Application of Improved Particle Swarm Optimisation Algorithm in Hull form Optimisation

Zheng, Qiang; Feng, Bin; Liu, Zuyuan; Chang, Haichao

doi:10.3390/jmse9090955

Cited by 19 publications

(8 citation statements)

References 27 publications

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“…In marine engineering, PSO is applied in designing different vital parts. Zheng et al used PSO for hull form optimization of a ship and found acceptable improvement in performance [25]. Wang et al used multi-objective PSO to optimize ship energy efficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

Design Optimization of Marine Propeller using Elitist Particle Swarm Intelligence

Khan

Shoukat

Shah

et al. 2023

Preprint

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Marine transportation is still the primary source of global transportation. The propeller, which is a critical componentof the propulsion system, must be designed with multiple constraints and objectives to satisfy the need. Recent studies propose that utilizing an improved optimization algorithm and computational analysis would explore better designs than conventionalmethods. In the present study, Elitist Particle Swarm Optimization (EPSO) technique is implemented to optimize the design ofa marine propeller. Potsdam’s Conventional Propeller VP 1304 is used as a benchmark design case. Reynold’s Averaged NavierStokes equation based Computational Fluid Dynamics (CFD) along with Vortex Lattice Method (VLM) and Fluid StructureInteraction (FSI) model is used for computational analysis. The results obtained in this study are validated against the previously published experimental data. An optimized propeller design is proposed based on the Elitist Particle Swarm Optimization technique.It is observed that the proposed design shows improved open water performance for lower advance coefficient (J) valuesbased on the given constraints. It’s also observed that open water efficiency is improved by 7 percent for J=0.6 compared tothe original design. The one-way Fluid Structure Interaction analysis shows that the proposed design is structurally stable underopen water test conditions

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Section: Literature Reviewmentioning

confidence: 99%

Design Optimization of Marine Propeller using Elitist Particle Swarm Intelligence

Khan

Shoukat

Shah

et al. 2023

Preprint

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“…At present, PSO has been widely used to solve such engineering problems. The algorithm has the characteristics of high calculation efficiency, reliable calculation results and good optimization effect [11,27,30]. The optimization of PSO is shown in Figure 4.…”

Section: Standard Pso Algorithmmentioning

confidence: 99%

“…Liu et al [8][9][10] built the ballast water allocation optimization models for the FC with different ballast systems, and proposed a dynamic programming strategy and intelligent algorithms, and a numerical simulation combined with case analysis showed that the optimal scheme can effectively reduce the mass of ballast water allocation and improve the operation efficiency. Zheng et al [11] proposed an improved PSO algorithm to optimize the hull form of an engineering vessel to reduce the wave-making resistance coefficient under static constraints.…”

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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“…To optimize the shape of the tugboat hull, the Particle Swarm Optimization (PSO) method was used, already employed for this purpose by [42,43]. For optimization purposes, the constraints are introduced, granting invariability of the geometric parameters presented in Table 3, i.e., length, width and volume of displaced water.…”

Section: Hull Shape Optimizationmentioning

confidence: 99%

Analysis of Hull Shape Impact on Energy Consumption in an Electric Port Tugboat

Koznowski

Łebkowski

2022

Energies

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The trend to replace internal combustion engines with electric zero-emission drives, visible in the automotive industry, also exists in the shipbuilding industry. In contrary to land vehicles, the requirements for the electric propulsion system of tugs are much greater, which combined with the limited space and energy on board, makes any amount of energy valuable. Strategic changes in the policy of many countries, such as the “Fit for 55” package, introduce plans to significantly reduce CO2 emissions, which favors the development of alternative drives and their introduction to new areas of operation. This article presents that it is possible to reduce the amount of energy an electric tug spends for movement by applying the Particle Swarm Optimization method to modify the shape of its hull. A statistical analysis of public data was performed to determine the speed profiles of actual port tugs. The Van Oortmerssen method was used to determine the hull resistances of the proposed tug and the impact of the hull shape modification sets on reducing these resistances. Based on the six obtained speed profiles, it was determined that one of the tested variants of modifications made it possible to reduce energy consumption on average by 2.12%, to even 3.87% for one of the profiles, and that some modifications increase energy consumption by even 6.59%.

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Application of Improved Particle Swarm Optimisation Algorithm in Hull form Optimisation

Cited by 19 publications

References 27 publications

Design Optimization of Marine Propeller using Elitist Particle Swarm Intelligence

Design Optimization of Marine Propeller using Elitist Particle Swarm Intelligence

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

Analysis of Hull Shape Impact on Energy Consumption in an Electric Port Tugboat

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