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Identification of hydrodynamic derivatives and motion prediction for ship maneuvering based on the elliptic blending turbulence model
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Ming-tao DUAN, Yang BAI, Hai-jue XU, Jun-zheng LIU, Meng-chun QIN
Journal of Ship Mechanics | 2026, 30(8) : 1294 - 1307
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Journal of Ship Mechanics | 2026, 30(8): 1294-1307
• Hydrodynamics •
Identification of hydrodynamic derivatives and motion prediction for ship maneuvering based on the elliptic blending turbulence model
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Ming-tao DUAN, Yang BAI, Hai-jue XU, Jun-zheng LIU, Meng-chun QIN
Affiliations
  • State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin 300354, China
Published: 2026-08-15 doi: 10.3969/j.issn.1007-7294.2026.08.007
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To address the insufficient analytical accuracy of traditional turbulence models in simulating ship maneuvering flow characteristics, this study proposesd a hydrodynamic derivative identification method based on the Elliptic Blending (EB) turbulence model, aiming to improve the prediction accuracy of ship motion under complex maneuvering conditions. Taking the KCS ship as the object, the performance of the k-ε turbulence model, Shear Stress Transport (SST) k-ω turbulence model and EB turbulence model was compared in terms of flow stability and vortex-resolving capability. Based on the EB turbulence model, static drift and pure yaw simulations were conducted to identify hydrodynamic derivatives, which were then input into the MMG model to predict turning motions. The EB turbulence model significantly improves the resolution of flow with strong pressure gradients near the wall by reconstructing the Reynolds stress transport equations. It accurately captures the evolution of bilge vortex clusters and asymmetric stern vortices in static drift conditions. In pure yaw motion, it effectively represents the dynamic coupling between vortex intensity and free-surface fluctuations. For the 35° rudder angle turning prediction, the average deviations of tactical diameter and steady turning diameter are only 3.34% and 1.55%, respectively, representing a maximum accuracy improvement of over 30% compared to the k-ε turbulence model. The EB turbulence model demonstrates high fidelity in simulating ship maneuvering flow characteristics, enables accurate identification of hydrodynamic derivatives, provides reliable prediction of maneuvering motions, and offers a reliable tool for the safety assessment of actual ship navigation.

ship maneuverability  /  elliptic blending turbulence model  /  hydrodynamic derivatives  /  turning motion prediction
段明涛, 白洋, 徐海珏, 刘军政, 秦梦春. 基于椭圆混合湍流模型的船舶操纵水动力导数识别及运动预报. 船舶力学, 2026 , 30 (8) : 1294 -1307 . DOI: 10.3969/j.issn.1007-7294.2026.08.007
Ming-tao DUAN, Yang BAI, Hai-jue XU, Jun-zheng LIU, Meng-chun QIN. Identification of hydrodynamic derivatives and motion prediction for ship maneuvering based on the elliptic blending turbulence model[J]. Journal of Ship Mechanics, 2026 , 30 (8) : 1294 -1307 . DOI: 10.3969/j.issn.1007-7294.2026.08.007
Year 2026 volume 30 Issue 8
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doi: 10.3969/j.issn.1007-7294.2026.08.007
  • Receive Date:2026-03-02
  • Online Date:2026-11-03
  • Published:2026-08-15
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  • Received:2026-03-02
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    State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin 300354, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
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Percentage of
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Number of
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Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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