Test Tank Research Articles

Acute Behavioral and Neurochemical Effects of Sulpiride in Adult Zebrafish.

Affective and psychotic disorders are highly prevalent and severely debilitating mental illnesses that often remain untreated or treatment-resistant. Sulpiride is a common antipsychotic (neuroleptic) drug whose well-established additional (e.g., antidepressant) therapeutic effects call for further studies of a wider spectrum of its CNS effects. Here, we examined effects of acute 20-min exposure to sulpiride (50-200mg/L) on anxiety- and depression-like behaviors, as well as on brain monoamines, in adult zebrafish (Danio rerio). Overall, sulpiride exerted overt anxiolytic-like effects in the novel tank test and showed tranquilizing-like effects in the zebrafish tail immobilization test, accompanied by lowered whole-brain dopamine and its elevated turnover, without affecting serotonin or norepinephrine levels and their turnover. Taken together, these findings support complex behavioral pharmacology of sulpiride in vivo and reconfirm high sensitivity of zebrafish-based screens to this and, likely, other related clinically active neuroleptics.

Cognitive and behavioral response of mosquitofish (Gambusia affinis) to environmental factors: Microplastics, predator cues, and detour design methods.

Urban stream syndrome is the collective term used to describe the physical and ecological degradation of streams draining urban lands that poses substantial threats to freshwater ecosystems. Among various consequences of urban expansion, microplastic pollution and shifts in predator-prey dynamics are prominent alterations to natural habitat that could impact the cognitive and behavioral responses of aquatic species. To explore how symptoms of urban stream syndrome impact the cognitive and behavioral responses of fish, we conducted two experiments using a delayed detour test to measure risk-taking and inhibitory control in Gambusia affinis. In the first experiment, we hypothesized that G. affinis exposed to different concentrations of microplastics would show altered inhibitory control and risk-taking. In the second experiment, we hypothesized that exposure to predator chemical cues during the detour task would alter inhibitory control and risk-taking in G. affinis. We did not find significant differences in inhibitory control or risk-taking in G. affinis exposed to microplastics or predator cues. We then compared the effect size and confidence intervals (CI) of these results with published results that used the same detour test to study inhibitory control and risk-taking in G. affinis in response to different environmental conditions. Our investigations revealed that the CIs of the two studies presented here were larger than the CIs in the previously published studies. We consider potential changes to the experimental design that might have affected our ability to detect differences, such as the dimensions of the testing tanks. We also suggest extending the duration of the test to allow ample time for both exiting the starting chamber and solving the detour. We also propose considering the size and age of the species under study and adjusting the dimensions used in the detour paradigm design. Although our findings are specific to G. affinis, our results underscore the importance of considering aspects of the detour test design that are ecologically relevant to the study species when analysing cognitive and behavioral responses in fish. With our discussion, we contribute to the understanding of detour test methodologies and highlight potential ecological factors that could influence cognitive and behavioral outcomes.

Acoustic Imaging Learning-Based Approaches for Marine Litter Detection and Classification

This paper introduces an advanced acoustic imaging system leveraging multibeam water column data at various frequencies to detect and classify marine litter. This study encompasses (i) the acquisition of test tank data for diverse types of marine litter at multiple acoustic frequencies; (ii) the creation of a comprehensive acoustic image dataset with meticulous labelling and formatting; (iii) the implementation of sophisticated classification algorithms, namely support vector machine (SVM) and convolutional neural network (CNN), alongside cutting-edge detection algorithms based on transfer learning, including single-shot multibox detector (SSD) and You Only Look once (YOLO), specifically YOLOv8. The findings reveal discrimination between different classes of marine litter across the implemented algorithms for both detection and classification. Furthermore, cross-frequency studies were conducted to assess model generalisation, evaluating the performance of models trained on one acoustic frequency when tested with acoustic images based on different frequencies. This approach underscores the potential of multibeam data in the detection and classification of marine litter in the water column, paving the way for developing novel research methods in real-life environments.

Ship-shaped vessel hydroelastic numerically supported analysis in a narrow ultra-reduced model tank with full scale extrapolation

Although the rigid body hypothesis is broadly used when studying floating bodies dynamics, it is known that a ship-shaped vessel will have hydroelastic responses. Considering a conventional closed main deck hull in which the ship's length is considerably greater than its breadth, it is expected that the vertical bending moments can represent an important load that must be considered to guarantee structural integrity. Numerical models can be developed to assess the hydroelastic response, but the validation process is necessary. Model tests can be performed to validate the numerical model and require specific considerations to properly represent hydroelastic phenomena, such as having equivalent bending stiffness when compared to the full-scale body. Many experimental facilities that can be used to perform such experiments consist of narrow wave channels, in which the wall effect will influence the model's dynamics. This work implements a Tank Green Function (TGF) to a numerical model developed in Capytaine to represent the wall effect on the body's response. The numerical results were then compared to experimental data from tests in a narrow wave channel and good adherence was found. The validated numerical model can then be used to simulate open-water conditions, so the results can be extrapolated to full scale without the need to perform model tests in an ocean tank in which the wall effect would not be relevant.

Chronic exposure to low concentration of diflubenzuron and pyriproxyfen induces brain oxidative stress and inflammation and alters locomotion in zebrafish (Danio rerio)

Diflubenzuron (DFB1) and pyriproxyfen (PPF) are pesticides widely used in agriculture and urban environments to control insect actions. The aim of this study was to evaluate the effects of chronic 30-day exposure to DFB (0.025 and 0.125 mg/L) and PPF (0.379 and 0.758 mg/L) on the behavior of juvenile zebrafish (Danio rerio). Fish were exposed to insecticides from early stage (4 h post fertilization) to 30 days post fertilization (dpf). At 45 dpf, fish were evaluated in the novel tank test, social behavior test, and mirror aggressive test. Brain gene expression related to oxidative stress and inflammation was also evaluated. DFB reduced locomotor parameters in the novel tank and aggression tests, while it induced to hyperactivity in the social behavior test. PPF reduced anxiety-like behavior, measured by the time spent in risky areas of the novel tank, and reduced aggression against the mirror image. There was a significant reduction in mRNA levels of the nfe2l2 gene (∼0.54 fold downregulated) and increase in levels of cat (PPF ∼1.8 fold change), gsr (PPF ∼1.5 fold change), gpx1a (PPF ∼1.6 and DFB 1.1 fold change), tnf-α (PPF 1.9 and DFB 2.2 fold change), and il-6 (PPF ∼1.2 and DFB 2.3 fold change). These endpoints are indicative of the threatening effects of insecticides to aquatic organisms and the need for alternative methods to control pests by using less harmful and safer substances for animal and human well-being, as well as for the environment.

Investigation of higher-order springing of a ship in regular waves by experimental analysis and two-way CFD-FEA coupled method

In this paper, the higher-order springing phenomenon is addressed for a segmented barge ship model through experimental and numerical measures. An efficient in-house two-way coupled numerical solver between Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) is developed and validated against experimental results. The coupling method is based on a domain-separated approach and necessitates the resolution of individual boundary value problems in distinct domains. To ensure convergence within these individual domains, an implicit numerical scheme is employed and further facilitated exchange of variables for coupling. The current approach emphasizes the overall convergence between two solvers, maintaining a strongly coupled setup to comprehensively address fluid-structure interaction phenomena, including added mass and damping effects. A series of tank tests were conducted first to measure the wave-induced sectional loads and motions, during which the springing responses to very high-order harmonics of wave load were observed. By comparing the numerical prediction with the tank test results for rigid body motion and flexible vertical bending moment (VBM), the proposed numerical method demonstrated agreement with experimental results, affirming its validity and robustness. Finally, the springing response up to 14th order harmonics is discussed and investigated.

Modelling Sea-Surface Wave Motion and Ship Response Using Smoothed Particle Hydrodynamics and Finite Element Analysis

The response of a ship or other vessel to surface sea waves, including extreme waves, may compromise crew and vessel safety and long-term operational capability. Herein, a novel high-fidelity numerical time-dependent simulation approach is presented using Smoothed Particle Hydrodynamics (SPH) for modelling sea waves coupled with Finite Element Analysis for modelling vessel structural response under wave loading conditions. The results are compared with physical scale model wave tank test results. Good agreement was obtained for heave and pitch motions and vertical bending moments for various forward (head) speeds in regular head waves, heave and pitch motions, and vertical bending moments. High computational demands can be met by the increasing availability of computation power. Ongoing research is outlined. The implications for the design of vessels such as ships and for through-life assessment are discussed.

Housing and Husbandry Factors Affecting Zebrafish (Danio rerio) Novel Tank Test Responses: A Global Multi-Laboratory Study.

The reproducibility crisis in bioscience, characterized by inconsistent study results, impedes our understanding of biological processes and global collaborative studies offer a unique solution. This study is the first global collaboration using the zebrafish (Danio rerio) novel tank test, a behavioral assay for anxiety-like responses. We analyzed data from 20 laboratories worldwide, focusing on housing conditions and experimental setups. Our study included 488 adult zebrafish, tested for 5 min, focusing on a variety of variables. Key findings show females exhibit more anxiety-like behavior than males, underscoring sex as a critical variable. Housing conditions, including higher stocking densities and specific feed types, influenced anxiety levels. Optimal conditions (5 fish/L) and nutritionally rich feeds (e.g., rotifers), mitigated anxiety-like behaviors. Environmental stressors, like noise and transportation, significantly impacted behavior. We recommend standardizing protocols to account for sex differences, optimal stocking densities, nutritionally rich feeds, and minimizing stressors to improve zebrafish behavioral study reliability.

Low-uncertainty wave tank testing and validation of numerical methods for floating offshore wind turbines

Abstract. Accurate simulation of the loads and motions of floating offshore wind turbines (FOWTs) in operation is key to the commercialisation of this technology. To improve such load predictions, a critical assessment of the capabilities and limitations of simulation methods for FOWTs is mandatory. However, uncertainties arise during the whole validation process of a numerical method. These can drastically impair the quality of the validation. In the case of FOWTs, the interaction between aerodynamic, hydrodynamic and mooring loads on the one hand and platform motions on the other hand causes a high level of uncertainty in the measurement data acquired in model tests. This also applies to comparing a numerical model to the test data, as these interactions make the distinction between cause and effect challenging. To address these challenges, several improvements to the validation process aiming to reduce the uncertainties are proposed and evaluated in this work. The major improvements are the measurement of the rotor thrust force excluding the tower top inertia loads, the wind field quality in the wave tank, a comparison of the rotor aerodynamics in the wind tunnel and wave tank, and the utilisation of hybrid simulations based on the measured platform motions. These steps are applied to wave tank tests of a FOWT utilising a single-point mooring and the subsequent validation of the numerical panel method panMARE. The improvements allowed for a considerable decrease in the random and systematic uncertainty in the model tests and made a valuable contribution to the distinction between cause and effect regarding the deviations between measurements and simulations.

Experimental Analysis of Cavitation Erosion: Parameter Sensitivity and Testing Protocols

The scientific goal of this study was to investigate the effects of various parameters on cavitation-induced erosion, with the aim to enhance the understanding and assessment of cavitation resistance in hydraulic systems. Cavitation erosion poses significant challenges to the durability and efficiency of hydraulic components, such as those found in hydropower plants and pumping stations. Prompted by the need to improve the reliability of cavitation testing and material assessment, this research conducted a comprehensive sensitivity analysis of a cavitation jet apparatus (CJA). This study employed an experimental platform that consisted of a vertical cylindrical test tank, a submerged nozzle, and an aluminum sample. By examining a range of orifice diameters, this research identified that smaller diameters led to increased erosion intensity, with the most pronounced effects observed at a diameter of 2 mm. Furthermore, various standoff distances (SoDs) were tested, which revealed that shorter distances resulted in greater erosion, with the highest impact noted at an SoD of 5 cm. This study also evaluated different nozzle geometries, where it was found that a 132° conical sharped edges nozzle, combined with an orifice diameter of 2 mm and an SoD of 5 cm, produced the most severe erosion. Conversely, chamfered edges nozzles and a commercial nozzle (MEG2510) with an SoD of 10 cm or greater showed reduced erosion. These results highlight that by standardizing the testing duration to 1200 s, the CJA could reliably assess the cavitation resistance of materials. This study established a clear relationship between increased pressure and higher impact forces, which led to more severe erosion. The findings underscore the effectiveness of the CJA in evaluating material resistance under various cavitation conditions, thus addressing a critical need for reliable cavitation testing tools.

Continuous and funnel-gate configurations of a permeable reactive barrier for reclamation of groundwater laden with tetracycline: experimental and simulation approaches

The current study investigates removing tetracycline from water using batch, column, and tank experiments with statistical modelling using ANN for continuous tests. An artificial neural network (ANN) using the Levenberg-Marquardt back-propagation (LMA) training algorithm is constructed to compare the effectiveness of Tetracycline removal from aqueous solution using the sorption technique with prepared adsorbent. Several characterization analyses XRD, FT-IR, and SEM are employed for prepared Brownmillerite (Ca2Fe2O5)–Na alginate beads. The operating conditions of batch tests involved, contact time (0.1–3 h), initial of tetracycline (Co) of (100–250 mg/L), pH (3–12), agitation speed (50–250) rpm and dosage of adsorbent (0.2–1.2 g/50 mL). The outcomes of experiments have demonstrated that the optimum conditions for the batch test to achieve the maximum adsorbent capacity (qmax =7.845 mg/g) are achieved at pH 7, contact time 1.5 h, adsorbent dose 1.2 g/50 mL, agitation speed of 200 rpm, and initial concentration of TC 100 mg/L. Minimum mean square error (MSE) values of 7.09E-04 for 30 hidden neurons and 0.0029 for 59 hidden neurons in the 1D and 2D systems are accomplished, respectively. The artificial neural network model has exhibited excellent performance with correlation coefficients exceeding 0.980 for the operating variables, demonstrating its accuracy and effectiveness in predicting the experimental outcomes. According to sensitivity analysis, the influential parameter in the column test (1D) is the flow rate (mL/min), with a relative importance of 32.769%. However, in the tank test (2D), time (day) is signified as an influential parameter with a relative importance of 31.207%.

Neurotoxicity of aluminium chloride and okadaic acid in zebrafish: Unravelling Alzheimer's disease model via learning and memory function evaluation

Introduction/objectivesAlzheimer's disease (AD) is characterised by a progressive decline in cognitive abilities, especially learning and memory. To validate the zebrafish as a suitable model organism for AD, the study examined the effects of 2 neurotoxin agents, aluminium chloride (AlCl3) and okadaic acid (OKA). In the full experimental design, both neurotoxins were administered intraperitoneally at 3 distinct doses (low, medium, and high) twice weekly for 21 days. At 3 time-points, behavioural tasks were conducted on day 7 (short duration), day 14 (moderate duration), and day 21 (long duration). The behavioural tasks consisted of a novel tank test lasting 6 min, followed by a T-maze tank test lasting 5 min. MethodsIn this article, the T-maze tank test was discussed in detail to evaluate which neurotoxins and their optimal dosages are impactful in developing a zebrafish AD model towards learning and memory functions. This evaluation measured four parameters: the amount of time spent in the wrong arm, the total distance travelled in the deeper chamber, and the 3-h and 24-h inflexion ratios. ResultsIn summary, a 100 nM dosage of OKA with a maximum of 21 days of evaluation resulted in significant (P<.05) outcomes in all parameters evaluated. The longest duration was spent in the wrong arm, accompanied by a reduction in the total distance travelled in the deeper chamber and a decreasing pattern in the 3-h and 24-h inflexion ratios. ConclusionThese observations suggest that OKA is the optimal choice of neurotoxin for a validated and optimised zebrafish AD model.

Design and Tank Testing of Reinforcement Learning Control for Wave Energy Converters

Design and Tank Testing of Reinforcement Learning Control for Wave Energy Converters

Experimental investigation on the longitudinal stability of the aerodynamically alleviated marine vehicle with multi-steps

To investigate the hydrodynamic performance and motion characteristics of the ultra-high-speed aerodynamically alleviated marine vehicle (AAMV) with multi-steps, a towing tank test scheme was designed and carried out at the China Special Vehicle Research Institute. The study analyzed the effects of canard angle, flap angle, longitudinal center of gravity, and displacement tonnage on the motion stability of multi-stepped AAMV at different speeds. The results indicate that the canard generates an overturning moment that reduces the resistance but brings forward the speed at which porpoising behavior occurs. Additionally, the backward shift of the longitudinal center of gravity causes motion oscillation during the high-speed planing phase, which negatively affects longitudinal stability. On the other hand, the flaps provide aerodynamic lift and restoring moments, improving the lift-drag ratio and enhancing longitudinal stability. Furthermore, while increased mass may result in higher total resistance, it can actually improve resistance performance per unit mass and improve the lift-drag ratio at cruising speed. The computational fluid dynamics (CFD) method was used to analyze the destabilization mechanism of AAMV under extreme conditions in the test. Numerical results indicate that the longitudinal stability of AAMV is directly affected by the relative positions of the center of gravity and the center of pressure. These results demonstrate the changing rules of resistance performance and longitudinal stability of AAMV under different design parameters, thus providing a powerful tool for optimizing AAMV.

Notes on Towed Self-Propulsion Experiments with Simulated Managed Ice in Traditional Towing Tanks

Efficiency estimation of a propeller behind a vessel’s hull while sailing through ice floes, together with the ship’s resistance to motion, is a key factor in designing the power plant and determining the safety measures of a ship. This paper encloses the results from the experiments conducted at the CEHINAV towing tank, which consisted of analyzing the influence of the concentration at the free surface of artificial blocks, simulating ice, in propeller–block interactions. Thrust and torque were measured for a towed self-propelled ship model through simulated broken ice blocks made of paraffin wax. Three block concentrations of different block sizes and three model speeds were studied during the experimentation. Open-water self-propulsion tests and artificial broken ice towed self-propulsion tests are shown and compared in this work. The most relevant observations are outlined at the end of this paper, as well as some guidelines for conducting artificial ice-towed self-propulsion tests in traditional towing tanks.

Emoxypine succinate modulates behavioral and molecular responses in zebrafish model of iron Overload-Induced neuroinflammation via CDK5/GSK3- β and NLRP3 inflammasome pathway

Excessive iron accumulation in the brain plays a significant role in neurodegenerative processes, contributing to the pathogenesis of Alzheimer’s disease (AD). AD, a prominent neurological disorder affecting the central nervous system, is characterized by the accumulation of beta-amyloid (Aβ) and tau phosphorylation. This accumulation leads to the subsequent development of cognitive impairments, particularly in learning and memory functions. This study investigates the neuroprotective effects of emoxypine succinate in a zebrafish model of iron overload-induced neurodegeneration. Iron was administered to the zebrafish for 28 days to induce neurodegeneration. Following induction, Emoxypine succinate was employed as a treatment intervention for 14 days (concentrations of 4 mg/L, 8 mg/L, and 12 mg/L). Following the end of the treatment, behavioral tests (Y maze test, Novel tank test) were conducted on the zebrafish, and the biochemical (MDA, Catalase, SOD, GSH) and molecular parameters (AchE, Iron levels, IL-1β, TNF-α, CDK-5, GSK-3β, and NLRP3) of the zebrafish brain were also assessed. In the novel tank test, emoxypine succinate-treated groups exhibited significantly increased time in the upper zone (p < 0.001), higher distance travelled (p < 0.001), and shorter latency to the top (p < 0.001) compared to the negative control. Similarly, the Y-maze test revealed improved time in the novel arm (p < 0.001) and total distance travelled (p < 0.001) in treated groups versus the negative control. Assessment of oxidative stress parameters demonstrated significant reductions in oxidative stress in emoxypine succinate-treated groups. Furthermore, AChE activity decreased significantly (p < 0.001), and brain iron levels decreased substantially (p < 0.001) in treated groups, indicating positive therapeutic outcomes. Molecular analysis showed a significant reduction in pro-inflammatory markers like IL-1β, TNF-α, CDK-5, GSK-3β, and NLRP3 (p < 0.001). This comprehensive study highlights the potential efficacy of emoxypine succinate in mitigating neurodegeneration associated with iron dysregulation.

SEDIMENTATION IN HYDROELECTRIC POWER TURBINES

The primary cause of erosive wear and energy loss is friction, and reportedly, one-third of the world’s energy resources go to overcome friction by several methods. The presence of deposits in water is a common problem in mountainous regions and some Ukrainian hydroelectric power stations. Hydro turbines face serious issues related to erosion from deposits during operation. Erosive wear occurs due to the impact of solid particles against a solid surface. The current environment contains particles whose velocity is sufficient to damage metal surfaces. Various researchers have conducted numerous studies to minimise the effect of deposit erosion in multiple locations of Francis turbine components (FT). For this purpose, they performed field investigations, experimental measurements, empirical modelling, computational fluid dynamics (CFD) work, and other methods. Various empirical models have been used to describe erosive wear in terms of material and fluid properties. They established that, for ductile materials, maximum erosion occurs at an impact angle of 30°, whereas for brittle materials, it occurs in the range of 80–90°. In the literature, various experimental methods are available to quantitatively assess slurry erosion, such as the rotating disk apparatus (RDA), slurry tank testing, jet erosion testing, and rotating drum testing. Due to manufacturing technologies used in mechanical processing processes, the exposed surface has a certain absolute roughness that increases during machine operation due to abrasion or erosion. Therefore, surface texture leads to increased energy efficiency losses during operation. Technological advancements have facilitated the widespread use of computational tools to address deposit erosion issues. In recent decades, numerical methodology has been a widely used and effective tool, yielding tangible and reliable results. This study examines potential methods for detecting and reducing deposits. This type of erosion depends on flow characteristics, surface properties, and properties of the eroding material. The article provides comprehensive information on sedimentation (deposits) causing wear in hydraulic turbines. Keywords: hydroelectric turbine, sedimentation erosion, computational fluid dynamics, fluid-structure interaction.

The Blockage Effect on Resistance Coefficients Estimation for AUVs with Different Configurations in the Towing Tank

When a resistance test of an underwater vehicle model is conducted in a towing tank, the blockage effect will inevitably occur, particularly since the experimental model is relatively large. This paper investigates the estimation of resistance coefficients for an Axisymmetrical Rotary Body Underwater Vehicle (ARBUV) and a Blended Wing Body Underwater Vehicle (BWBUV). The Computational Fluid Dynamics (CFD) method is employed to predict the resistance of Autonomous Underwater Vehicles (AUVs). In order to quantify the blockage effect on the resistance coefficients of AUVs with different configurations, the resistance coefficients of AUVs are calculated in the infinite domain and finite domain under various blockage ratios. Through analysis of the resistance results, velocity distribution, and pressure distribution, the action law of the blockage effect is provided. It indicates that blockage effects have a greater influence on the pressure resistance for ARBUV. Surprisingly, the resistance coefficients of BWBUV are less affected, though it is closer to the sidewalls. It suggests that the blockage ratio of ARBUV and BWBUV should be separately smaller than 0.375% and 2.5% in the towing tank test. The towing tank experiments satisfy the blocking ratio with a Reynolds number greater than 107, which saturates the blocking effect and further reduces the effect on the drag coefficient.

An attention-neural-processes approach to reconstructing unsteady water load for seaplanes

The distribution of holographic unsteady water load offers important information for evaluating the hydrodynamic performance of seaplanes. However, traditional tank test is limited by the number of sensors that can be deployed on the bottom of hull, thus only providing sparse data for estimating load distribution and leading to inaccurate evaluation of seaplane performance. To achieve accurate and rapid reconstruction of holographic load distribution, a machine learning load-reconstruction model based on Attention Neural Processes is proposed. This model performs spatiotemporal modeling of seaplane water load utilizing sparse sensor data. It directly learns the load patterns across multiple time steps and employs Attention modules to capture the spatial distribution of load. Comparisons with alternative methods demonstrate the model's superior ability to simultaneously capture spatial and temporal dependencies of the unsteady load data. In addition, the model's robust generalization capability is also validated by reducing the number of sensors in the training data. The results indicate that the proposed model exhibits high prediction efficiency, accuracy, and generalization for the reconstruction of unsteady water load distribution, which is of great significance for comprehensively evaluating the hydrodynamic performance of seaplanes.

Experimental and numerical study on the flow and heat transfer of ring-ribbed tank in deep-sea manned submersible

The ring-ribbed tank is the key equipment of cooling system of deep-sea manned submersible. The heat transfer characteristics of the outer wall and the heat transfer and flow characteristics of the inner flow channel of the ring-ribbed tank for different inlet and outlet temperatures and flow rates were studied through a water tank test. The results indicate that Nusselt number for the inner flow channel correlates with Reynolds and Prandtl numbers, while for the outer wall, it correlates with Grashof and Prandtl numbers with an overall error within 5%. A numerical study using the Realizable k-ε turbulence model and Boussinesq approximation of the flow-solid conjugate heat transfer is conducted, which can accurately determine the heat exchange capacity and the import and export differential pressure with an average relative error of 1.98% for hot water temperature and 7.73% for shell wall temperature. Additional simulations for determining the heat transfer capacity and flow resistance characteristics of the ring-ribbed tank in open water results demonstrate that the differential pressure and its coefficient are basically consistent with model test results. The cooling system can achieve a heat transfer rate of up to 17 kW with an external seawater flow velocity of approximately 2 knots.