Journal of Shanghai Jiao Tong University ›› 2023, Vol. 57 ›› Issue (2): 168-176.doi: 10.16183/j.cnki.jsjtu.2021.305

Special Issue: 《上海交通大学学报》2023年“船舶海洋与建筑工程”专题

• Naval Architecture, Ocean and Civil Engineering • Previous Articles     Next Articles

Numerical Simulation of Crashback Condition of a Propeller Based on OpenFOAM

GUO Haipeng1, ZOU Zaojian2(), LI Guangnian1   

  1. 1. Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, Zhejiang, China
    2. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2021-08-06 Revised:2021-11-19 Accepted:2021-12-03 Online:2023-02-28 Published:2023-03-01
  • Contact: ZOU Zaojian E-mail:zjzou@sjtu.edu.cn.

Abstract:

The hydrodynamic characteristics of a propeller under the crashback condition are closely related to the crash stopping ability of a ship, which directly affect the ship navigational safety. In this paper, a numerical study on the hydrodynamic characteristics of a propeller and the flow field around the propeller under the crashback condition is conducted based on the Reynolds-averaged Navier-Stokes solver in the open source computational fluid dynamics platform OpenFOAM. Taking the 5-blade propeller DTMB4381 model as the study object, the ahead and crashback conditions are numerically simulated. The numerical results are compared with international open model test data to validate the effectiveness of the numerical method in the prediction of the hydrodynamic characteristics of the propeller under different conditions. Based on the obtained hydrodynamic loads and flow field details, the local flow field characteristics changing with the advance velocity and the relation between the local flow fields and the global hydrodynamic forces are explored, which provides theoretical basis for the evaluation of ship crash stopping ability.

Key words: propeller crashback, hydrodynamic characteristics, computational fluid dynamics (CFD), OpenFOAM, Reynolds-averaged Navier-Stokes (RANS) method

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