Sea trials and application of a numerical method for the analysis of the ocean current displacement phenomena of demersal longlines

Lee, Jihoon; Lee, Chun‐Woo; Karlsen, Ludvig

doi:10.1016/j.oceaneng.2011.08.003

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…The mass added to the mass points was obtained from the following equation:

Δm = ρ_{italicsw} V_{N} K_{m}

where ρ sw is the density of seawater, V N is the volume of the mass points and K m is the added mass coefficient. The K m value of the floats and sinkers, regarded as spheres, was set to 1.5 (Takaki et al ., ; Wakaba and Balachandar, ; Lee CW et al ., ; Lee JH et al ., , ). Cylindrical structures, such as ropes, were described by the following equation:

K_{m} = 1 + sin α

where α is the angle of attack.…”

Section: Methodsmentioning

confidence: 99%

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Which factors strongly influence the sinking speed of a demersal longline?

Lee

Karlsen

et al. 2013

Aquatic Conservation

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Sinking speed is one of the main factors affecting the performance of longlines. Demersal and pelagic longlines need to sink quickly, to prevent bycatch of marine animals and bait loss to seabirds. The incidental catch or bycatch of seabirds by longlining is a problem from the environmental conservation point of view. Thus, it is necessary to develop techniques to reduce the incidental catch or bycatch by longlining. This study focuses on the sinking speed of longlines. To determine the significant factors that may influence the sinking speed, the study considers the various parameters for longlining such as bait properties, rope materials, rope thickness, anchor weights, shooting speeds, shooting methods, and the ratio between the depth and mainline length. The results of the numerical analysis were verified by comparing them with observations from field experiments. The results suggest that the sinking speed can be increased and the bycatch during the sinking process can be reduced when baits have elliptical shapes with a small projected area relative to the sinking orientation, as well as when high‐density and thicker materials are used. Heavier anchors also help to increase the sinking speed of the anchor part, excluding other parts such as the middle part of a mainline. If the water is shallow compared with the line's length, the anchor's weight has a smaller influence on the speed of sinking in the middle of the line. In this case, the factors that influence the sinking speed of a longline 10, 30, and 50 m from the stern are rope material, rope thickness, and shooting speed. These results may be used to design techniques for bycatch prevention. Based on these results, accounting for these important factors when designing a longline is expected to increase the fishing efficiency. Copyright © 2013 John Wiley & Sons, Ltd.

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“…The mass added to the mass points was obtained from the following equation:

Δm = ρ_{italicsw} V_{N} K_{m}

K_{m} = 1 + sin α

where α is the angle of attack.…”

Section: Methodsmentioning

confidence: 99%

“…resistance coefficient) of baits have not been dealt with by earlier research. Lee et al (2011) carried out analyses to define the hydrodynamic characteristics of baits in connection with various sinking orientations. The sinking speed of a longline is also influenced by shooting speeds and shooting methods employed.…”

Section: Introductionmentioning

confidence: 99%

Which factors strongly influence the sinking speed of a demersal longline?

Lee

Karlsen

et al. 2013

Aquatic Conservation

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“…To reduce the calculation loads, we used the approximation method, in which several actual meshes were bundled together into a virtual mathematical mesh having the same physical properties (e.g., mass, specific gravity, weight, projected area, hydrodynamic coefficients) (Lee et al, 2005a;Kim et al, 2007;Lee et al, 2008aLee et al, , 2011. It was assumed that the virtual mesh and the original mesh were geometrically identical; in other words, the angle between two adjacent virtual mesh bars and the angle of attack were the same as those of the original netting.…”

Section: Physical Modeling Of Fish Cagesmentioning

confidence: 99%

Dynamic behavior and deformation analysis of the fish cage system using mass-spring model

Lee

Park

2015

China Ocean Eng

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Fish cage systems are influenced by various oceanic conditions, and the movements and deformation of the system by the external forces can affect the safety of the system itself, as well as the species of fish being cultivated. Structural durability of the system against environmental factors has been major concern for the marine aquaculture system. In this research, a mathematical model and a simulation method were presented for analyzing the performance of the large-scale fish cage system influenced by current and waves. The cage system consisted of netting, mooring ropes, floats, sinkers and floating collar. All the elements were modeled by use of the mass-spring model. The structures were divided into finite elements and mass points were placed at the mid-point of each element, and mass points were connected by springs without mass. Each mass point was applied to external and internal forces, and total force was calculated in every integration step. The computation method was applied to the dynamic simulation of the actual fish cage systems rigged with synthetic fiber and copper wire simultaneously influenced by current and waves. Here, we also tried to find a relevant ratio between buoyancy and sinking force of the fish cages. The simulation results provide improved understanding of the behavior of the structure and valuable information concerning optimum ratio of the buoyancy to sinking force according to current speeds.

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“…where ρ sw is the density of seawater, ν N is the volume of the mass point, and K m is the added mass coefficient, which is 1.5 because the structural connections are considered to be spheres (Takagi et al, 2004;Wakaba and Balachandar, 2007;Lee, 2009). Cylindrical structures, such as ropes, are described as…”

Section: Mathematical Fishing-gear Modelmentioning

confidence: 99%

Applying Fishing-gear Simulation Software to Better Estimate Fished Space as Fishing Effort

Lee¹,

Lee²,

Choe³

et al. 2011

Fisheries and aquatic sciences

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Modeling fishing-gear systems is essential to better understand the factors affecting their movement and for devising strategies to control movement. In this study, we present a generalized mathematical modeling methodology to analyze fishing gear and its various components. Fishing gear can be divided into a finite number of elements that are connected with flexible lines. We use an algorithm to develop a numerical method that calculates precisely the shape and movement of the gear. Fishing-gear mathematical models have been used to develop software tools that can design and simulate dynamic movement of novel fishing-gear systems. The tool allowed us to predict the shape and motion of the gear based on changes in operation and gear design parameters. Furthermore, the tool accurately calculated the swept volume of towed gear and the surrounding volume of purse-seine gear. We analyzed the fished volume for trawl and purse-seine gear and proposed a new definition of fishing effort, incorporating the concept of fished space. This method may be useful for quantitative fishery research, which requires a good understanding of the selectivity and efficiency of fishing gear used in surveys.

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Sea trials and application of a numerical method for the analysis of the ocean current displacement phenomena of demersal longlines

Cited by 6 publications

References 8 publications

Which factors strongly influence the sinking speed of a demersal longline?

Which factors strongly influence the sinking speed of a demersal longline?

Dynamic behavior and deformation analysis of the fish cage system using mass-spring model

Applying Fishing-gear Simulation Software to Better Estimate Fished Space as Fishing Effort

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