Predicting and decreasing airframe noise
An ambitious goal of the Advisory Council for Aviation Research and Innovation in Europe (ACARE) is a 50 % reduction in the perceived noise level of fixed-wing aircraft by 2020. Airframe noise (AFN) is a major contributor to the overall noise emitted by modern aircraft. With increasing emphasis on virtual prototyping, accurate models of AFN are critical. However, the complexity and diversity of broadband turbulent AFN sources make prediction and subsequent design for noise reduction a challenging task. The EU-funded project 'Validation and improvement of airframe noise prediction tools' (VALIANT) simplified the complexity. Researchers focused on test case configurations representing the main broadband AFN mechanisms, namely landing gears and high-lift devices. The generic simplified test cases were chosen to validate and improve noise prediction to be later applied in realistic full-scale airframes. Researchers evaluated the components of the noise generation chain and their mutual interactions, enabling the development of an experimental database and numerical predictive tools. VALIANT delivered efficient and reliable numerical approaches to AFN prediction together with an experimental database and increased insight into noise mechanisms. Outcomes pave the way for future optimisations of predictive tools, leading to reduced computational load and increased accuracy. Developments will facilitate design breakthroughs for quieter aircraft, thus satisfying ACARE's vision.
