Multi-point aerodynamic design and optimization of a nacelle for an electric fan
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Examensarbete för masterexamen
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Model builders
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Abstract
Engines that power commercial airliners are becoming more carbon neutral as
propulsion technologies are evolving at a rapid pace, targeting progressive decarbonization
goals. Electrification of sub-regional aircraft could be an initial step in
controlling emissions in the skies. In accordance with this goal, GKN Aerospace
has been leading the EleFanT project that is aimed at developing an electric fan
thruster for an electric aircraft. The present multi-point aerodynamic design of
the nacelle is done as a part of the Electric Fan thruster (EleFanT) project. A multiobjective
shape optimization method was implemented to obtain an initial set of
axisymmetric shape parameters for nacelle and nozzle geometries. The optimization
workflow consists of a non-dominated sorting genetic algorithm (NSGA-II),
coupled with 2-D axisymmetric Reynolds Averaged Navier Stokes (RANS) equations
based CFD code. The good designs from 2-D cruise studies were subjected
to multi-point analysis, where the 3-D asymmetric flow fields from various operating
points like cruise, take-off and crosswind were studied. The aerodynamic
drag and thrust coefficients and the engine performance metrics were recorded
using a defined bookkeeping method. For the 3-D simulations, a validated faninlet
coupling model, the modified parallel compressor (MPC) method was employed
at the fan face boundary to adapt to the incoming flow distortions. Thorough
investigations on inlet drooping were done to analyze its positive impact on
intake aerodynamics. With drooping, besides a reduction in drag coefficient Cd
at cruise, mitigation of intake flow separation and distortion at take-off was also
achieved. Further, a small increment done to the highlight radius at the lower
position of the nacelle gave sizeable reductions in incoming flow distortion at the
fan face.
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Keywords
aerodynamic design, multi-objective optimization, nacelle design, multi-point analysis, CFD
