Svoboda | Graniru | BBC Russia | Golosameriki | Facebook
Next Article in Journal
Express Diagnosis and Prediction of Remote Mass Mortality of Scallop Mizuhopecten yessoensis in Mariculture Farms Using Biomarkers
Previous Article in Journal
Design of Ship Trajectory Control Method Integrating Self Disturbance Rejection and Neural Network
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JMSE
Volume 12
Issue 7
10.3390/jmse12071150
jmse-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Research on Sea Trial Techniques for Motion Responses of HDPE Floating Rafts Used in Aquaculture

by
Fei Fu
1,2,
Xiaoying Zhang
1,*,
Zhe Hu
1,
Yan Li
1,
Lihe Wang
3 and
Jianxing Yu
1,2
1
School of Marine Engineering, Jimei University, Xiamen 361021, China
2
College of Mechanical and Marine Engineering, Beibu Gulf University, Qinzhou 535011, China
3
China Energy Engineering Group Guangdong Electric Power Design Institute Co., Ltd., Guangzhou 510663, China
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2024, 12(7), 1150; https://doi.org/10.3390/jmse12071150
Submission received: 9 May 2024 / Revised: 5 July 2024 / Accepted: 7 July 2024 / Published: 9 July 2024
(This article belongs to the Section Marine Aquaculture)
Browse Figures
Versions Notes

Abstract

:
The innovative aquaculture equipment known as high-density polyethylene (HDPE) floating rafts has gained popularity among fishermen in the southeast coastal regions of China. Compared to deep-water anti-wave fish cages, the construction costs of HDPE floating rafts are 50% to 75% less. There is a dearth of comprehensive publicly available records of HDPE floating rafts sea trial data, despite substantial numerical studies on the motion response of aquaculture fish cages and scale model experiments under controlled-wave conditions. This study involves sea trial techniques under operational and extreme environmental conditions for motion responses of HDPE floating rafts, presents a comprehensive procedure for sea trials of HDPE floating rafts, summarizes the issues encountered during the trials, and suggests solutions. Using MATLAB for independent programming, motion videos and photos collected from the sea trials are processed for image capture, yielding the original time history curve of vertical displacement. Based on the sea trials’ data, including motion displacement, acceleration, mooring line force, overall deformation patterns, and current and wave data, recommendations are provided for the design and layout of HDPE floating rafts. Based on the Fast Fourier Transform (FFT) method for spectral analysis, the influence of interference items on the observational data is eliminated; the rationality of the observational data is verified in conjunction with the results of the Gabor Transform. This study offers a scientific analytical method for the structural design and safe operation of HDPE floating rafts and provides a reference for subsequent numerical simulations.

1. Introduction

With the ever-increasing population, producing more high-quality and safe aquatic products to meet the growing demand for protein is a formidable task and challenge. According to the Food and Agriculture Organization of the United Nations (FAO) [1], in 2020, global aquaculture production reached a record 122.6 million tons, of which approximately 68.1 million tons came from marine and coastal aquaculture. Due to the limited acquisition of natural fishery resources, aquaculture is crucial to global food security [2,3,4]. It is predicted that by 2030, global aquaculture fish production will significantly increase to 106 million tons, a 32% increase from the 2020 figures [5]. The rapid development of large-scale aquaculture has generated substantial economic benefits, becoming one of the fastest-growing sectors in global agricultural production [6,7,8], with a growth rate of 8.6% [9].
The rapid growth and unplanned development of aquaculture have sparked public concern about ecological consequences [4]. The adverse effects such as water pollution [3,10], coastal vulnerability [11], greenhouse gas emissions [4,12], and micro-plastic/plastic pollution [13,14,15] have also constrained the further development of aquaculture [16]. In response, sustainable aquaculture production has received policy support and the attention of participants in the aquaculture industry [10].
Innovating marine aquaculture equipment is one of the effective pathways to achieve sustainable aquaculture, which holds significant importance for ensuring food safety, driving industry upgrades, and protecting the marine environment. Traditional floating rafts were constructed using bamboo, wood, and foam floats, with wooden walkway planks consuming a substantial amount of timber. The foam floats gradually disintegrate during their use, exerting a highly detrimental impact on the environment [17]. Coupled with their poor safety performance and short lifespan, such floating rafts are now being phased out. In waters between 10 and 20 m deep, high-density polyethylene (HDPE) floating rafts are a common piece of equipment used in nearshore aquaculture [18]. Aquaculture equipment has made widespread use of HDPE, which is recognized for its resilience to corrosion and low cost of raw materials [19], as illustrated in Figure 1.
Compared to circular cages, rectangular floating rafts have the following advantages:
  • Structural Stability: HDPE floating rafts exhibit superior structural stability, capable of supporting larger aquaculture cages, making them suitable for deep-sea farming;
  • Economic Benefits: HDPE floating rafts are easy to maintain and manage, coupled with longer service life and recyclability of materials, which can lead to better economic benefits in the long run;
  • Multifunctionality: HDPE floating rafts are not only suitable for aquaculture but can also be integrated with recreational fishing activities, such as marine sightseeing and fishing, enhancing the comprehensive value of the fishing industry.
However, insufficient rigidity combined with HDPE floating rafts’ extreme flexibility can cause distortion and deformation under windy situations, which can result in structural damage [20]. A thorough investigation of the nonlinear significant deformation response characteristics of HDPE floating rafts for aquaculture is necessary due to the intricate mechanism of destruction of these structures under the influence of wind and waves.
A floating system (walkway plate and buoy), net system, ballast system, and anchoring system combine to produce the comprehensive construction of HDPE floating rafts for aquaculture. Figure 2 shows the components of a plate-type HDPE floating raft. The cultivation area is composed of multiple small units, allowing for the separate placement of fish or shellfish in the cultivation area. The walkway plate creates a framework structure that gives room for regular upkeep and management. Using strong bolts or cables, the connectivity of each plastic buoy creates an integral structure while providing buoyancy. The HDPE floating raft is moored by cables that are part of the mooring system, which is secured to the ocean floor.
Complex nonlinear factors including load, geometry, and material are involved in the dynamic response of HDPE floating rafts. Research can be conducted using both physical experiments and numerical simulation methods, drawing on the expertise of various aquaculture cages. Experiments using physical models yield comprehensible and trustworthy results when examining the dynamic reaction of aquaculture cage array and how it affects wave fields. For instance, in order to provide recommendations for fish cage array design, Zhao [21] carried out a series of physical model experiments to measure the main mooring tension and flow velocity of fish cage arrays under various configurations. In terms of numerical simulation research, Chu [20] studied the hydro-elastic response of a floating raft with a mooring system in regular and irregular waves using the Morison equation and the CFD numerical simulation approach. This study provided information about the force distributions and motion response patterns of floating rafts under various wave conditions. An expanded 3D hydroelasticity theory-based numerical model was developed by Fu [22] to forecast the dynamic response of farming floating collars with 5 by 2 fish cages in regular waves. The problem of oblique wave incidence on a cage array of independent circular fish cages was studied by Gharechae [23] using a semi-analytical method. The results showed that hydro-elastic interactions become more significant as wavenumbers increase. Numerous studies have integrated numerical simulation techniques with physical model experiments. Fredriksson [5] built a comprehensive finite element model of HDPE net pen flotation structures using finite element technology and laboratory experimentation. Shen [24] and Xu [25] investigated the nonlinear dynamic behavior of an aquaculture cage array containing 16 net cages in a 2 × 8 configuration under wave action by combining numerical simulations with physical model tests. More studies do not consider the significant deformation of the floating frame structure [26,27,28,29,30], which is obviously no longer applicable to the study of HDPE floating rafts.
It is difficult to mimic complicated sea conditions in harsh environments, the extent of biofouling, and the consequences of fish movement using laboratory-based physical model experiments and numerical simulation methods. Prior studies have indicated a notable divergence between the outcomes of these two study methodologies and real-world scenarios. For example, Winthereig [31] used field testing and computational fluid dynamics (CFD) to compare the fluid flow in fish cages used for aquaculture. The analysis showed discrepancies between the real measurement data and the CFD simulation, with the CFD simulation 50% overestimating the flow velocity. This disparity was explained by the nets having an increased net solidity as a result of water flow-induced deformation and the blocking effect from the fish inside the cage. Dong [32] used both full-scale and model tests to examine the water resistance and deformation of fish cages, demonstrating the possibility of inaccuracies when converting model test findings to full-scale test results. It is not feasible to do physical model experiments on expansive fishing areas [33]. Sea trials are essential to gather accurate dynamic response data on HDPE floating rafts in challenging sea conditions. In contrast to model tests, sea trials may encounter unforeseen issues while taking measurements. Measuring elements such as net force and deformation, wave and flow field variations surrounding the net cage, and the intricate movement of mooring fiber ropes is very difficult due to monitoring system constraints [34]. Sea trials offer useful information for model experiments and numerical simulations [32]. For instance, Bi [35] carried out a case study in the waters surrounding Nanji Island, which is located 55 km away from Wenzhou, China, and trained an artificial neural network to forecast the structural failure of HDPE offshore net cages in typhoon waves. Using wave statistics data from the previous 30 years, Shi [36] computed the failure risk of HDPE fish cages under the influence of typhoon waves. Klebert [37] investigated the changes in volume and flow rate of large circular flexible fish cages under high flow rates using numerical modeling and field measurements. There is currently a dearth of research data from sea trials, with little information on both domestic and international sea trials readily available. The primary objectives of sea trials have been to measure the drag force [32,38], net cage deformation [32,37,38,39,40], and variations in flow rate [31,37,39,40] of gravity-type fish cages. There are not many measurements of the mooring forces of gravity-type fish cages [41] and there are not any documented sea trials that especially examine the motion and deformation of HDPE floating rafts in various sea conditions.
The present research focuses on the difficulty of acquiring specific data throughout the testing process by collecting sea observation data from HDPE floating rafts under various sea conditions. The motion response properties of HDPE floating rafts used in aquaculture have been investigated in this study. The outcomes of the sea trials can be used to support the validity of time-domain numerical models, evaluate the safety of HDPE floating rafts, and provide technical guidelines for on-the-ground fish farm monitoring. The organization of this study is as follows. Section 2 introduces the selection of sea trial observation sites, the conditions of the observed floating rafts, and the design of the observation plan. In Section 3, the content and process of sea trial observations are described in detail, including sea current observations, HDPE floating rafts motion measurements, deformation measurements, and mooring force measurements. In Section 4, the observation results are analyzed and, based on these results, the vulnerability positions of the floating rafts are identified. Section 5 discusses the measurement results, focusing on the dynamic response characteristics of the HDPE floating rafts. Finally, conclusions are drawn in Section 6.

2. Material and Methods

2.1. Research Area

The sea trials were conducted in a fishery located in Sandu’ao, Fuzhou City, China, targeting two sets of HDPE floating rafts for aquaculture, as shown in Figure 3.
Throughout its entire lifecycle, an HDPE floating raft is subjected to various environmental and operational conditions. This study selects two typical environmental conditions (Test 1 and Test 2) to provide references for later analysis of the performance of HDPE floating rafts under different environments.
Test 1 involved a structure formed by connecting a red pipe-type floating raft, a blue plate-type floating raft, and a yellow plate-type floating raft. The individual floating rafts were set up in a 4 × 5 configuration without hanging nets. The blue floating raft was positioned in the middle, with the red and yellow floating rafts at either end. Two sets of mooring ropes (numbered 1–10) were arranged at both ends for anchoring to the seabed and another set of mooring ropes (numbered 11–16) was arranged in the middle for interconnecting the floating rafts. All the mooring ropes and floating raft groups were arranged in the same direction, forming an overall I-shaped structure. The mooring ropes are evenly distributed on both sides of the floating rafts. Before the sea trials, the tension of each rope was measured in advance and the balance of the rope tension was maintained by adjusting the length of the ropes. The floating raft groups were oriented in the north–south direction, with the red floating raft facing north. A real-life image of the Test 1 floating raft is shown in Figure 4 and the structural dimensions of the different floating raft types are provided in Table 1.
The objects subjected to the Test 2 measurements consisted of a configuration comprising a blue plate-type floating raft, a black pipe-type floating raft, and a yellow plate-type floating raft interconnected to form a group structure. Additionally, a red pipe-type floating raft was included, resulting in a 3 + 1 arrangement. Each individual floating raft was arranged in a 4 × 5 configuration, with yellow and blue floating rafts equipped with nets. The blue and yellow floating rafts were positioned at the ends, with the black floating raft at the center. The layout included three mooring ropes on the north side of the blue floating raft and three on the south side of the yellow floating raft, all utilized for seabed anchoring. Two sets of four mooring ropes each were positioned in the middle, facilitating an interconnection between the floating rafts. The red floating raft, placed independently, featured one mooring rope on the north side and two on the south side, all serving for seabed anchoring. All mooring ropes and floating raft groups were arranged in the same direction, forming an overall I-shaped structure.

2.2. Setup

In order to assess floating raft motion displacement, acceleration, net cage deformation, and mooring force as well as the speed and direction of ocean ambient flow, a variety of approaches were employed during these sea trials. The sensor layout for Test 1 is illustrated in Figure 5, while a similar layout was adopted for Test 2, as shown in Figure 6. A full list of the test-related instruments is shown in Figure 7.
For Test 1, eight crack gauge sensors were placed on each floating raft for measuring deformation, labeled R1–R8 for the red floating raft, B1–B8 for the blue floating raft, and Y1–Y8 for the yellow floating raft. Additionally, six capacitive triaxial acceleration sensors for measuring motion acceleration, labeled K1–K6, were placed on the floating rafts. The motion trajectory capture points were designated H1 and H2.
For Test 2, eight gyroscopes were placed on each floating raft to measure the motion acceleration of the floating rafts, labeled G1–G8 for the red floating raft, G9–G16 for the black floating raft, G17–G24 for the yellow floating raft, and G25–G32 for the separate red floating raft. The motion trajectory capture points were designated H3–H10. Power for all equipment is provided by the chassis on each floating raft.

3. Sea Trials

3.1. Current and Wave Measurements

HDPE floating raft fish farming is an intensive farming method, which inevitably has negative impacts on the hydrological environment, such as hindering water flow, reducing oxygen exchange [33], wasting water, and exacerbating eutrophication [42]. Detailed water flow information collection and mathematical modeling are crucial for evaluating both aquaculture activities inside fish cages and the hydrological environment outside fish cages. This approach not only aids in controlling the quality of aquaculture products but also contributes to spatial planning for marine aquaculture.
Changes in flow velocity can be measured using acoustic Doppler current profilers (ADCPs) and acoustic Doppler velocimeters (ADVs) [37]; alternatively, an ADCP can be used outside the net cage to measure flow velocity and modular acoustic velocity sensors (MAVSs) can be used inside the net cage [39]. The current meter has greater quality for surface flow velocity measurements. In this investigation, the flow velocity was measured using a current meter. As shown in Figure 8, the current meter for Test 1 was positioned on the west side of each of the three floating rafts, installed in the middle of a cross-shaped frame, and fastened to the side of the floating raft using a rope. As seen in Figure 9, the current meters for Test 2 were positioned in the middle of the yellow and black floating rafts, affixed in the center of a plastic ring frame, and fastened to the floating raft aisle using a rope.
Acoustic waves and currents profilers are deployed around the floating rafts to obtain more detailed oceanographic data, including wave information.

3.2. Motion Measurements

The interactions between wave-float structures include the vertical motion and acceleration of the floating structure, wave overtopping, and float emergence phenomena. This sea trial mainly measured the motion trajectory and acceleration of HDPE floating rafts. The main body of the HDPE floating raft is below the water surface and its spectral information is weak [43]. In addition, the more complex marine environment and the presence of aerosols cause significant color deviation and fogging in recorded videos and images, as well as other issues like fuzzy details and low resolution. In order to clarify the fogged photos, Fattal [44], He [45], and Kim [46] proposed single-image defogging methods. Subsequently, scholars [47,48,49] proposed various models based on deep networks to achieve super-resolution reconstruction of the image, with successful outcomes. The surface of the fish cage was marked with specially colored capture points, or floats, as shown in Figure 10, and the motion trajectory of these dots was captured using onshore camera equipment. As seen in Figure 11, the camera was installed atop the communication tower close to the coast for Test 1. A similar installation technique was applied in Test 2. After trying colors commonly used for signal lights (red, green, and yellow) and the orange color commonly used for life-saving equipment, it was found that orange was the easiest to identify under the conditions of this sea measurement. As a result, orange was ultimately chosen as the color of the motion trajectory capture point.
In order to avoid image color distortion, inhomogeneity, and other issues, a color telephoto camera with good color resolution should be selected, which has pixels of 2–5 million, a horizontal definition of 2 million, 3 million, and 5 million, a signal-to-noise ratio ≥48 dB, an infrared distance of 60–120 m, 30× optical zoom, and a focal length of 4–96 mm. Shooting from a distance, small and inconspicuous markers, and changing shooting environments (sunlight, birds, waves, sudden camera shake, etc.) can pose challenges to capture. Collecting video images requires careful attention, including making modifications repeatedly. An attempt was made to photograph at a great distance in order to increase the image resolution and reduce the effect of a unit pixel on the actual distance.
Capacitive triaxial acceleration sensors were used in Test 1 to measure the acceleration of the floating rafts; sensor parameters are provided in Table 2. Gyroscopes were used in Test 2, which has a high-performance microprocessor, advanced dynamic algorithm, and Kalman dynamic filtering algorithm to quickly solve for the current real-time motion attitude of the module. Whichever instrument is chosen, the power supply and data-collecting equipment need to be sealed and waterproofed to handle complicated and variable marine environments.

3.3. Floating Raft Deformation Measurements

Strain gauges are widely used to measure the strain in steel equipment. Strain gauges are useful for identifying tension or contraction in hard-to-perceive structures. However, for significant deformations of HDPE floating rafts used in aquaculture, traditional strain gauges are no longer appropriate. The deformation of HDPE floating rafts was evaluated by using a crack gauge sensor during this sea trial, whose parameters are shown in Table 3. The HDPE floating raft underwent deformation in tandem with the sea trial process. It was essential to make sure the insulating properties of the crack gauge sensors were preserved in the maritime environment and that they were firmly attached to the floating raft surface. For this sea trial, specifically developed crack gauge sensors fasteners and fixtures were employed; the crack gauge sensors were fixed to the main pipe (for pipe-type floating rafts) or fish cage walkway plate (for plate-type floating rafts). The probe position changed with the motion of the floating raft, indicating that the floating raft was deformed. The installation and measurement methods are shown in Figure 12.

3.4. Mooring Line Force Measurements

Mooring line breakage is a typical failure mode of HDPE floating rafts [20] and research has shown that the failure of one mooring line significantly affects the failure probability of the remaining mooring lines [50]. Mooring line forces measurements utilized a plate-type tension sensor, NTJL-7. The sensor weighs 6.1 kg, has a working voltage of 10 V and a measuring range of 10 t, and is constructed of 42 CrMo alloy steel. Its sensitivity is 2 mV/V and its dimensions are shown in Figure 13. Each mooring line was equipped with a tension sensor to record the tension changes.

4. Results

Factors such as the sensor angle, signal propagation time, signal receiver, and sampling frequency may lead to measurement results containing outliers. Therefore, to improve the accuracy of sea trial data and eliminate data points with significant errors and inconsistencies, careful data filtering is essential [51]. The data presented in this sea trial are the result of repeated debugging and correction.

4.1. Current and Wave

Flow velocity and direction data are based on current meter measurements. Figure 14 and Figure 15 present the changes in surface flow velocity and direction, respectively, over 24 h at the Test 1 site from 16:00 on 1 May 2022, to 16:00 on 2 May 2022. The maximum surface flow velocity in the area during this period was 0.93 m/s, with a northward direction. Four peak values occurred within 24 h and the flow direction also changed.
Test 2 took place during the 15th day of the 8th lunar month (mid-autumn festival) when tidal currents reached their maximum for the year in the local area. Due to adverse on-site conditions and unexpected factors, not all the sensors obtained valid measurement data. Figure 16 and Figure 17 show the flow velocity and direction near the yellow and red floating rafts, respectively. The maximum surface flow velocity near the yellow floating raft exceeded 1.386 m/s and the maximum surface flow velocity near the red floating raft did not exceed 1.097 m/s. The floating rafts had a certain inhibitory effect on the ocean currents.
Wave data of Test 1 were acquired through the deployment of acoustic waves and current profilers. The significant wave height is 0.57 m, the maximum wave height is 0.78 m, the zero-crossing period is 4.28 s, and the average wave direction is 65°. The wave spectrum is shown in Figure 18.

4.2. Motion

After capturing floating raft motion videos with a telephoto camera, a MATLAB 2016b program for image digital processing was developed to calculate the pixel position of the capture points, resulting in a pixel position curve for the captured points. The effectiveness of the sea trial is weather-dependent; in adverse weather conditions, the lack of distinct color differences makes capture difficult, necessitating repeated adjustments to the program’s capture control parameters. The original image capture results are pixel positions with integer values and the capture result curve is stepped. To obtain a smoother motion curve, the original capture curve is subjected to smoothing processing. A relationship between the image distance and actual distance is established by measuring the height of the marked points in advance and taking the pixel distance of the marked points in the image, obtaining the number of pixels corresponding to each meter in actual spatial distance. To verify the rationality of the above conversion method, photographs taken at multiple time periods were selected and the pixel length of the marked points was measured in each photo and converted into pixels per meter. After converting to actual motion positions, the displacement time history curve of the captured points was obtained. The capture curve time shift has a certain degree of overall offset, which was later found to be caused by tidal fluctuations, thus requiring tidal level correction. To eliminate the impact of interference terms on the results, spectral analysis is needed, converting the corrected displacement time curve into a displacement spectrum density curve. The entire process uses proprietary source code developed independently with MATLAB for data analysis and processing, detailed steps are shown in Figure 19. Finally, the motion displacements of the floating rafts are obtained, as shown in Figure 20 and Figure 21.
For Test 1, the measured results of the vertical acceleration at observation points K1, K2, and K5 are shown in Figure 22. For Test 1, observation points K1 and K2 were on the red floating raft and observation point K5 was on the yellow floating raft. The observed data suggest that the acceleration data of the red floating raft fluctuate rapidly, while the acceleration data of the yellow floating raft change more steadily.

4.3. Deformation

The maximum deformation of the floating rafts can be determined by comparing crack gauge sensor data for the three floating rafts in Test 1. The red floating raft experienced a maximum deformation of 0.517 mm, as shown in Figure 23a, while the yellow floating raft experienced a maximum deformation of 0.495 mm, as shown in Figure 23b.
During Test 2, which coincided with the 15th day of the 8th lunar month (mid-autumn festival), the tidal currents reached their maximum throughout the year. Due to the intense flow velocity, the yellow floating raft experienced severe rolling deformation and damage, as shown in Figure 24.

4.4. Mooring Line Force

After multiple attempts, Test 1 obtained 24-h tension data for mooring lines 2 and 5, as shown in Figure 25. The data reflected significant differences in tension between different mooring lines at the same time and the trends also differed. This suggests that the mooring lines at the test site were irregularly arranged, with varying lengths and uneven forces, and that the directions were chaotic.
During the 2–6-h time period, the tension data for mooring line 2 in Test 1 showed a small peak. During this time period, the flow direction was close to due north and mooring line 2 did not bear the tension of the floating raft. The tension on mooring line 2 mainly came from the force of the ocean current on the mooring line (including drag force and frictional force). The relatively short length of the mooring line itself brought about a large tension, causing the floating raft to sink further during high flow velocities, further increasing the tension.
Test 2 encountered the maximum annual ocean current; the data for mooring line 3 of the blue floating raft are shown in Figure 26. Its maximum tension was nearly 60 kN, far exceeding the mooring line tension under normal environmental conditions in Test 1.

5. Discussion

5.1. Selection of Testing Equipment for Sea Trials of Floating Rafts

The choice of testing equipment is crucial for the quality of the data obtained and the accuracy of subsequent research when conducting sea trials of HDPE floating rafts. When selecting equipment, it is essential to choose devices with stable performance, high precision, and fast response based on the specific objectives and requirements of the sea trials. Additionally, considering the relatively harsh environment of marine testing, the equipment must possess strong environmental adaptability, good durability, and reliability. On HDPE floating rafts, there are generally few long-term stable power supply methods, so the energy requirements and power supply methods of the equipment must be considered in advance. The equipment selected for this study has been verified as reliable through repeated practice and it is relatively simple to operate and maintain, providing a reference for future sea trials.
It is important to note that HDPE floating rafts in the wave-facing area are prone to wave overtopping. If not treated with waterproofing, it can easily lead to equipment damage or even loss. Choosing the measurement area in a wave-sheltered region can effectively reduce the equipment failure rate but the measurement results may be underestimated. For the consideration of equipment layout, a small wooden hut can be set up on the floating raft (see Figure 27), which will play a significant role in the arrangement of on-site cabinets and the management of equipment. Throughout the trial process, the impact on the marine environment should be considered and measures should be taken to reduce pollution and ecological damage.

5.2. Condition Selection

In actual marine aquaculture, whether it is the initial installation of the floating raft or subsequent net maintenance, the floating raft will be in a state without nets and counterweights. This study mainly analyzes the motion performance, acceleration, and mooring line force characteristics of the HDPE floating rafts under the action of ocean currents and waves in both with nets (Test 2) and without nets (Test 1) conditions. At the same time, it observes the phenomenon of significant deformation and curling failure of the HDPE floating raft with nets under extreme sea conditions. These data and imagery can provide reference and support for subsequent HDPE floating raft design analysis and risk avoidance.

5.3. Data Analysis

Based on hydrological observations, the variations in surface ocean current velocity and direction at the Sanduo’ao fishery over a continuous 24-h period are obtained, as shown in Figure 14 and Figure 15. By analyzing the data results, the surface ocean current velocity exhibited four extreme peaks, which may indicate a significant increase in current velocity at these specific time points. The direction of the current also changed over the 24-h period, implying that the direction of the ocean current is not constant but varies with time. In contrast, under extreme environmental conditions as depicted in Figure 16 and Figure 17, the data show multiple sharp increases or decreases, with rapid changes in velocity and direction, posing an extreme test for the safety of the HDPE floating rafts. For the measurement of wave data, the vertical motion trajectory of a buoy can be used as a wave surface variation curve, and the direction of the waves can be roughly estimated through video recording.
In the motion observation of the floating rafts, the number of pixels per meter in the video recording was stable at around 60, with variations in the number of pixels per meter from different images fluctuating within a range of 4 pixels around the average value, attributed to measurement errors from the human eye. The proportional differences caused by the size-distance effect are not greater than the measurement errors from the human eye, and it can be considered that each position essentially follows the same number of pixels per meter. The final number of pixels per meter is an overall average of 60.5, equivalent to a unit pixel length of about 16 mm. After video capture and floating raft motion analysis, displacement curves under different conditions were derived (see Figure 20 and Figure 21). Comparing these two curves, the magnitude and pattern of displacement are as expected, the data are reasonable, and this validates the reliability of the methods proposed in this paper.
To verify the validity of the observational data and to analyze the motion response patterns of floating rafts, this study employs the Fast Fourier Transform (FFT) for spectral analysis of the data. To study the local energy characteristics of the motion displacement curve at any given moment, this study employs the Gabor Transform, selecting the Gauss function as the window function for further analysis. For the given constants a and b, the Gabor Transform G f ( a , b ) of f ( t ) under the window function g ( t ) is defined as Equations (1) and (2), as follows:
G f ( a , b ) = ∫ − ∞ + ∞ f ( t ) g ( t − b ) e − i t a d t
g ( x ) = 1 2 π α 0 e − x 2 4 α 0
where f ( t ) is the signal function; g ( t ) is the window function; and α 0 is constant and controls the width of the window.
Selected data from Test 1, specifically the displacements in the z-direction measured at points H1 and H2 of the yellow floating raft (see Figure 20), and the acceleration measured at point K5 (see Figure 22c) were used for verification. These three measurement points are near each other and the data collected from them can mutually validate the accuracy of the measurements. The results of the FFT and Gabor Transform are presented in Figure 28. From the FFT, it can be observed that the energy of the three curves peaks around a frequency of 0.2 Hz, with the majority of the energy concentrated within the range of 0 to 0.4 Hz. The shapes and trends of the FFT curves are essentially the same and the trends of the curves’ rises and falls are also similar. Additionally, by comparing the time–frequency characteristics of the three curves through the Gabor Transform, it is evident that the energy fluctuations are relatively stable within the same time frame. Around 300 s, the brightest high-energy regions corresponding to each color can be identified in all three curves.
The motion response of the floating raft can be characterized by the Response Amplitude Operator (RAO). The wave spectrum measured in Test 1 (see Figure 18) is transformed into the amplitude–frequency curve of the waves, denoted as FFTw. After performing a Fast Fourier Transform on the vertical displacement time curve, the amplitude–frequency curve of the vertical displacement denoted as FFTz, is obtained (see Figure 28). According to the following formula,
R A O = F F T z F F T w
the RAO of the floating raft is calculated. When describing the vertical displacement motion response, the RAO is a dimensionless value. Under the influence of various environmental loads, the motion response curves of the floating raft are not smooth. The obtained RAO curves also need to be smoothed, as shown in Figure 29.
The analysis results indicate that the vertical displacement response exhibits a peak value near the frequency of 0.1 Hz, with a large amplitude of response. A trough is observed near 0.26 Hz; beyond 0.26 Hz, there are minor fluctuations but the response amplitudes remain relatively small.
An FFT was conducted on the motion displacement curve (Figure 21) of the yellow floating raft in Test 2, resulting in Figure 30. Under extreme environmental conditions, the primary frequencies of the displacement in the X-axis direction are concentrated between 0.1 and 2.0 Hz, with peak frequencies appearing near 0.373 Hz and 1.34 Hz. The primary frequencies of the Z-axis direction are also concentrated between 0.1 and 2.0 Hz, with peak frequencies occurring near 0.373 Hz and 1.35 Hz. High-frequency factors influence the displacement in both directions.
The acceleration curve in Figure 22 is the result of many influencing factors, with the magnitude and pattern of data changes being reasonable. Spectral analysis was conducted on the Z-axis acceleration of Test 1, as depicted in Figure 31. The primary frequencies of the acceleration at point K1 are concentrated between 0.1 and 1.0 Hz, with peak frequencies occurring near 0.24 Hz, 0.61 Hz, and 0.84 Hz. The primary frequencies of the acceleration at point K2 are also concentrated between 0.1 and 1.0 Hz, with peak frequencies appearing near 0.34 Hz and 0.74 Hz. The zero-crossing wave frequency measured during this time interval is 0.24 Hz. This proves that the approach of using an acceleration sensor for measurement is feasible and can provide vibration information of the floating raft, which is of certain significance.
Figure 23 shows the deformation results of different floating rafts. The deformation curves are relatively smooth, with the maximum deformation range under the measured sea conditions being between −0.6 mm and 0.5 mm, which is essentially equivalent to the preliminary estimated values. The measurement range of the used instruments within 5 mm is sufficient. Through spectral analysis, the deformation of the red floating raft at point R5 has its primary frequencies concentrated between 0.05 and 1.0 Hz, with peak frequencies appearing near 0.055 Hz, 0.148 Hz, 0.277 Hz, and 0.401 Hz. The deformation of the yellow floating raft at point Y8 also has its primary frequencies concentrated between 0.05 and 1.0 Hz, with peak frequencies occurring near 0.034 Hz, 0.106 Hz, 0.178 Hz, and 0.357 Hz, as shown in Figure 32.
Figure 24 shows that the floating raft’s significant deformation and curling caused the local floating raft board to fold, with the fold angle approximately 45 degrees to the board direction, resulting in structural damage and a significant reduction in stiffness near the fold. The curling did not occur instantaneously but gradually increased until it was completely rolled. The curled structural part is not located directly below the floating raft but is offset to the east side, that is, it curls toward the lower side. The reasons for the floating raft curling, in addition to environmental factors, are also affected by the uneven lengths of the floating raft cables and uneven forces, as shown in Figure 25. Under extreme environmental loads, the tension of the mooring line increases sharply (see Figure 26), which can easily lead to floating raft failure. It is worth mentioning that when the large deformation phenomenon occurred, the position of the marker buoy on the anchor rope was abnormal, as shown in Figure 33, where a marker buoy appeared on the side of the floating raft, indicating an abnormal direction of cable stretching.

6. Conclusions

This study focuses on introducing sea trial methods for HDPE floating rafts for aquaculture, as well as potential challenges and solutions. It records some valuable on-site work experiences and provides a good reference for future similar work.
  • The effectiveness of sea trials is weather-dependent. Under adverse weather conditions, color differences may not be distinct, leading to difficulties in capturing images. When markers become blurry in bad weather and in good weather, their motion may be subtle, resulting in a small pixel range and relatively large relative errors. The interconnected structure of floating raft groups, formed by the interaction of ocean currents and waves, exhibits inconsistent motion forms and accelerations at different positions. Through the mutual verification of multiple sets of data, it is proven that the measurement data and motion capture method used in this sea trial are effective;
  • Under the dynamic load of conventional conditions, the HDPE floating rafts exhibit a particularly significant structural response near a frequency of 0.1 Hz, which requires special attention during the design and analysis process;
  • HDPE floating rafts for aquaculture are anchored by multiple mooring lines and, under different flow directions, the tension in different mooring lines varies. Damage to a single mooring line may lead to the failure of the entire mooring system. The arrangement of mooring lines affects the overall safety performance of the floating raft and displacement of mooring lines under strong currents can cause the floating raft to roll.
Due to differences in instrument deployment and layout, as well as the influence of on-site observational environmental conditions during offshore observations, there are disparities between the data and the results of some observational elements and expectations. It is acknowledged that sea trials are an effective method for studying HDPE floating rafts. However, the current number of observations and duration is insufficient. Future efforts should increase the observation time, cover different sea conditions, and obtain more comprehensive data. In summary, sea trials provide valuable insights into the dynamic behavior of HDPE floating rafts in real-world marine environments. Addressing these challenges and optimizing experimental designs will enhance the reliability and applicability of these observations, contributing to the ongoing development and refinement of HDPE floating raft technology.

Author Contributions

Conceptualization, F.F., X.Z., Z.H. and J.Y.; methodology, F.F., X.Z. and Z.H.; software, F.F., Y.L. and L.W.; validation, X.Z., Z.H. and J.Y.; formal analysis, F.F., Y.L. and L.W.; investigation, F.F., X.Z. and Z.H.; resources, Z.H.; data curation, Z.H.; writing—original draft preparation, F.F., X.Z. and Z.H.; writing—review and editing, F.F., X.Z. and Z.H.; visualization, Y.L. and L.W.; supervision, J.Y.; project administration, F.F.; funding acquisition, X.Z., Z.H. and Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (Grant No. 52371321; 52301320), the Natural Science Founds of Fujian Province (No. 2021J01840; 2023J01790), and the Jimei University National Fund Cultivation Program Project (ZP2023002; ZP2023001).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

Author Lihe Wang was employed by the company China Energy Engineering Group Guangdong Electric Power Design Institute Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Food and Agriculture Organization of the United Nations. The State of World Fisheries and Aquaculture. Towards Blue Transformation. 2022. Available online: http://www.fao.org/documents/card/en/c/cc0461en (accessed on 3 June 2024).
  2. Whitmore, E.H.; Safford, T.G.; Hamilton, L.C. What does the public think about farming seafood? Modeling predictors of social support for aquaculture development in the U.S. Ocean Coast. Manag. 2022, 226, 106279. [Google Scholar] [CrossRef]
  3. Drizo, A.; Shaikh, M.O. An assessment of approaches and techniques for estimating water pollution releases from aquaculture production facilities. Mar. Pollut. Bull. 2023, 196, 115661. [Google Scholar] [CrossRef]
  4. Mohammed, K.S.; Nassani, A.A.; Sarkodie, S.A. Assessing the effect of the aquaculture industry, renewable energy, blue R&D, and maritime transport on GHG emissions in Ireland and Norway. Aquaculture 2024, 586, 740769. [Google Scholar] [CrossRef]
  5. World Economic Forum. The Global Sustainable Aquaculture Roadmap: Pathways for Systematic Change. White Paper Published in March 2023. Available online: https://www.aquacultureroadmap.org (accessed on 6 June 2024).
  6. Li, K.; Jiang, R.; Qiu, J.; Liu, J.; Shao, L.; Zhang, J.; Liu, Q.; Jiang, Z.; Wang, H.; He, W.; et al. How to control pollution from tailwater in large scale aquaculture in China: A review. Aquaculture 2024, 590, 741085. [Google Scholar] [CrossRef]
  7. Bjørndal, T.; Dey, M.; Tusvik, A. Economic analysis of the contributions of aquaculture to future food security. Aquaculture 2024, 578, 740071. [Google Scholar] [CrossRef]
  8. Kaleem, O.; Sabi, A.F.B.S. Overview of aquaculture systems in Egypt and Nigeria, prospects, potentials, and constraints. Aquac. Fish. 2020, 6, 535–547. [Google Scholar] [CrossRef]
  9. Ngarava, S.; Zhou, L.; Nyambo, P.; Chari, M.M.; Bhungeni, O. Aquaculture production, GHG emission and economic growth in Sub-Sahara Africa. Environ. Chall. 2023, 12, 100737. [Google Scholar] [CrossRef]
  10. Afewerki, S.; Osmundsen, T.; Olsen, M.S.; Størkersen, K.V.; Misund, A.; Thorvaldsen, T. Innovation policy in the Norwegian aquaculture industry: Reshaping aquaculture production innovation networks. Mar. Policy 2023, 152, 105624. [Google Scholar] [CrossRef]
  11. Pantusa, D.; Saponieri, A.; Tomasicchio, G.R. Assessment of coastal vulnerability to land-based sources of pollution and its application in Apulia, Italy. Sci. Total. Environ. 2023, 886, 163754. [Google Scholar] [CrossRef]
  12. Kotyza, P.; Bajan, B.; Ponsioen, T.; Smutka, L.; Shubitidze, G.; Chobaniani, N.; Andres, L. The emission intensity of the freshwater aquaculture production value chain in Georgia. Aquaculture 2024, 586, 740844. [Google Scholar] [CrossRef]
  13. Wu, H.; Hou, J.; Wang, X. A review of microplastic pollution in aquaculture: Sources, effects, removal strategies and prospects. ecotoxicol. Environ. Saf. 2023, 252, 114567. [Google Scholar] [CrossRef]
  14. Skirtun, M.; Sandra, M.; Strietman, W.J.; van den Burg, S.W.K.; De Raedemaecker, F.; Devriese, L.I. Plastic pollution pathways from marine aquaculture practices and potential solutions for the North-East Atlantic region. Mar. Pollut. Bull. 2022, 174, 113178. [Google Scholar] [CrossRef]
  15. Krüger, L.; Casado-Coy, N.; Valle, C.; Ramos, M.; Sánchez-Jerez, P.; Gago, J.; Carretero, O.; Beltran-Sanahuja, A.; Sanz-Lazaro, C. Plastic debris accumulation in the seabed derived from coastal fish farming. Environ. Pollut. 2020, 257, 113336. [Google Scholar] [CrossRef]
  16. Samat, N.; Goh, K.H.; See, K.F. Review of the application of cost–benefit analysis to the development of production systems in aquaculture. Aquaculture 2024, 587, 740816. [Google Scholar] [CrossRef]
  17. Tian, Y.; Yang, Z.; Yu, X.; Jia, Z.; Rosso, M.; Dedman, S.; Zhu, J.; Xia, Y.; Zhang, G.; Yang, J.; et al. Can we quantify the aquatic environmental plastic load from aquaculture? Water Res. 2022, 219, 118551. [Google Scholar] [CrossRef]
  18. Hou, T.; Sun, W.; Chen, C.; Yang, G.; Meng, X.; Peng, J. Marine Floating raft aquaculture extraction of hyperspectral remote sensing images based decision tree algorithm. Int. J. Appl. Earth Obs. Geoinf. 2022, 111, 102846. [Google Scholar] [CrossRef]
  19. Fredriksson, D.W.; DeCew, J.C.; Tsukrov, I. Development of structural modeling techniques for evaluating HDPE plastic net pens used in marine aquaculture. Ocean Eng. 2007, 34, 2124–2137. [Google Scholar] [CrossRef]
  20. Chu, B.; Chen, Y.; Zhang, Y.; Zhang, G.; Xiang, X.; Zhang, X. Numerical study on wave-induced hydro-elastic responses of a floating raft for aquaculture. Ocean Eng. 2021, 240, 109869. [Google Scholar] [CrossRef]
  21. Zhao, Y.P.; Bi, C.W.; Chen, C.P.; Li, Y.C.; Dong, G.-H. Experimental study on flow velocity and mooring loads for multiple net cages in steady current. Aquac. Eng. 2015, 67, 24–31. [Google Scholar] [CrossRef]
  22. Fu, S.; Moan, T. Dynamic analyses of floating fish cage collars in waves. Aquac. Eng. 2012, 47, 7–15. [Google Scholar] [CrossRef]
  23. Gharechae, A.; Ketabdari, M.J. A dynamical study on sea waves interaction with an array of circular elastic floaters of aquaculture fish cages. Mar. Struct. 2022, 85, 103241. [Google Scholar] [CrossRef]
  24. Shen, H.; Zhao, Y.P.; Bi, C.W.; Xu, Z. Nonlinear dynamics of an aquaculture cage array induced by wave-structure interactions. Ocean Eng. 2023, 269, 113711. [Google Scholar] [CrossRef]
  25. Xu, Z.; Bi, C.W.; Ma, C. Nonlinear dynamics of an aquaculture cage array under oblique wave attack. Ocean Eng. 2023, 288. [Google Scholar] [CrossRef]
  26. Ma, C.; Bi, C.W.; Xu, Z.; Zhao, Y.P. Dynamic behaviors of a hinged multi-body floating aquaculture platform under regular waves. Ocean Eng. 2022, 243, 110278. [Google Scholar] [CrossRef]
  27. Ma, C.; Xie, S.; Bi, C.W.; Zhao, Y.P. Nonlinear dynamic analysis of aquaculture platforms in irregular waves based on Hilbert–Huang transform. J. Fluids Struct. 2023, 117, 103831. [Google Scholar] [CrossRef]
  28. Ma, C.; Zhao, Y.P.; Bi, C.W.; Xie, S. Numerical study on dynamic analysis of a nine-module floating aquaculture platform under irregular waves. Ocean Eng. 2023, 285, 115253. [Google Scholar] [CrossRef]
  29. Bi, C.W.; Ma, C.; Zhao, Y.P.; Xin, L.X. Physical model experimental study on the motion responses of a multi-module aquaculture platform. Ocean Eng. 2021, 239, 109862. [Google Scholar] [CrossRef]
  30. Ma, C.; Zhao, Y.P.; Xu, Z.; Bi, C.W. Experimental investigation on the wave performance with the interference of floating aquaculture cages in single and tandem arrangements. Ocean Eng. 2022, 262, 112255. [Google Scholar] [CrossRef]
  31. Winthereig-Rasmussen, H.; Simonsen, K.; Patursson, Ø. Flow through fish farming sea cages: Comparing computational fluid dynamics simulations with scaled and full-scale experimental data. Ocean Eng. 2016, 124, 21–31. [Google Scholar] [CrossRef]
  32. Dong, S.; Park, S.; Kitazawa, D.; Zhou, J.; Yoshida, T.; Li, Q. Model tests and full-scale sea trials for drag force and deformation of a marine aquaculture net cage. Ocean Eng. 2021, 240, 109941. [Google Scholar] [CrossRef]
  33. Fredriksson, D.W.; DeCew, J.C.; Tsukrov, I.; Swift, M.R.; Irish, J.D. Development of large fish farm numerical modeling techniques with in situ mooring tension comparisons. Aquac. Eng. 2007, 36, 137–148. [Google Scholar] [CrossRef]
  34. Su, B.; Bjørnson, F.O.; Tsarau, A.; Endresen, P.C.; Ohrem, S.J.; Føre, M.; Fagertun, J.T.; Klebert, P.; Kelasidi, E.; Bjelland, H.V. Towards a holistic digital twin solution for real-time monitoring of aquaculture net cage systems. Mar. Struct. 2023, 91, 103469. [Google Scholar] [CrossRef]
  35. Bi, C.W.; Zhao, Y.P.; Sun, X.X.; Zhang, Y.; Guo, Z.X.; Wang, B.; Dong, G.H. An efficient artificial neural network model to predict the structural failure of high-density polyethylene offshore net cages in typhoon waves. Ocean Eng. 2020, 196, 106793. [Google Scholar] [CrossRef]
  36. Shi, X.W.; Zhao, Y.P.; Bi, C.W.; Liu, Q.; Fan, Z.Q.; Zhou, S.H.; Jia, N. Failure probability of offshore high-density polyethylene net cages under typhoon waves. Aquac. Eng. 2022, 98, 102254. [Google Scholar] [CrossRef]
  37. Klebert, P.; Patursson, Ø.; Endresen, P.C.; Rundtop, P.; Birkevold, J.; Rasmussen, H.W. Three-dimensional deformation of a large circular flexible sea cage in high currents: Field experiment and modeling. Ocean Eng. 2015, 104, 511–520. [Google Scholar] [CrossRef]
  38. Gansel, L.C.; Oppedal, F.; Birkevold, J.; Tuene, S.A. Drag forces and deformation of aquaculture cages—Full-scale towing tests in the field. Aquac. Eng. 2018, 81, 46–56. [Google Scholar] [CrossRef]
  39. DeCew, J.; Fredriksson, D.W.; Lader, P.F.; Chambers, M.; Howell, W.H.; Osienki, M.; Celikkol, B.; Frank, K.; Høy, E. Field measurements of cage deformation using acoustic sensors. Aquac. Eng. 2013, 57, 114–125. [Google Scholar] [CrossRef]
  40. Lader, P.; Dempster, T.; Fredheim, A.; Jensen, Ø. Current induced net deformations in full-scale sea-cages for Atlantic salmon (Salmo salar). Aquac. Eng. 2008, 38, 52–65. [Google Scholar] [CrossRef]
  41. Colbourne, D.B.; Allen, J.H. Observations on motions and loads in aquaculture cages from full scale and model scale measurements. Aquac. Eng. 2001, 24, 129–148. [Google Scholar] [CrossRef]
  42. Huang, Y.; Li, Z.; Sun, C.; Feng, Z.; Li, J.; Wei, D.; Wang, B.; Jiang, S.; Chen, K.; Sun, X. Using the roughness height and manning number in hydrodynamic model to estimate the impact of intensive oyster aquaculture by floating & fixed rafts on water exchange with an application in Qinzhou Bay, China. Ecol. Modell. 2023, 476, 110230. [Google Scholar] [CrossRef]
  43. Liu, Y.; Wang, Z.; Yang, X.; Zhang, Y.; Yang, F.; Liu, B.; Cai, P. Satellite-based monitoring and statistics for raft and cage aquaculture in China’s offshore waters. Int. J. Appl. Earth Obs. Geoinf. 2020, 91, 102118. [Google Scholar] [CrossRef]
  44. Fattal, R. Single image dehazing. ACM Trans. Graph. 2008, 27, 1–9. [Google Scholar] [CrossRef]
  45. He, K.; Sun, J.; Tang, X. Single image haze removal using dark channel prior. IEEE Trans. Pattern Anal. Mach. Intell. 2011, 33, 2341–2353. [Google Scholar] [CrossRef]
  46. Kim, C. Robust Single-Image Dehazing. Electronics 2021, 10, 2636. [Google Scholar] [CrossRef]
  47. Dong, C.; Loy, C.C.; He, K.; Tang, X. Image super-resolution using deep convolutional networks. IEEE Trans. Pattern Anal. Mach. Intell. 2016, 38, 295–307. [Google Scholar] [CrossRef]
  48. Kim, J.; Lee, J.K.; Lee, K.M. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, Las Vegas, NV, USA, 27–30 June 2016; 1646–1654. [Google Scholar] [CrossRef]
  49. Lim, B.; Son, S.; Kim, H.; Nah, S.; Lee, K.M. Enhanced Deep Residual Networks for Single Image Super-Resolution. In Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Honolulu, HI, USA, 21–26 July 2017; 136–144. [Google Scholar] [CrossRef]
  50. Hou, H.M.; Liu, Y.; Dong, G.H.; Xu, T.J. Reliability assessment of mooring system for fish cage considering one damaged mooring line. Ocean Eng. 2022, 257, 111626. [Google Scholar] [CrossRef]
  51. Jia, P.; Xu, H.; Du, Z.; Xie, Y.; Zhao, C. Prediction of net mouth area for trawlers based on sea trials and machine learning. Ocean Eng. 2024, 293, 116266. [Google Scholar] [CrossRef]
Jmse 12 01150 g001
Figure 1. Application of HDPE in aquaculture equipment, namely an (a) aquaculture fish cage; (b) plate-type floating raft; (c) handrail-type floating raft; and (d) pipe-type HDPE floating raft.
Figure 1. Application of HDPE in aquaculture equipment, namely an (a) aquaculture fish cage; (b) plate-type floating raft; (c) handrail-type floating raft; and (d) pipe-type HDPE floating raft.
Jmse 12 01150 g001
Jmse 12 01150 g002
Figure 2. Composition of a plate-type HDPE floating raft for aquaculture.
Figure 2. Composition of a plate-type HDPE floating raft for aquaculture.
Jmse 12 01150 g002
Jmse 12 01150 g003
Figure 3. Site selection and target floating rafts.
Figure 3. Site selection and target floating rafts.
Jmse 12 01150 g003
Jmse 12 01150 g004
Figure 4. Test 1 actual scenes of floating rafts: (a) red pipe-type floating raft; (b) blue plate-type floating raft; and (c) yellow plate-type floating raft.
Figure 4. Test 1 actual scenes of floating rafts: (a) red pipe-type floating raft; (b) blue plate-type floating raft; and (c) yellow plate-type floating raft.
Jmse 12 01150 g004
Jmse 12 01150 g005
Figure 5. Sensor layout for Test 1.
Figure 5. Sensor layout for Test 1.
Jmse 12 01150 g005
Jmse 12 01150 g006
Figure 6. Sensor layout for Test 2: (a) the consortium of three floating rafts and (b) the independent red floating raft.
Figure 6. Sensor layout for Test 2: (a) the consortium of three floating rafts and (b) the independent red floating raft.
Jmse 12 01150 g006
Jmse 12 01150 g007
Figure 7. Sensors for sea trials.
Figure 7. Sensors for sea trials.
Jmse 12 01150 g007
Jmse 12 01150 g008
Figure 8. Test 1 current meter installed in a cross-shaped frame.
Figure 8. Test 1 current meter installed in a cross-shaped frame.
Jmse 12 01150 g008
Jmse 12 01150 g009
Figure 9. Test 2 current meter installed in the plastic ring frame.
Figure 9. Test 2 current meter installed in the plastic ring frame.
Jmse 12 01150 g009
Jmse 12 01150 g010
Figure 10. Test 1 motion capture points.
Figure 10. Test 1 motion capture points.
Jmse 12 01150 g010
Jmse 12 01150 g011
Figure 11. Test 1 onshore telephoto camera.
Figure 11. Test 1 onshore telephoto camera.
Jmse 12 01150 g011
Jmse 12 01150 g012
Figure 12. Crackmeter sensor testing method.
Figure 12. Crackmeter sensor testing method.
Jmse 12 01150 g012
Jmse 12 01150 g013
Figure 13. Tension sensor dimensions (A = 300, B = 90, C = 38, and D = 200, Φ = 45; dimensions in mm).
Figure 13. Tension sensor dimensions (A = 300, B = 90, C = 38, and D = 200, Φ = 45; dimensions in mm).
Jmse 12 01150 g013
Jmse 12 01150 g014
Figure 14. The 24-h surface flow velocity at the Test 1 site.
Figure 14. The 24-h surface flow velocity at the Test 1 site.
Jmse 12 01150 g014
Jmse 12 01150 g015
Figure 15. The 24-h surface flow direction at the Test 1 site.
Figure 15. The 24-h surface flow direction at the Test 1 site.
Jmse 12 01150 g015
Jmse 12 01150 g016
Figure 16. Flow velocity in Test 2: (a) near the yellow floating raft and (b) near the red floating raft.
Figure 16. Flow velocity in Test 2: (a) near the yellow floating raft and (b) near the red floating raft.
Jmse 12 01150 g016
Jmse 12 01150 g017
Figure 17. Flow direction in Test 2: (a) near the yellow floating raft and (b) near the red floating raft.
Figure 17. Flow direction in Test 2: (a) near the yellow floating raft and (b) near the red floating raft.
Jmse 12 01150 g017
Jmse 12 01150 g018
Figure 18. Wave spectrum for Test 1.
Figure 18. Wave spectrum for Test 1.
Jmse 12 01150 g018
Jmse 12 01150 g019
Figure 19. The detailed steps for obtaining the motion displacement curve.
Figure 19. The detailed steps for obtaining the motion displacement curve.
Jmse 12 01150 g019
Jmse 12 01150 g020
Figure 20. Z-axis displacement of Test 1 (without nets): (a) displacement capture point H1 and (b) displacement capture point H2.
Figure 20. Z-axis displacement of Test 1 (without nets): (a) displacement capture point H1 and (b) displacement capture point H2.
Jmse 12 01150 g020
Jmse 12 01150 g021
Figure 21. Motion displacements of yellow floating raft (with nets) capture point H2 in Test 2: (a) horizontal direction and (b) vertical direction.
Figure 21. Motion displacements of yellow floating raft (with nets) capture point H2 in Test 2: (a) horizontal direction and (b) vertical direction.
Jmse 12 01150 g021
Jmse 12 01150 g022
Figure 22. Test 1 Z-axis acceleration sea trial results: (a) acceleration measurement point K1; (b) acceleration measurement point K2; and (c) acceleration measurement point K5.
Figure 22. Test 1 Z-axis acceleration sea trial results: (a) acceleration measurement point K1; (b) acceleration measurement point K2; and (c) acceleration measurement point K5.
Jmse 12 01150 g022
Jmse 12 01150 g023
Figure 23. Test 1 axial deformation: (a) red floating raft R5 and (b) yellow floating raft Y8.
Figure 23. Test 1 axial deformation: (a) red floating raft R5 and (b) yellow floating raft Y8.
Jmse 12 01150 g023
Jmse 12 01150 g024
Figure 24. Rolling deformation of the yellow floating raft.
Figure 24. Rolling deformation of the yellow floating raft.
Jmse 12 01150 g024
Jmse 12 01150 g025
Figure 25. The 24-h tension of the mooring lines in Test 1: (a) mooring line 2 and (b) mooring line 5.
Figure 25. The 24-h tension of the mooring lines in Test 1: (a) mooring line 2 and (b) mooring line 5.
Jmse 12 01150 g025
Jmse 12 01150 g026
Figure 26. The 24-h tension of mooring line 3 in Test 2 (extreme condition).
Figure 26. The 24-h tension of mooring line 3 in Test 2 (extreme condition).
Jmse 12 01150 g026
Jmse 12 01150 g027
Figure 27. The small wooden hut on the floating raft.
Figure 27. The small wooden hut on the floating raft.
Jmse 12 01150 g027
Jmse 12 01150 g028
Figure 28. FFT and Gabor Transform results of displacement and acceleration: (a) FFT and (b) Gabor Transform.
Figure 28. FFT and Gabor Transform results of displacement and acceleration: (a) FFT and (b) Gabor Transform.
Jmse 12 01150 g028
Jmse 12 01150 g029
Figure 29. RAO of Test 1: (a) displacement capture point H1 and (b) displacement capture point H2.
Figure 29. RAO of Test 1: (a) displacement capture point H1 and (b) displacement capture point H2.
Jmse 12 01150 g029
Jmse 12 01150 g030
Figure 30. FFT of displacement (capture point H2 on the yellow floating raft in Test 2, with nets): (a) horizontal direction and (b) vertical direction.
Figure 30. FFT of displacement (capture point H2 on the yellow floating raft in Test 2, with nets): (a) horizontal direction and (b) vertical direction.
Jmse 12 01150 g030
Jmse 12 01150 g031
Figure 31. FFT of the Z-axis acceleration (Test 1): (a) acceleration measurement point K1 and (b) acceleration measurement point K2.
Figure 31. FFT of the Z-axis acceleration (Test 1): (a) acceleration measurement point K1 and (b) acceleration measurement point K2.
Jmse 12 01150 g031
Jmse 12 01150 g032
Figure 32. FFT of axial deformation (Test 1): (a) red floating raft R5 and (b) yellow floating raft Y8.
Figure 32. FFT of axial deformation (Test 1): (a) red floating raft R5 and (b) yellow floating raft Y8.
Jmse 12 01150 g032
Jmse 12 01150 g033
Figure 33. Abnormal position of an anchor rope buoy.
Figure 33. Abnormal position of an anchor rope buoy.
Jmse 12 01150 g033
Table 1. Structural dimensions of pipe-type and plate-type floating rafts.
Table 1. Structural dimensions of pipe-type and plate-type floating rafts.
ComponentsParametersPipe-Type Floating RaftPlate-Type Floating Raft
Walkway plateWidth (m)0.50.4
Center distance (m)4.54.5
PipeDiameter (mm)125/
Wall thickness (mm)11.5/
Center distance (mm)375/
PlateWidth (mm)/400
Height (mm)/75
Bottom wall thickness (mm)/10
Vertical wall thickness (mm)/10
Number of stiffeners/6
Thickness of stiffeners (mm)/5
Mooring ropeDiameter (mm)3636
MaterialPEPE
Density (g/cm³)0.950.95
Table 2. Parameters of the capacitive triaxial acceleration sensor.
Table 2. Parameters of the capacitive triaxial acceleration sensor.
ParametersValues
Sensibility (23 ± 5 °C)42 mV/m·s−2
Measuring range20 m·s−2
Frequency response (±5%)X and Y (0–1400), Z (0–550)
Resonant frequency>5.5 kHz
Impact limit (No power supply)10,000 g
Driving voltage8–16 VDC
Degree of nonlinearity ± 0.5 %
Operating temperature range−20 °C to 80 °C
WeightAbout 15 g
Overall dimension16 mm × 15 mm × 8 mm
Table 3. Parameters of the crack gauge sensor.
Table 3. Parameters of the crack gauge sensor.
ParametersValues
Standard resistance (Ω)1 K, 2 K, 5 K, 10 K, 20 K
Maximum selectable resistance50 KΩ
Total resistance toleranceStandard level ± 15% (L), Precision level ± 10% (K)
Independent linear toleranceStandard level ± 2.0%, Precision level ± 1.0%
Resolution ratioInfinitely small
Output smoothness<Input voltage 0.1%
Contact resistance variation<2% C.R.V.
Power0.2 W
Electronic stroke11 ± 0.5 mm
Mechanical strokeAbout 12 mm
Insulation resistance>1000 MΩ (500 V.D.C.)
Dielectrics voltage-resistance1 min (500 V.A.C)
Friction value<0.3 N (30 gf)
Stop withstand voltageAbout 10 N (1 kgf)
Temperature coefficient of resistance±400 p.p.m./°C
MassAbout 5 g
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Fu, F.; Zhang, X.; Hu, Z.; Li, Y.; Wang, L.; Yu, J. Research on Sea Trial Techniques for Motion Responses of HDPE Floating Rafts Used in Aquaculture. J. Mar. Sci. Eng. 2024, 12, 1150. https://doi.org/10.3390/jmse12071150

AMA Style

Fu F, Zhang X, Hu Z, Li Y, Wang L, Yu J. Research on Sea Trial Techniques for Motion Responses of HDPE Floating Rafts Used in Aquaculture. Journal of Marine Science and Engineering. 2024; 12(7):1150. https://doi.org/10.3390/jmse12071150

Chicago/Turabian Style

Fu, Fei, Xiaoying Zhang, Zhe Hu, Yan Li, Lihe Wang, and Jianxing Yu. 2024. "Research on Sea Trial Techniques for Motion Responses of HDPE Floating Rafts Used in Aquaculture" Journal of Marine Science and Engineering 12, no. 7: 1150. https://doi.org/10.3390/jmse12071150

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop