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Journal of Marine Science and Technology

, Volume 24, Issue 4, pp 1043–1056 | Cite as

An efficient calibration approach for cavitation model constants based on OpenFOAM platform

  • Houcun Zhou
  • Min XiangEmail author
  • Patrick N. Okolo
  • Zeping Wu
  • Gareth J. Bennett
  • Weihua Zhang
Original article
  • 233 Downloads

Abstract

To precisely capture the cavitation process, it is essential to establish physical and mathematical models that describes the thermodynamic process between liquid and vapor. However, most mass transfer models represented by the cavitation model involves numbers of empirical constants which are case specific. The calibration for the cavitation model constants is therefore required for accurate numerical simulations. In this paper, a rapid and effective calibration approach for model coefficients using a surrogate-based approximate optimization (SAO) strategy is established based on OpenFOAM platform. Coefficients calibration has been carried out for the Kunz cavitation model using both two-dimensional and three-dimensional hydrofoil experimental data. The selection law for the Kunz model constants which defines a specific region that would guarantee low levels of errors is obtained, implying the mass transfer mechanism between gas and liquid. Furthermore, the optimized values for the model constants are gained. Validations have been carried out using the cases of the three-dimensional hemispherical head-form. Results show that the optimal constants perform much better in cavitation predictions. The proposed calibration method is validated for feasibility and efficiency for cavitation model constant calibration and can also be applied for the other models with various empirical constants.

Keywords

Cavitation model Optimization Calibration Numerical simulation OpenFOAM 

Notes

Acknowledgements

The authors gratefully acknowledge support by the National Nature Science Foundation of China (NSFC, Grant nos. 51776221, 61872380) and foundation of State Key Laboratory of High Performance Computing of China (Grant no. 201803-01).

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Copyright information

© JASNAOE 2018

Authors and Affiliations

  • Houcun Zhou
    • 1
  • Min Xiang
    • 1
    Email author
  • Patrick N. Okolo
    • 2
  • Zeping Wu
    • 1
  • Gareth J. Bennett
    • 2
  • Weihua Zhang
    • 1
  1. 1.National University of Defense TechnologyChangshaChina
  2. 2.University of Dublin, Trinity CollegeDublinIreland

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