Mathematical modeling of objects functioning and technical means for airfield control ensuring process

Abstract

In civil aviation primary focus is on the quality of fuel filled in the aircraft fuel tanks, as one of the components of flight safety ensuring. The introduction of digital technologies and trends in automation, digitalization of modern civil aviation aircraft provision are becoming the basic tool for civil aviation refueling complexes in terms of ensuring flight safety of civil aviation aircraft. This article considers the processes of airfield control that take place in the stationary operating conditions of refueling complexes of civil aviation airports as Markov processes and studies the approaches to their mathematical modeling. The authors claim that in the case of disruption, there is a transition from Markov to Poisson processes, which mathematical description requires different approaches. The practical application of these statements is obvious in the study of the states probabilities value as a function of time t. For practical purposes, the limiting probabilities of states at t→∞ are of interest. This creates conditions for entering new variables, such as performance and others. Thus, Markov processes allow us to apply the mathematical apparatus of operations research, where the system of states is transformed into the queuing system. To maintain Markov processes, the authors suggest giving due consideration to the objects and technical means of airfield control functioning including: retrofitting of filling points and refueling facilities with closed sampling systems, operational measurement of aviation fuel quality indicators and registration of their results, automated monitoring of filter elements condition while refueling and its blocking in the case of stochastic differential pressure beyond the specified indicators. A special novelty is the view on the measuring process of the aircraft refueling operations as an integral part of airfield control, using block chain technologies as an advanced application of Markov chains.