On Resistance Reduction of a Hull by Trim Optimization

Lyu, Xujian; Tu, Haiwen; Xie, De; Sun, Jichao

doi:10.21278/brod69101

Cited by 20 publications

(8 citation statements)

References 11 publications

(12 reference statements)

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“…The ship's crew could set an operating speed pattern or undertake cargo shifts to optimize trim. Trim optimization was regarded as one of the simplest and easiest techniques for improving ship performance, specifically ship resistance (Lyu et al, 2018) and reducing fuel consumption (Sherbaz & Duan, 2014). Trim optimization at various speeds and drafts may be a simple and efficient method for boats to reduce resistance for increasing efficiency energy, decreasing fuel consumption, and restricting hazardous emissions (Islam & Soares, 2019).…”

Section: Resultsmentioning

confidence: 99%

Experimental and Computational Fluid Dynamics Investigations into the Effect of Loading Condition on Resistance of Hard-Chine Semi Planning Crew Boat

Riyadi¹,

Aryawan²,

Utama³

2022

IJTech

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Nowadays, the issue of energy efficiency in the maritime transportation sector has been strongly associated with the decreasing use of fossil energy and greenhouse gas emissions. Crew boats are one of the ship modes which consumes a lot of fuel in maritime transportation. This affects the number of exhaust gases released into the atmosphere. A study into the estimation of crew boat resistance was carried out experimentally using a towing tank, numerically using a CFD methodology, and then compared with Savitsky's method. Measurements were taken in calm waters under even keel and trim scenarios, considering load variation had been adjusted for. Determining the correct load position affected the LCG (Longitudinal Center of Gravity) and VCG (Vertical Center of Gravity) parameters, affected trim, and decreased crew boat resistance. Overall results showed that the experimental test, CFD method, and the empirical estimation from Savitsky were in good agreement with average errors up to 3%. The calculation results demonstrated that trim had a greater influence on decreasing resistance up to 3.062% than even keel position. Furthermore, the shifting of LCG had a more significant effect than that of VCG in the context of resistance changes.

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Section: Resultsmentioning

confidence: 99%

Experimental and Computational Fluid Dynamics Investigations into the Effect of Loading Condition on Resistance of Hard-Chine Semi Planning Crew Boat

Riyadi¹,

Aryawan²,

Utama³

2022

IJTech

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“…Generally, the ship has been optimized to achieve minimum drag after the hull design [15]. Usually in even keel or trim by stern condition for most ships.…”

Section: Trim Angle Validationmentioning

confidence: 99%

Biomimetics Design Optimization and Drag Reduction Analysis for Indonesia N219 Seaplanes Catamaran Float

Utomo¹,

Gunawan²,

Yanuar³

2021

Processes

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Design optimization on the Indonesia N219 seaplane catamaran is necessary to provide better service to rural islands of Indonesia. This research aims at decreasing drag using a design based on biomimicry by imitating the hydrodynamic characteristics of sailfish (Istiophorus platypterus) for pontoon floats. The design is then validated using a numerical fluid test using ANSYS Fluent to see the reduction in drag due to the change from a conventional or Wipeline® 13000 design to a biomimetics adaptation design. Next, further optimization was carried out based on the adaptation design based on trim tests, clearance tests, and deadrise angle dimensions suitable for biomimicry designs at Froude number speeds of 0.4 to 0.7. The design results with the adaptation of biomimicry show that a change in the design with this optimization affects a drag reduction that reaches 30% of the total drag generated by the conventional design.

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“…Crudu et al [13] modified the bulb immersion in the Holtrop and Mennen method to estimate the resistance of a 3700 dwt chemical tanker. CFDs simulations offer a viable alternative to towing tank tests [14] and are widely used in ship resistance prediction [15][16][17][18]. The factors that affect the CFDs calculation results are computational grids, turbulence models, etc.…”

Section: Introductionmentioning

confidence: 99%

Research on Ship Resistance Prediction Using Machine Learning with Different Samples

Yang,

Zhang,

Zhao

et al. 2024

JMSE

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Resistance serves as a critical performance metric for ships. Swift and accurate resistance prediction can enhance ship design efficiency. Currently, methods for determining ship resistance encompass model tests, estimation techniques, and computational fluid dynamics (CFDs) simulations. There is a need to improve the prediction speed or accuracy of these methods. Machine learning is gradually emerging as a method applied in the field of ship research. This study aims to investigate ship resistance prediction methods utilizing machine learning across various datasets. This study proposes two methods: employing stacking ensemble learning to enhance resistance prediction accuracy with identical ship samples and utilizing various ship resistance prediction models for accurate resistance prediction through transfer learning. Initially focusing on container ships as the research subject, the stacking ensemble learning model outperforms the basic machine learning model, the Holtrop and Mennen method, and the updated Guldhammer and Harvald method based on comparative prediction results. Subsequently, the container ship resistance prediction model achieves precise resistance prediction for bulk carriers. This study offers dependable guidance for applying machine learning in predicting ship hydrodynamic performance.

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On Resistance Reduction of a Hull by Trim Optimization

Cited by 20 publications

References 11 publications

Experimental and Computational Fluid Dynamics Investigations into the Effect of Loading Condition on Resistance of Hard-Chine Semi Planning Crew Boat

Experimental and Computational Fluid Dynamics Investigations into the Effect of Loading Condition on Resistance of Hard-Chine Semi Planning Crew Boat

Biomimetics Design Optimization and Drag Reduction Analysis for Indonesia N219 Seaplanes Catamaran Float

Research on Ship Resistance Prediction Using Machine Learning with Different Samples

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