Underwater Structure Research Articles

A Flexible Alternating Current Field Measurement Magnetic Sensor Array for In Situ Inspection of Cracks in Underwater Structure

A Flexible Alternating Current Field Measurement Magnetic Sensor Array for In Situ Inspection of Cracks in Underwater Structure

Vibro-Acoustic Analysis of an Underwater Cylindrical Shell with Internal Structures and a Comparison with Experiment

Abstract: In this work, the low-frequency vibration response and full-band acoustic radiation characteristics of an underwater reinforced cylindrical shell with internal structures are studied by combining the FEM with SEA. The stiffened cylindrical shell contains internal structures such as the F-shape plates and the support valve frames. The exciting sources have two different exciting forces corresponding to two experimental conditions. In the low-frequency band, the FEM was employed, and in the medium and high-frequency bands, the SEA was used. A comparison of the numerical results and the experiment shows that they agree well. The FEM and SEA give better results at [1,1k] Hz and [1k,10k] Hz, respectively. Due to mesh quality limitations, the FEM is not favorable for medium and high-frequency calculations. The SEA focuses on the structural mean power flow but cannot obtain position-specific vibrational responses. The results show that the internal excitation source mainly causes the structural vibration and sound radiation and are closely related to the free vibration characteristics of the structure. In addition, with the increase in frequency, the circumferential sound pressure level of the underwater structure has more substantial directivity.

Methodology based on the Hu moment invariants for object comparison on radar satellite imagery

In this paper we present a methodology for comparing objects, identified on satellite images acquired by Synthetic Aperture Radar (SAR). The methodology describes object transformations mathematically and provides a quantitative estimate of the similarity of different shapes. To demonstrate its capabilities we examine a case study – we detect an underwater structure in the Western Black Sea, which becomes visible on radar imagery under favourable sea conditions. Our aim is to quantitatively describe if it changes over time and to determine on which dates the detections reveal the greatest similarity.The suggested methodology is based on computation of the Hu moment invariants, or the image moments. They give a set of 7 invariants, which describe object transformations, such as translation, scale, rotation and reflection. The presented methodology can be applied in different contexts on satellite imagery for quantitative description of structure transformations.

On the radiation of sound from an immersed cylindrical shell close to the sea surface

Numerical methods for the prediction of underwater radiated noise from immersed structures play a key role in the naval and offshore industry to ensure high acoustic performance of systems or to preserve natural habitats. Most of the approaches so far assume that the surrounding fluid is homogeneous and unbounded. However, in many situations the structure can be close to interfaces, namely the sea surface and the sea bottom, such as navigation of underwater vehicles in shallow waters. The Lloyd's mirror effect describes the interference phenomena occurring when a sound source is close to the sea surface. This effect is easily accounted for with a source image approach, while the strong vibro-acoustic coupling between the structure and the interface is more complicated to deal with. In this context, an analytical method has recently been developed to predict the vibro-acoustic behaviour of an infinite length cylindrical shell close to the surface, based on the shell equations and Graf's addition theorem. In the present work, we compare this approach to a simplified one where the strong interactions between the surface and the structure are not considered. Results highlight these effects on a typical underwater structure

Investigation on the working performance of a non-dispersible grouting material for the crack repairment of underwater structures

Underwater structure repair is highly susceptible to various factors, including the pressure of the underwater environment and dynamic water flow. Traditional materials used for repairs are prone to dilution and dispersion, resulting in a subpar repair outcome. To address the limitations of traditional grouting materials, specifically their poor retention rate and vulnerability to erosion caused by dynamic water, an underwater non-dispersible crack repair grouting material was developed. It is composed of liquid epoxy resin, curing agent, and aggregate (ECA). Comprehensive and systematic testing was conducted to evaluate the performance of ECA grout. The results show that optimized ECA grouting material has advantages such as a high retention rate under dynamic water erosion, strong adhesion, high fluidity, high early strength, and suitable setting time. The ECA grout demonstrates excellent underwater working performance. In addition, the microstructure was analyzed using X-ray diffractometry (XRD), Fourier-transform infrared spectroscopy (FTIR), and environmental scanning electron microscopy (ESEM). The results show that the addition of aggregates to the epoxy resin does not cause any chemical reaction. Furthermore, the aggregates are bonded together by epoxy resin. Due to the formation of cross-linked microstructures, the microstructure becomes more compact. The addition of aggregates during the curing process has good compatibility and stability, which enhance the performance of the ECA grout. The material has been successfully applied in a restoration project of underwater cultural relics protection facilities, effectively addressing and repairing the existing defects. Its potential value as a reference for similar projects is substantial.

Numerical modeling and simulation of underwater explosions interacting with discrete rigid bodies

The smoothed particle hydrodynamics (SPH) method is widely used to simulate underwater explosion phenomena. However, previous studies have focused on the interaction between the underwater explosion and continuous structures (e.g., steel plates and dams), while studies on the interaction between the explosion and discrete objects (e.g., debris) have not been reported. In this study, a multi-media coupled model containing water, explosion gas, discrete objects, and steel plates is developed based on the SPH method. The discrete object is modeled as a rigid body with a certain shape, which is discretized by SPH particles. The interaction between the discrete object and the adjacent fluid particles is realized by the kernel approximation, while the collision between different objects is realized by the contact algorithm. To improve the numerical stability, an artificial viscous term containing a threshold switch is added to the SPH momentum equation, while a density dissipation term is introduced into the continuity equation to reduce the noise of the pressure field. Subsequently, the established SPH model is used to simulate the underwater explosion process containing discrete rigid bodies, and the effects of the distribution, stacking form, and number of rigid bodies on the propagation of shock waves, bubble expansion, and deformation of steel plates and the effect of damage are analyzed. The results show that the rigid body will hinder the propagation of shock waves, help reduce the peak pressure of the shock wave behind, and then affect the direction of the diffusion of the explosion energy. Shock waves would produce diffraction, reflection, and transmission when passing through the rigid bodies, and the superposition of various waves would make the pressure distribution near the liquid–gas interface irregular. The rigid bodies stacked above the explosives would enhance the damage effect of the explosion on the steel plates below, and the damage effect is affected by the stacking form. The established model can simulate the multi-medium coupling process in a unified framework without coupling other methods and can effectively restore the complex interaction process between underwater explosion, discrete object, and structure.

Multi-objective optimization decision-making of an underwater vehicle rotary docking skirt structure

This study determines the design parameters, analysis methods, and mesh size of a finite-element analysis model in the structural design of a rotary docking skirt (RDS) structure for an underwater vehicle. The impact of the structural design variables on the response is then studied. The sample points determined using the optimal Latin hypercube method are analyzed and fitted with the Kriging model, response surface model, and radial basis function. After comparing the fitting accuracies of the three approximation models, an approximation model of the RDS structure is determined. Next, several typical multi-objective optimization algorithms are tested and the improved nondominated sorting genetic algorithm II (INSGA-II) is selected for establishing an optimization model of the RDS structure. INSGA-II obtains the Pareto solution set of multi-objective optimization. The weights are obtained by combining the subjective and objective weights determined through the subjective-weighting analytic hierarchy process and the objective-weighting entropy weight method, respectively. Based on the combination weight, the technique for order preference by similarity to the ideal solution method is selected for multi-objective optimization decision-making. The final decision-making scheme of the rotary docking skirt structure improved the optimization effect compared to the initial scheme.

An Experiment of the Actual Vertical Resolution of the Sub-bottom Profiler in an Anechoic Tank

Sub-bottom profiler (SBP) is an acoustic instrument commonly used to survey underwater shallow geological structure and embedded objects whose most important performance parameter is the actual vertical resolution. This paper presented a methodology to measure and evaluate the actual vertical resolution of SBP based on an experiment in an anechoic tank, which was divided into three components: building of artificial geological model, measurement of acoustic parameters, and determination of actual vertical resolution of the acoustic profiles. First, the wedge-shaped geological model, whose thickness could be accurately controlled, was designed and built in an anechoic tank to try to directly measure the vertical resolution of SBP. Then, the acoustic pulse width of SBP was measured to calculate the theoretical general vertical resolution and extreme vertical resolution. Finally, based on the acoustic profiles obtained in the experiment, the method which was used to evaluate the actual vertical resolution by measuring the duration of reflection event was put forward. Due to comparing measurement data of different parameter settings of the SBP, the study has revealed that the SBP had the lowest resolution in the 4 kHz-500 μs setting, which was 226.5 μs, or 36.2 cm, and the highest resolution in the 15 kHz-67 μs setting, which was 72.7 μs, or 11.6 cm. The vertical resolution decreased with the increase of the pulse width. The results also showed that the actual resolution was close to the theoretical general resolution and far from the extreme resolution.

Vibroacoustic analysis of a submarine-propeller system under self-propulsion condition from the perspective of approximate configurations

As a particular instance of the complete acoustic radiation problem for an underwater structure, structure-borne noise radiated from a combined submarine-propeller system under self-propulsion condition is investigated. The analysis procedure applies a set of numerical methods to capture different aspects of the problem: unsteady computational fluid dynamics to express the hydrodynamic excitation, finite element analysis to obtain the dynamic characteristics of the combined elastic system, and boundary element method to assess the radiated noise owing to structural vibrations. The structural and acoustic responses rely on the modal descriptions. The study has three objectives: employing the methodology in a realistic setting, investigating the validity of the proposed approximate configurations, and studying the influence of propeller blade flexibility on noise radiation. The DARPA-SUBOFF submarine and INSEAN E1619 propeller models are adopted for the application. It is found that approximate configurations provide accurate estimations for limited frequency bands and should be employed with caution. In addition, the flexibility of the propeller plays a major role in noise generation, not only by yielding higher noise levels but also by increasing the amplitude of the peak responses in the low- and high-frequency regions.

Optimisation of an underwater vehicle rotary docking skirt structure

ABSTRACT This paper presents a comprehensive procedure for the parametric design and analysis of a underwater vehicle rotary docking skirt (RDS) structure. Different types of software were integrated to improve the design efficiency, and different techniques were used to establish an approximate model of the RDS structure with high fitting accuracy. Nondominated sorting genetic algorithm II (NSGA-II) was improved by dynamic adjustment of the population size according to the number of iterations and new crossover and mutation operations (i.e. INSGA-II), which was then applied to a multi-objective optimisation model of the RDS structure. A Pareto solution set was obtained, and a sensitivity analysis was performed on the design variables and objective functions of four representative optimisation schemes. These results can be used to provide a richer selection for designers to reference when designing RDS structures. Abbreviations: RDS; Rotary docking skirt; NSGA-II; Nondominated sorting genetic algorithm II

Dynamic response analysis of spherical pressure hull implosion inside adjacent underwater structure

The implosion will occur when the pressure hulls have a geometric imperfection or are impacted from the outside, which could cause the collapse of submerged vessels. In this work, the open-source finite element solver OpenRadioss is used to analyze the implosion caused by the failure of the spherical pressure hull and the interference with the adjacent cylindrical shell in the double-hulled cabin of a submarine. Firstly, the implosions of the cylindrical tube and destruction of the spherical pressure hull are compared with experimental results. Secondly, the underwater implosion of the sphere is analyzed inside a cylinder with local impacts in different induced directions. The results found the flow field and structural deformation show obvious directivity, in which the deformations of the cylindrical shell are mainly caused by the absorption action instead of the shock wave effect when implosions occur in the direction closer to the cylinder. Finally, the dynamic responses of implosions are discussed under different triggering modes and hydrostatic pressures. We found that the structural deformation and energy evolution are similar when the sphere is subjected to a collapse load. However, the effect of triggering modes gradually becomes larger with the increase of hydrostatic pressure.

Simulation evaluation of underwater robot structure and control system based on ADAMS

Abstract The twenty-first century is the century of marine resources. The ocean is a treasure of biological resources, energy, water resources and mineral resources, and it would gradually become the “second space” of mankind. In the next few years, it would be more and more relevant to human life. Many scholars have realized the importance of the ocean and began to vigorously develop and use the ocean. Underwater robot is a means for human beings to explore and develop the ocean, and it would be widely used in this field. The development and promotion of underwater vehicles are of great significance to resource development, economic development, and national security. With the increasing shortage of land resources, the development and utilization of marine resources have received increasing attention. The direct exploitation of marine resources by humans would have adverse effects, so the underwater robot technology has developed rapidly in recent years. However, at present, most underwater robots are driven by electric turbines. The underwater working environment requires that the underwater motor has good sealing performance, so its structure is complex and expensive, and it is rarely used in ordinary underwater operations. In recent years, intelligent robots have been used more and more, but because of the complexity and uncertainty of the underwater working environment, there are many uncertain factors. Therefore, it is very meaningful to carry out stability control for it. The research results showed that the displacement, stability, and other corresponding test curves of each component can be obtained by establishing a simple model with software and through ADAMS (Automatic Dynamic Analysis of Mechanical Systems) simulation analysis. This can simulate the movement of real objects in the real environment and find the existing problems, so as to provide a reference for the actual underwater robot design. In this way, the development cycle and production costs can be reduced. This article analyzed the structure and control system of the underwater vehicle based on ADAMS simulation. The results showed that the dynamic stability of the underwater vehicle based on ADAMS simulation analysis was improved by 4.67% compared with the underwater vehicle before optimization.

Natural threat to the Turkish straits sea area: the mucilage

The Turkish Straits Sea Area comprises the Istanbul, the Canakkale Straits, and the Marmara Sea. The area is the most essential natural waterway connecting the continents of Asia and Europe. However, as of May 2021, it is polluted with Mucilage which is a slippery mass of microorganisms mostly clustered together, covering large areas, mainly in the Sea of Marmara and locally in the Turkish Straits. Unicellular organisms release fatty acids from the body under stressful environmental conditions. The Turkish Straits Sea area, which also connects the Black Sea and the Aegean Sea, constitutes a critical marine habitat among marine species. On the one hand, ballast operations create a sticky surface on the ship's hull and the underwater structure in contact with water. At the same time, there is also the necessity of cooling the ship's machinery with seawater. Ship cooling systems use seawater to cool the ship's engine block, while filtration prevents damage to the system. However, the mucilage effect affects the control of the vessel by causing clogging of the filters that serve to protect the system. The fact that the water taken by filtration is affected by Mucilage, clogging, and involving the outer surface of the ship affects the safety of the vessel at a high level. This research article tries to explain the damage and effects of Mucilage on ships sailing in the Turkish Straits.

Automatic Detection of Surface Defects on Underwater Pile-Pier of Bridges Based on Image Fusion and Deep Learning

As an important part of the bridge structure system, the underwater pile-pier structure usually occurs various defects on its surfaces due to its complex hydrological environment. The existing conventional defect detection approaches exist two aspects of problems: (1) insufficient definition and color distortion of the underwater images, and (2) low efficiency and error-prone. To solve these problems, this paper proposed the target defect detection model by integrating the image-fusion enhancement algorithm and the deep learning algorithm. Firstly, by analyzing the reasons for the degradation of the underwater images, the ACE (automatic color equalization) and CLAHE (contrast limited adaptive histogram equalization) algorithms are selected to enhance the image, respectively. Secondly, the two enhanced images are fused based on the point sharpness weight, and then the fusion results are further sharpened by the USM (unsharp mask) algorithm, thus obtaining the final fused images. Thirdly, 3,200 fused images are taken as the training set, by adopting the YOLOv3 algorithm to train the detection model, and then the training model is validated and tested by the other each 400 fused images, thus building up the target automatic detection model of underwater pile-pier surface defects. Finally, a series of comparison and discussion were conducted to validate the effectiveness of image-fusion and the robustness and effectiveness of the target detection model. The results found that the target detection model has excellent robustness against noise and effectiveness in the surface defect detection. This indicates that the image-fusion approach proposed in this paper can effectively enhance the image features, and the target detection model is feasible, robust, and effective in the automatic detection of surface defects on underwater pile-pier structures.

Vibro-Acoustic Performance of a Fluid-Loaded Periodic Locally Resonant Plate

The vibro-acoustic performance of a fluid-loaded periodic locally resonant (LR) plate was examined in this research, with a specific focus on the effect of water fluid on the vibration and sound radiation of the LR structure. The analytical models of the fluid-loaded LR plate’s band gap, vibration, and acoustic radiation were theoretically derived with closed-form solutions, which can be used to predict the general vibro-acoustic rules of underwater LR structure. The results show that the LR band-gap width and Bragg frequency are significantly reduced when water fluid is considered. Besides, the frequency range that can be tuned to control the vibration and sound radiation for the LR plate with fluid is much narrower than that without fluid. The reason for inducing the above effects was also given in this research, which can be physically explained by the attached mass caused by the water fluid. In addition, the reason for the enhanced radiation efficiency close above the band gap was also discussed, which is caused by the change of radiation mode from corner or edge radiation to monopole radiation. Furthermore, adding small damping into the resonator could reduce the vibration and sound radiation in the frequency range above or close below the band gap, inducing the attenuation zone to be significantly broadened. Thus, designing the periodic resonators with proper damping could be an efficient method to make the LR plate more beneficial for vibration and noise reduction in water-surrounding applications.

Prediction Method for RUL of Underwater Self-Enhancement Structure: Subsea Christmas Tree High-Pressure Valve Actuator as a Case Study

Underwater pressure-bearing structures are produced in practice by means of pressure self-enhancement methods in order to improve the stress distribution and enhance the pressure-bearing performance. On the other hand, the pairs equation shows that stress is an important factor influencing the degradation of the structure. In fact, improving the stress distribution will not only improve the pressure-bearing performance, but will have an impact on the life degradation trend. Thus, pressure self-enhancement affects the structural life by changing the stress distribution. With this in mind, this paper considers the effect of pressure self-enhancement on the service time of subsea structures, and a Bayesian network (BN)-based method that can be used to predict the remaining useful life (RUL) of underwater self-enhanced structures is proposed. The method also takes into account the influence of multiple sources of structural factors in order to predict the RUL of the structure more accurately. The life degradation process of an all-electric Christmas tree valve actuator is used as a case study. The prediction results are compared with data in the literature to verify the validity of the method. The results have implications for guidance on the O&M assurance of underwater production systems.

An efficient underwater absorber using pentamode metamaterials for broadband frequency

To further design and develop broadband and efficient underwater sound absorption structure, we propose a hybrid acoustic structure composed of a rubber matrix layer, cylindrical cavity, pentamode metamaterial (PM) layer, impedance matching layer, and steel backing plate. Thanks to the special properties of the PMs, the hybrid acoustic structure obtains excellent broadband sound absorption performance (SAP) in the frequency range of 500–10000 Hz than that of the traditional cavity acoustic structure. To this end, we study the design principle of PM structure and its metal–water characteristics and analyze the sound absorption mechanism at the working frequency. In addition, the research shows that the material and geometric parameters of the structure have a significant impact on the SAP. By the optimization of structural material parameters, the average absorption coefficient at 500–10000 Hz can further increase to above 0.781. Finally, we also demonstrate that the structure still has good SAP under a wide range of oblique incidence angles. The research in this paper opens up bright perspectives for the design of underwater anechoic coatings for multifunctional applications.

An inversion method of subsurface thermohaline field based on deep learning and remote sensing data

ABSTRACT Seawater temperature and salinity are basic marine environmental parameters, which can be used to calculate other marine environmental parameters. However, most of the on-site observation data have the problems of uneven spatial distribution and time discontinuity, and it is difficult for remote sensing observation methods to obtain subsurface information. In this study, we proposed a deep learning model with combining remote sensing temperature and salinity as well as in-situ measured data by Argo profiles, and the nonlinear relationship was revealed. An effective and direct inversion method was realized for underwater three-dimensional thermohaline structure based on remote sensing temperature and salinity at accurate points on global scale. The SST data were obtained from the FY3C-VIRR daily sea surface temperature product, the SSS data were acquired from the SMAP Level 3 8-day running averages sea surface salinity product, and the Argo scatter data were got from the ‘Global Ocean Argo Scatter Data Set’. Based on the temporal and spatial location information of the data, this paper matched the remote sensing data from 2016 to 2019 with the Argo data, 64751 valid pairing points were obtained. The deep learning model was constructed as a multilayer perceptron model with 5 hidden layers. The RMSE of temperature had a maximum value of 2.106°C in 130 m depth and a minimum value of 0.367°C in 1000 m with an average of 1.174°C for validation dataset. And the RMSE of salinity had a maximum value of 0.356 psu in 0 m and a minimum value of 0.045 psu in 1000 m with an average of 0.202 psu. Compared with other methods based on fixed mesh products, this study realized a direct inversion method at any location in the global ocean and improved the inversion accuracy, which provides a reliable data support for refined marine monitoring.

Real-time prediction of mechanical behaviors of underwater shield tunnel structure using machine learning method based on structural health monitoring data

Predicting the mechanical behaviors of structure and perceiving the anomalies in advance are essential to ensuring the safe operation of infrastructures in the long run. In addition to the incomplete consideration of influencing factors, the prediction time scale of existing studies is rough. Therefore, this study focuses on the development of a real-time prediction model by coupling the spatio-temporal correlation with external load through autoencoder network (ATENet) based on structural health monitoring (SHM) data. An autoencoder mechanism is performed to acquire the high-level representation of raw monitoring data at different spatial positions, and the recurrent neural network is applied to understanding the temporal correlation from the time series. Then, the obtained temporal-spatial information is coupled with dynamic loads through a fully connected layer to predict structural performance in next 12 h. As a case study, the proposed model is formulated on the SHM data collected from a representative underwater shield tunnel. The robustness study is carried out to verify the reliability and the prediction capability of the proposed model. Finally, the ATENet model is compared with some typical models, and the results indicate that it has the best performance. ATENet model is of great value to predict the real-time evolution trend of tunnel structure. • A more credible prediction model is presented to solve practical engineering problem. • Timely prediction for the subsequent state and precise perception for anomaly in advance. • Interdisciplinary research of machine learning in the analysis of structural mechanical behaviors.

Extreme Underwater Image Compression Using Physical Priors

Underwater images (UWIs) require higher compression ratio than terrestrial images due to the limited bandwidth of underwater wireless acoustic channel. In many studies such as marine species, the foreground objects (FGOs) in UWIs need to be observed in detail, while the background only needs to be viewed in general. However, existing image compression methods achieve limited compression ratio and reconstruction quality, which cannot fulfill these practical applications since they do not consider the unique underwater physical priors. To overcome the limitation, we propose an underwater physical prior-based extreme compression network (PPECN) for UWIs compression, which includes an underwater physical prior-guided FGOs autoencoder (UPGAE) and a FGOs-assisted background generator (FG-BGGAN). Specifically, we design an underwater physical prior guidance structure that simulates the data flow in the underwater physical imaging process to adaptively adjust the distribution of received Gaussian features in the UPGAE to be more consistent with real UWIs. During the adjustment, some basic UWI properties can be reconstructed, which can improve the reconstruction quality and implicitly reduce bits through the end-to-end training. Furthermore, the background is generated from simple semantic map under the constraint of the perceptual consistency between background and FGOs, significantly saving coding bits and improving the perceptual quality of the generated background. Extensive experimental results on four underwater image datasets verify that, compared with state-of-the-art compression methods, our PPECN achieves both impressive improvement in the perceptual quality of the whole image and significant gain in the pixel fidelity of the FGOs at the similar low bitrate.