International Journal of Mathematical, Engineering and Management Sciences (Aug 2023)
Hierarchical Reliability Modelling and Analysis of Life Support System of Fighter Aircraft
Abstract
The paper proposes a hierarchical reliability modelling and assessment approach for a life support system (LSS) that provides oxygen to the pilot and is employed in a combat aircraft. The system has the primary function of generating oxygen onboard, and it has a backup gaseous oxygen tank as redundancy. An emergency oxygen bottle is also part of the ejection seat for emergency use. Both backup oxygen and emergency oxygen have a fixed capacity and a fixed duration of oxygen supply. Therefore, it is crucial to assess the reliability of the LSS to ensure its safety and effectiveness of this LSS during a mission by the combat aircraft. The proposed reliability model of LSS is developed as a two-level hierarchical model, that captures the inherent randomness in the operation of the system. At the lowest level of the hierarchy, Markov chains are used to model the events that may lead to the failure of the LSS. The events include the failure of individual components, the depletion of backup oxygen, and the depletion of emergency oxygen. The Markov chains consider the interactions between individual components and events during the mission profile. At the top level of the hierarchy, a fault tree is used to model the interactions between various events during the mission profile. The fault tree considers the interactions between individual events and the effects of redundancy on the reliability of the LSS. The results of the Markov chains at the lower level are exported to the higher level modelled via fault tree to find the overall system reliability. The reliability model is further extended to incorporate the deterministic nature of the LSS due to the fixed capacity of the backup tank and emergency bottle. The work addresses the modelling of six different scenarios of LSS operations. The modelling of these scenarios is achieved using Semi-Markov Processes (SMP), which allow the state holding time to be a general distribution.
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