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.
Fields of science
Call for proposal
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Funding SchemeCP-FP - Small or medium-scale focused research project
197198 Saint Petersburg