessment of flight risk under icing conditions. Using the six degree-of-freedom simulation model, the icing effects model is used to obtain the extreme values of the key parameters relevant to fight safety, allowing calculation of accident probability based on extreme value theory. The risk portion of the flight risk index is designed to account for different levels of flight risk and to provide criteria to allow pilots’ decision-making. Numerical examples are carried out by a series of simulated elevator overshoots of various levels and different distributions of ice accretion to compare the risk index under different icing conditions.
Findings
Case results show that the proposed methodology is able to analyze conditions of different severity and distribution of icing and assess quantitatively how these different parameters affect flight safety.
Practical implications
The quantification of flight risk in icing conditions demonstrated here can be applied to provide an objective and intuitive instrument to facilitate decisions by the aircrew or air traffic controller, especially prior to the aircraft entering into areas with adverse meteorological conditions.
Originality/value
Existing flight risk assessments under icing conditions are typically guided by aerodynamic changes, ice accumulation process or the subjective feeling of the pilot. Here, it is proposed to use the probability of flight risk event to measure different icing intensity levels in a quantitative way. This quantitative metric combines the alteration of aerodynamic characteristics, flight dynamic characteristics and limitation of critical parameters, providing a new and comprehensive viewpoint to measure in-flight icing risk. This may be a promising and more reasonable way to assess the risk.
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