System Noise Prediction Uncertainty Quantification for a Hybrid Wing–Body Transport Concept

Abstract

Aircraft system noise prediction for advanced, unconventional concepts has undergone significant improvement over the past two decades. Prediction model uncertainty quantification is necessary to reliably assess the potential benefits of unconventional configurations, which can be outside the range of empirical models. This paper builds on previous work to improve estimates of element prediction uncertainties where the model has improved, or new validation data are available. These element-level uncertainties are propagated via a Monte Carlo method to the system level for predictions at each of the three certification points. Although the quantitative uncertainty values contained here are specific to the hybrid wing–body configuration presented, the underlying process is the same regardless of configuration. Comparisons with previous work show a reduction of 1.1 EPNdB in the 95% coverage interval of the cumulative noise level. The largest impediment for continued uncertainty reduction is the need for validation experiments and improved modeling of fan source noise, propulsion airframe aeroacoustic effects, and the Krueger flap source noise, which comprise the bulk of the uncertainty in the cumulative certification noise level.