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- W2084771799 abstract "In this paper, we present a study on the aerodynamic shape optimization of a three-dimensional subsonic enginenacelle using computational fluid dynamics simulations. Gaussian process-based surrogate modeling (kriging) andparameter screening techniques are combined to tackle the high cost associated with both computational fluiddynamics simulations and the large number of design variables involved, with a multi-objective genetic algorithmbeing used to obtain the Pareto fronts. The primary goal of the study was to identify the tradeoff betweenaerodynamic performance and noise effects associated with various geometric features within practicalcomputational costs. The fan face total pressure recovery is used to measure the aerodynamic performance, and thescarf angle is used as an indicator of the noise impact on the ground. The geometry is modeled using a feature-basedparametric computer-aided design package. An unstructured tetrahedral mesh is generated for the subsequentsolution using the Reynolds averaged Navier–Stokes flow equations. Analyses of variance techniques are used toidentify the dominant geometry parameters, thereby reducing the number of design variables and computationalcost in the trade study. Multiple Pareto fronts are constructed using progressively built kriging models based onsimulation data with the reduced parameter set. A full-scale search was also carried out for comparison with theresults produced using the reduced parameter set. The procedures outlined can be further applied to otheroptimization problems with significant numbers of parameters and high-fidelity analysis codes." @default.
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- W2084771799 date "2007-10-01" @default.
- W2084771799 modified "2023-09-25" @default.
- W2084771799 title "Surrogate-Based Aerodynamic Shape Optimization of a Civil Aircraft Engine Nacelle" @default.
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- W2084771799 doi "https://doi.org/10.2514/1.30015" @default.
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