Probabilistic Assessment for Structural Failure Severity of Aero‐Engine Components in Fire Scenarios Based on Cumulative Failure Frequency

Fire accidents can cause severe damage to aircraft and jeopardize passenger safety. Current research on civil aviation safety generally focuses on guaranteeing continued operational safety and airworthiness, typically treating fire as a potential hazard or risk factor. In addition, fire prevention design in civil aviation is generally based on pessimistic assumptions that components have lost their intended functions in fire scenarios, leading to redundant or inadequate fire prevention design. Therefore, this paper proposes a probabilistic assessment methodology for structural failure severity of aero‐engine components in fire scenarios based on cumulative failure frequency (CFF). The proposed methodology first considers all possible combinations of fire scenarios that may occur in an aero‐engine by discretizing the probability distributions of the random variables associated with these scenarios. Subsequently, fire simulation using the fire dynamics simulator in conjunction with heat transfer analysis is carried out to determine the temperature distribution of structural elements. To enhance the computational efficiency of consequence analysis, a temperature approximation model based on the extreme learning machine is then introduced to reduce computational burden. Finally, structural failure severity is quantified by identifying the state of each structural element with the inclusion of the transition state and calculating the corresponding CFF. A case study is presented to demonstrate the applicability of the proposed methodology in identifying critical structural elements in fire scenarios, thereby validating its practicality and effectiveness.