Dynamic Model of a Semi-Submersible Platform for the Development of Ballast Control Systems

Samyn, Leandro Marques; Paulo, José; Cunha, José Paulo V. S.

doi:10.3182/20090916-3-br-3001.0067

Cited by 5 publications

(2 citation statements)

References 6 publications

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“…Manzi et al [12] designed a ballast system with a human-computer interaction interface on the basis of the original ballast system to improve the ballast efficiency. Samyn et al [13] established a six-free-degree dynamic ballast water-control system for a semi-submersible platform by taking into account the effects of ballast tank weight, inertia, and moment. Woods et al [14] designed two sets of unique variable ballast devices to realize the automatic allocation of the ballast water for controling the launching depth, center of gravity, and inclination angle of the Autonomous Underwater Vehicle (AUV).…”

Section: Crane Ballast Systemmentioning

confidence: 99%

Point-to-Point-Based Optimization Method of Ballast Water Allocation for Revolving Floating Cranes with Experimental Verification

Wang,

Yu,

et al. 2024

JMSE

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The Revolving Floating Crane (RFC) is a specialized engineering vessel crucial for offshore lifting operations, such as offshore platform construction and deep-water salvaging. It boasts impressive lifting capacity, good adaptability to various environmental conditions, and high operational efficiency. Conventionally, the safety and stability of RFC operations heavily depend on manual ballast water allocation, which is directly influenced by factors such as personnel status and sea conditions. These manual operations often result in reduced lifting efficiency, higher energy consumption, and compromised operational safety. In response, this paper introduces a ballast water-allocation approach based on the Point-to-Point (PTP) theory for the intelligent operation process of the RFC. The fundamental principles of the PTP theory are analyzed, and a method tailored to optimize ballast water allocation for RFC is proposed. Considering the unique characteristics of the ballast system and the specific requirements of lifting operations, an optimization model for PTP-based ballast water allocation is established. Numerical experiments are conducted to verify the efficacy and reliability of the proposed method. Comparing it to the conventional approaches, the results demonstrate a notable 17.75% reduction in energy consumption and an impressive 73.49% decrease in decision-making time, showcasing the superiority of the proposed approach. Finally, the engineering feasibility of the PTP-based optimization method for ballast water allocation is validated through actual lifting experiments, underscoring its potential to enhance RFC operations.

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Section: Crane Ballast Systemmentioning

confidence: 99%

Point-to-Point-Based Optimization Method of Ballast Water Allocation for Revolving Floating Cranes with Experimental Verification

Wang,

Yu,

et al. 2024

JMSE

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“…For the optimization modeling and solving algorithm, Pan et al [3] proposed a mathematical model of ballast water adjustment for the FC, which calculates the ballast water allocation mass when the crane arm rotates at each unit angle. Combining the influence of ballast tank mass, inertia and moment, Samyn et al [4] proposed a six-degree-of-freedom dynamic ballast water control system for semi-submersible platforms. Chen et al [5] proposed a hover control based on LI adaptive theory for the submarine, and established the ballast tank and submarine dynamics model.…”

Section: Introductionmentioning

confidence: 99%

Ballast Water Dynamic Allocation Optimization for Revolving Floating Cranes Based on a Hybrid Algorithm of Fuzzy-Particle Swarm Optimization with Domain Knowledge

Liu

et al. 2022

JMSE

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Ballast systems and ballast water dynamic allocation between ballast tanks are very important for ensuring the offshore operation efficiency and safety of the revolving floating crane (RFC). Its modeling and solving have multiple difficulties such as modeling complexity, solving complexity and engineering practicability. Early studies showed that domain knowledge is of great significance for the optimization of the design quality and innovation of such complex engineering issues. By analyzing the coupled operation process characteristics among the floating crane, ship hull and ballast system, a ballast water allocation optimization model based on dynamic programming strategy is established. The domain knowledge of ship ballasting is extracted, and a domain knowledge base of expert experience rules for the ballast water allocation is established. A Fuzzy-Particle Swarm Optimization (FPSO) algorithm is given to obtain the optimal allocation scheme, which uses fuzzy logic inference to process domain knowledge and improve the solving quality. Three different cases are given to illustrate the validity of the proposed model and algorithm by comparing it with other algorithms. The analysis results show that the established optimization method can effectively improve the operation efficiency and reduce the calculation time and the number of ballast tanks involved in allocation, which makes the optimal scheme more suitable for engineering applications.

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Ballast water dynamic allocation optimization model and analysis for safe and reliable operation of floating cranes

Liu

Jiang

Gan³

et al. 2019

Ann Oper Res

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Dynamic Model of a Semi-Submersible Platform for the Development of Ballast Control Systems

Cited by 5 publications

References 6 publications

Point-to-Point-Based Optimization Method of Ballast Water Allocation for Revolving Floating Cranes with Experimental Verification

Point-to-Point-Based Optimization Method of Ballast Water Allocation for Revolving Floating Cranes with Experimental Verification

Ballast Water Dynamic Allocation Optimization for Revolving Floating Cranes Based on a Hybrid Algorithm of Fuzzy-Particle Swarm Optimization with Domain Knowledge

Ballast water dynamic allocation optimization model and analysis for safe and reliable operation of floating cranes

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