Abstract:Uncertainty analysis effectively enhances the robustness of aero-engine design. This study proposes a method that integrates Monte Carlo simulation to develop an engine performance prediction model that accounts for component-level parameter uncertainties. By generating a sample set of cycle parameters combinations, the uncertainty distribution of engine performance parameters and their compliance probabilities under different operating points are obtained. The performance realization levels at specified confidence levels are analyzed. The cycle parameter scheme meeting the design requirements is determined through comprehensive trade-offs between implementation risks under current technical capabilities and performance design margins. During the preliminary design phase of engine system concepts, the proposed method can effectively enhance the robustness of the design outcome and mitigate development risks. By comparing with the design specifications and experimental data of a specific engine type, both the rationality of its cycle parameter selection and the feasibility of the method proposed herein are demonstrated.
