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Detached Eddy Simulation for Industrial Aerodynamics (DESIDER)

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We have all fastened our seatbelts at the captain’s warning that we are experiencing turbulence. Turbulent airflow is by nature rough, caused by eddying of air leading to non-laminar flow of airstreams.

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Aside from natural occurrences in the air around the aircraft, turbulent flow also occurs over the contour of airplane wings and can result in loss of lift, a high degree of drag and increased noise among others. The ‘Detached eddy simulation for industrial aerodynamics’ (Desider) project was designed to develop simulation methods for the aeronautics industry that offer enhanced predictive capability for complex turbulent airflows. Predictive models can then be used in research and development for designs that minimise turbulent airflow. Specifically, the researchers sought to minimise the weaknesses inherent in existing turbulence-resolving approaches, including detached eddy simulation (DES), Reynolds-Averaged Navier-Stokes Large Eddy Simulation (RANS-LES) hybrids and scale adaptive simulation (SAS). The Desider project applied advanced numerical modelling techniques based on the DES approach to unsteady airflows and produced LES-comparable results with less costly computational resources. In addition, the researchers demonstrated the relevance of hybrid RANS-LES approaches to predicting inherently turbulent airflow in specific industrially relevant flow cases such as wakes and buffeting. Furthermore, based on multi-disciplinary expertise of consortium members, the investigators demonstrated the relevance of the hybrid RANS-LES approaches to other areas including noise reduction, weight reduction, analysis of unsteady loads and fatigue, as well as safety issues. Finally, the Desider project fostered collaboration and information dissemination among other industries, such as those involved in airframe, helicopter, turbo-engine and ground transportation manufacturing. In summary, the funding provided to the Desider project research team has helped increase the predictive accuracy of hybrid RANS-LES methods as applied to computational fluid dynamics and should help the European aeronautics industry become a leader in design and manufacturing for decreased turbulence, noise and weight.

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