Safety Assessment of Critical Aircraft Systems Under Multisource Uncertainty Based on Evidence Network

As civil aircraft components become more autonomous in China, airworthiness certification is facing the problem of insufficient failure data, leading to challenges in terms of uncertainty. Traditional probabilistic models struggle to effectively integrate multisource uncertainties, limiting their application in data‐scarce scenarios. This study therefore proposes a framework based on evidential networks for quantifying uncertainty risk, including: (1) classifying the failure rates of bottom events into handbook data, flight operation data, and expert experience; (2) quantifying uncertainties through log‐normal distributions and evidence combination rules; (3) converting fault trees into evidential networks and propagating uncertainties through logical gates. In the analysis of the flap control system, the probability intervals for catastrophic failure condition uncommanded motion of flaps are [3.449 × 10 −11  and 4.811 × 10 −9 ]. After the improved pignistic decision probability transformation, the point estimate is 1.638 × 10 −9 . For the eVTOL aircraft power system, the failure probability intervals of the catastrophic failure condition battery thermal runaway causes uncontrolled fire are [1.604 × 10 −10  and 2.287 × 10 −9 ], with a point estimate of 9.227 × 10 −10 . The result shows that by accommodating heterogeneous data sources and transparently propagating uncertainties, this method demonstrates significant applicability in both traditional aircraft components and new eVTOL aircraft systems, highlighting its effectiveness. It provides an extensible framework for safety assessment and airworthiness certification.