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GO4HYBRID

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Cerrado

Grey Area Mitigation for Hybrid RANS LES Methods

The aeronautical industry lacks confidence in the accuracy of computational fluid dynamics (CFD) in areas of highly non-linear, unsteady flows close to the flight envelope borders, which demands advanced approaches and methods. Th... ver más

30/09/2015

CFDB

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

CFD SOFTWARE ENTWICKLUNGS UND FORSCHUNGSGESE... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 7 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2015-09-30 No tenemos la información de la convocatoria

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7 Participantes

CFDB

0.00€ | Lider

Royal Netherlands Aerospace...

N.D. | Participante

ONERA

N.D. | Participante

DLR

N.D. | Participante

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Líder del proyecto

CFD SOFTWARE ENTWICKLUNGS UND FORSCHUNGSGESE... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The aeronautical industry lacks confidence in the accuracy of computational fluid dynamics (CFD) in areas of highly non-linear, unsteady flows close to the flight envelope borders, which demands advanced approaches and methods. The family of Hybrid RANS-LES Methods (HRLM) is the best candidate for the next generation of CFD methods for increased fidelity at industrially-feasible expense. While HRLM have been proven to perform considerably better than conventional (U)RANS approaches in situations with strong or massive flow separation, they are hampered by the Grey Area issue once they have to deal with thin separation regions and where shear layer instabilities are weaker. As exactly these areas are of high importance for aircraft performance (lift, loads) the acceptance of HRLM strongly depends on the ability to mitigate the extent of the Grey Area (GA). With the new/advanced Grey Area mitigation approaches, the Go4Hybrid project offers hybrid RANS-LES methods that improve predictive capability with increased flexibility and reduced user decision load. Hence, the incentive for future use of these highly sophisticated methods goes in line with a considerably high impact: • Progress beyond the state-of-the-art for non-zonal methods is achieved by the development and demonstration of generally-applicable extensions to mitigate the Grey Area problem, thereby extending their applicability to important industrial flows at the performance frontiers. • For embedded methods, a focus will be placed on improving methods so that they are applicable to arbitrary complex geometries, as opposed to many existing techniques that require e.g. canonical boundary layer assumptions or homogeneous flow directions and are hence fundamentally less flexible. In general, development work will pursue a number of key goals contributing to extended applicability, improved accuracy, increased flexibility, reduced user decision load and increased Technology Readiness Level of hybrid approaches.

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