The noise signature of contemporary turbofan engines is dominated by fan noise, both tonal and broadband. Accepted methods for predicting the tone noise have existed for many years. As well, engine designers have methods for controlling or treating tonal noise. This is not the case for broadband noise. Thus, further reductions in engine noise will require accurate prediction methods for the broadband noise from the engine fan to enable design decisions. Interaction noise from the fan-stage is a dominant broadband mechanism in a modern high bypass engine and is created by the interaction of the turbulence in the fan-wakes with the fan exit guide vanes (FEGVs). This project will leverage prior development of low-order models for the prediction of fan broadband interaction noise. Gaps in the low-order approach will be addressed based on knowledge gained from computation and experimentation.
Fan broadband noise, particularly in the aft direction, is a dominant source for future engines. Engine designers that have access to fast and accurate predictions of fan-stage broadband interaction noise can include this outcome as a design variable. Current fan broadband models rely on a multitude of simplifying assumptions that make them unable to simulate some realistic cases. Also, they require accurate representation of the fan-wake turbulence rendering them reliant on long runtime computations. The proposed research will address both of these shortcomings and deliver a faster, more applicable, fan broadband prediction method.