• Title/Summary/Keyword: Low Fidelity Solver

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Accuracy Improvement of Low Fidelity Solver by Augmentation of Fin Aerodynamic Database (공력 조종면 데이터베이스 확장을 통한 저 충실도 해석자의 정확도 개선)

  • Kang, Eunji;Kim, Younghwa;Yim, Kyungjin;Lee, Jae Eun;Kang, Kyoung-Tai
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.1
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    • pp.45-54
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    • 2022
  • There has been necessity to supplement the fin database to improve the accuracy of low-fidelity aerodynamic solver for missile configuration. In this study, fin database is expanded by in-house solver, utilized in the triservice data the previously established into regions beyond means of CFD. Fin alone data of CFD analysis results in the original region is matched well with triservice data originated from the wind tunnel tests. Extensive fin aerodynamic data from CFD analysis is added to the existing database of the low-fidelity solver. For confirmation, aerodynamic characteristics of body-tail and body-canard-tail missile configurations is computed using upgraded low-fidelity solver at transonic region. The result using improved solver shows good agreements with wind tunnel test and CFD analysis results, which implies that it becomes more accurate.

Physics-based Surrogate Optimization of Francis Turbine Runner Blades, Using Mesh Adaptive Direct Search and Evolutionary Algorithms

  • Bahrami, Salman;Tribes, Christophe;von Fellenberg, Sven;Vu, Thi C.;Guibault, Francois
    • International Journal of Fluid Machinery and Systems
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    • v.8 no.3
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    • pp.209-219
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    • 2015
  • A robust multi-fidelity optimization methodology has been developed, focusing on efficiently handling industrial runner design of hydraulic Francis turbines. The computational task is split between low- and high-fidelity phases in order to properly balance the CFD cost and required accuracy in different design stages. In the low-fidelity phase, a physics-based surrogate optimization loop manages a large number of iterative optimization evaluations. Two derivative-free optimization methods use an inviscid flow solver as a physics-based surrogate to obtain the main characteristics of a good design in a relatively fast iterative process. The case study of a runner design for a low-head Francis turbine indicates advantages of integrating two derivative-free optimization algorithms with different local- and global search capabilities.