Establishing a framework for dynamic risk management in 'intelligent' aero-engine control

The behaviour of control functions in safety critical software systems is typically bounded to prevent the occurrence of known system level hazards. These bounds are typically derived through safety analyses and can be implemented through the use of necessary design features. However, the unpredictability of real world problems can result in changes in the operating context that may invalidate the behavioural bounds themselves, for example, unexpected hazardous operating contexts as a result of failures or degradation. For highly complex problems it may be infeasible to determine the precise desired behavioural bounds of a function that addresses or minimises risk for hazardous operation cases prior to deployment. This paper presents an overview of the safety challenges associated with such a problem and how such problems might be addressed. A self-management framework is proposed that performs on-line risk management. The features of the framework are shown in context of employing intelligent adaptive controllers operating within complex and highly dynamic problem domains such as Gas-Turbine Aero Engine control. Safety assurance arguments enabled by the framework necessary for certification are also outlined

Near Magnetic Field of a Small Turbojet Engine

Different parameters like temperatures, pressures, speed, and vibrations are used in evaluation of technical state of turbojet engines. The article presents a pioneering idea to expand this set of parameters with measurements of distortions in magnetic field in a close vicinity of the engine to obtain more information about its state, which can be further used in its diagnostic and control systems. We believe that deviations in near magnetic field can hold valuable information, which can be used to predict malfunctions and evaluate the condition of the engine. The presented article shows pilot experimental results and gives answer to the basic hypothesis, if such measurements can be realized using a small turbojet engine, as well if there are significant changes in near magnetic field, which would warrant further research in the area

Educational model for evaluation of airport NIS security for safe and sustainable air transport

One of the praxeological problems of safe and sustainable air transport (airfreight transport/air cargo, and air passenger transport) is the prevention and management of risks by competent staff, with the support of modern information and communication technologies. This paper presents an educational information model and software for the airport network and information systems risk assessment, primarily intended for aviation education and training of professionals for ensuring safe and sustainable air transport. The solution to the problem is based on the application of the fuzzy logic method in the air transport environment. Based on a fuzzy expert model, the selected scenario, and the input data established separately for airport assets by a group of 23 experts from aviation practice and a university, the following three assessments of airport network information system assets were constructed: Asset A2 (meteorological information systems) has an insignificant risk with an estimated 0.1162, and assets A1 (air traffic control and management (ATM), navigational aids and approach) and A3 (runway monitoring system) received a low risk of airport network and information systems (NIS) security with ratings of 0.2623 and 0.2915, respectively. An airport NIS risk assessment was aggregated (0.2288), indicating a low degree of security risk to the airport's network and information systems. The aggregated risk assessment of airport NIS, including financial loss data, was calculated as 0.1438, representing a low degree of security risk to the airport's network and information systems. Scenarios for evaluating airport assets are changing for students during education. The results of the developed model and its software will be part of the Simulation Center of the Faculty of Aeronautics. © 2020 by the authors

Erratum: Correction: A Fuzzy Model of Risk Assessment for Environmental Start-Up Projects in the Air Transport Sector. Int. J. Environ. Res. Public Health 2019, 16, 3753 (International journal of environmental research and public health (2019) 16 19 PII: E4850)

The authors wish to make the following correction to their paper [...]