Abstract
Aerodynamic databases collected either by experimental or numerical approaches are relatively “local” in a large-scale design space, surrounding the reference configurations or operating conditions. However, the exploration of the design space requires knowledge of the “dark” space where few data is available. Therefore, the coupling of “remote” databases is necessary. Databases had been generated by performing CFD (Computational Fluid Dynamics) simulations with meshes morphed from different geometrical configurations. Then an ordinary least square method was used to obtain derivatives out of databases. Direct co-Kriging method was used to interpolate those derivative-integrated databases. Derivability studies were carried out on two main sub-models: regression model and correlation model. Appropriate models were proposed respectively. Referring to 2 geometries and 2 operating conditions, 4 second order integrated databases had been generated for an automotive engine cooling fan. Progressively database coupling shows the advantage of the proposed approach. Optimizations has been done to improve the fan performances at different operating conditions.
Supported by NSFC No.51575498.
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Zhang, Z., Buisson, M., Ferrand, P., Henner, M. (2020). Databases Coupling for Morphed-Mesh Simulations and Application on Fan Optimal Design. In: Le Thi, H., Le, H., Pham Dinh, T. (eds) Optimization of Complex Systems: Theory, Models, Algorithms and Applications. WCGO 2019. Advances in Intelligent Systems and Computing, vol 991. Springer, Cham. https://doi.org/10.1007/978-3-030-21803-4_97
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