Underwater Conditions Research Articles

Submerged pulsating water jet erosion of ductile material

This article deals with the manifestations of erosion of statically acting concentrated multiple droplet impingements on materials over different lengths of time in order to assess the erosion evolution when the materials are submerged, as compared with the action of droplets on the materials under atmospheric conditions. The study aims to determine the extent of the erosive effects of droplets in underwater conditions. Experiments were conducted in a plastic pool in which the water level was varied from h = 80 to h = 120 mm to identify the effect of hydrostatic pressure at p120 = 0.1025 MPa and p80 = 0.1021 MPa. The results were compared with that of a control group of samples obtained under atmospheric air conditions. To observe the erosive damage evolution, 15 (n = 5) sites on the ductile materials EN AW-Al 99.5 and CW004A were exposed to high-intensity droplet impingement at defined exposure times. The exposure time varied from 0.125 s to 1.875 s, with increments of 0.125 s. As a droplet generator, an ultrasonic pulsating water jet with a frequency f = 20 kHz, a pressure p = 30 MPa and a nozzle diameter d = 0.4 mm was used to achieve the theoretical subsonic speed of the droplets. The results exceeded the assumptions regarding the possible attenuation of water pulses. It was found that under the theoretical speed of the jet vw = 225 m/s, the submerged condition causes attenuation in its erosive action. The incident area in the case of submerged treatment was more symmetrical. The erosion shift in term of prolonging incubation erosion stage was found to be a result of the increasing hydrostatic pressure. The results suggest that this method can also be used under submerged conditions for treatment or material drilling.

Asymmetric toughening in the lap shear of metamaterial structural adhesives.

Metamaterial structural adhesives (MSAs), whose properties primarily rely on structural design, offer promising advantages over traditional adhesives, including asymmetric, switchable, and programmable adhesion. However, the effects of thick backing structures on the adhesion properties remain largely underexplored. Herein, we investigate a series of MSAs featuring a thin adhesive layer and an asymmetric thick beam structure terminated with a film. We conduct lap shear tests on the MSAs with varying terminated film thickness (t) and beam tilting angle (θ) while maintaining an identical adhesive layer. For MSAs with a thick terminated film (t = 2 mm), the effective adhesion energy is double that of solid samples without compromising shear strength, consistent with the theoretical predictions based on the crack trapping mechanism. Conversely, for MSAs with a thin terminated film (t = 0.5 mm), the maximum shear strength and effective adhesion energy are ∼2.8 times and ∼18.6 times those of solid samples, respectively, deviating significantly from the theoretical predictions due to new crack initiations. We further explore adhesion asymmetry by tuning the beam tilting angle (θ). For MSAs with highly tilted beams (θ = 70.3°), we achieve a maximum adhesion strength asymmetry factor of τ2/τ1 ∼ 2.2 for a thick terminated film (t = 2 mm), and a maximum adhesion energy asymmetry factor of Γ1/Γ2 ∼ 5.3 for a thin terminated film (t = 0.5 mm). Our work provides useful insights for designing metamaterial structural adhesives suitable for robotic grippers, wall-climbing robots, and wearable devices, particularly those requiring asymmetric, switchable, and stimuli-responsive adhesion, and adhesives on rough surfaces or in underwater conditions.

Inspection Operations and Hole Detection in Fish Net Cages through a Hybrid Underwater Intervention System Using Deep Learning Techniques

Net inspection in fish-farm cages is a daily task for divers. This task represents a high cost for fish farms and is a high-risk activity for human operators. The total inspection surface can be more than 1500 m2, which means that this activity is time-consuming. Taking into account the severe restrictions for human operators in such hostile underwater conditions, this activity represents a significant area for improvement. A platform for net inspection is proposed in this work. This platform includes a surface vehicle, a ground control station, and an underwater vehicle (BlueROV2 heavy) which incorporates artificial intelligence, trajectory control procedures, and the necessary communications. In this platform, computer vision was integrated, involving a convolutional neural network trained to predict the distance between the net and the robot. Additionally, an object detection algorithm was developed to recognize holes in the net. Furthermore, a simulation environment was established to evaluate the inspection trajectory algorithms. Tests were also conducted to evaluate how underwater wireless communications perform in this underwater scenario. Experimental results about the hole detection, net distance estimation, and the inspection trajectories demonstrated robustness, usability, and viability of the proposed methodology. The experimental validation took place in the CIRTESU tank, which has dimensions of 12 × 8 × 5 m, at Universitat Jaume I.

Skin-Integrated Electrodes Based on Room-Temperature Curable, Highly Conductive Silver/Polydimethylsiloxane Composites.

The quality of electrophysiological (EP) signals heavily relies on the electrode's contact with the skin. However, motion or exposure to water can easily destabilize this connection. In contrast to traditional methods of attaching electrodes to the skin surface, this study introduces a skin-integration strategy inspired by the skin's intergrown structure. A highly conductive and room-temperature curable composite composed of silver microflakes and polydimethylsiloxane (Ag/PDMS) is applied to the skin. Before curing, the PDMS oil partially diffuse into the stratum corneum (SC) layer of the skin. Upon curing, the composite solidifies into an electrode that seamlessly integrated with the skin, resembling a natural extension. This skin-integration strategy offers several advantages. It minimizes motion artifacts resulting from relative electrode-skin displacement, significantly reduces interface impedance (67% of commercial Ag/AgCl gel electrodes at 100Hz) and withstands water flushes due to its hydrophobic nature. These advantages pave the way for promising advancements in EP signal recording, particularly during motion and underwater conditions.

Self-powered sensors for flexible electronic skins capable of self-healing under multiple extreme environments

With the advancements in electronic skins (E-skins) and communication technologies, the applicability of sensors in extreme environments poses significant challenges. While various sensors have been reported, maintaining electrical output performance without external power source and self-healing capability across multiple extreme environments remains a hurdle. Herein, we present flexible, self-healing, and harsh environment-resistant self-powered sensors for E-skins, the self-healing capabilities of which are virtually invulnerable in diverse extreme environments, including underwater, saline, oxidized, alkali, and acid conditions, as well as low and high temperatures. The self-powered sensors are composed of self-healing polyurea (SH-PUrea) and Ag nanowires (AgNWs). Since physical entanglements that are less susceptible to environmental influences are introduced in SH-PUrea, the self-powered sensors exhibit exceptional self-healing performance without degradation of the output signals, regardless of the ambient conditions or extreme environments encountered. Specifically designed in a 3 × 3 pixel array structure, the self-powered sensors are ideal for E-skins that can adapt to sweaty and underwater environments. The detection of pressure position and underwater communication can be achieved by analyzing the electrical signals from the sensor array. This work introduces a novel strategy for enhancing the extreme environment-resistance and durability of flexible devices.

Uncertainty and velocity observer-based predefined-time nonsingular terminal sliding mode control of the underwater robot manipulators

This paper introduces an observer-based predefined-time nonsingular terminal sliding mode control to the position tracking control of the n-degree-of-freedoms underwater robot manipulators subject to the uncertainty compensation and sensor reduction. The proposed sliding surface has only the sliding phase, while the reaching phase is eliminated using a continuous augmented function. Besides, the sliding phase is predefined-time, where it is independent of the initial conditions and control parameters. As a result, it has led to the development of a predefined-time control scheme, in which not only its convergence time is fast, but also (due to the elimination of the reaching phase) the effect of uncertainties in this phase is eliminated. Naturally, there is a wide range of uncertainties such as structured-unstructured uncertainties and/or un-modeled dynamics, ocean current, waves, etc., in the underwater robot manipulators and underwater conditions. Therefore, the proposed predefined-time nonsingular terminal sliding mode control is combined with a finite-time observer to estimate the underwater robot manipulator's joint velocity and eliminate the destructive effect of existing uncertainties. Under this combination, the stability analysis could guarantee predefined-time global asymptotic stability of the system in the presence of existing uncertainties. Simulation results are conducted on a 2-link underwater robot manipulator to validate the proposal.

Biológiai vízminőségi paraméterek hatásainak vizsgálata a szarvasi Holt-Körösön

One of the essential natural resources is water resource in Hungary. It is threatened by many threats, both quantitative and qualitative. For these reasons, the protection of surface water and groundwater is a priority. The main objective of the present study is to determine which parameters have the greatest influence on the horizontal and vertical distribution patterns of phytoplankton in the water body. The study area is the Holt-Körös, which plays an important ecological, social, economic and recreational role in the region. Between the field and laboratory tests, the following physical, chemical and biological water quality parameters were investigated: water temperature, UV radiation index, Secchi depth, underwater light condition, dissolved oxygen content, suspended solids content, chlorophyll-a content, Fe, NO2-, NO3- NH4+, PO43-, Na+, K+, Mg2+, and pH value.

Community structure, environmental conditions and anthropogenic pressure on the habitat of the European endemic aquatic plant Luronium natans (L.) Raf.

Luronium natans (L.) Raf. is a European endemic species and is becoming increasingly rare and endangered in most countries. This study aimed to compare the community structure and environmental conditions of shallow and deep-water habitats of Luronium, and related anthropogenic influences. A total of 21 Luronium lake habitats were surveyed at Pomerania Lakeland (NW Poland). Luronium occurs mainly with other isoetids, as well as bryophytes, specifically Sphagnum denticulatum. It can also be found in oligotrophic lakes at a depth of 1.0 ± 0.6 m and in water with a large pH range (4.52 – 8.76), as well having a low conductivity (38.3 ± 20.9 µS cm−1; 19.0 – 106.1) and calcium concentration (3.9 ± 2.4 mg dm−3; 1.6 – 11,7).The largest Luronium cover occurs at a depth of 1.5 m (44.8 ± 35.3%), but occasionally as deep as 3.5 m. In the depth gradient, the structure of underwater vegetation and environmental conditions exhibit obvious changes, which presents a clear distinction between shallow and deep-water habitats of Luronium. The differences mainly pertain to the abundances of Isoëtes lacustris and Elodea canadensis in the community, as well as environmental factors, such as water calcium, nitrogen and phosphorus concentrations, PAR, conductivity, and water color.Compared to other isoetids, Luronium usually occurs in habitats with intermediate features, which are characterized by values between the typical, but deep-water, Isoëtes and shallow water Lobelia and Littorella. However, Luronium clearly prefers waters with higher temperatures (23.8 ± 2.7 °C), which are thus less oxygenated (96.6 ± 20.0%). In terms of pH, conductivity, and calcium concentration, Luronium occurs in waters having slightly lower values compared to other isoetids. Therefore, Luronium is a species that significantly expands the diversity of habitat number 3110 in the Natura 2000 network. Therefore, it can be considered as an indicator species of lobelia lakes.An increased anthropogenic pressure primarily results in an increased water conductivity and a decreased water transparency. Consequently, Luronium increasingly inhabits shallower waters that are more oxygenated. Moreover, Luronium abundance is decreasing, while the abundances of species comprising underwater communities are also decreasing, e.g., S. denticulatum and I. lacustris, with a concurrent increase in Myriophyllum alterniflorum and E. canadensis cover.

Mechanical and structural behavior of high-strength low-alloy steel pad welded by underwater wet welding conditions

The aim of the paper was to determine the metallurgical and mechanical behaviors of a high-strength low-alloy (HSLA) steel pad-welded specimen used in the structures of industrial and naval parts. Then to predict the metallurgical consequences (nature of the phases present) and the mechanical properties (hardness and impact strength) of the pad-welded steel obtained by underwater wet welding with different heat input values. The XRD patterns clearly reveal a ferritic alpha steel S460N for both parameters. The ferritic quantification is above 70 wt% for low-alloy steel. The welded specimens are characterized by the presence of different phases. In a specimen performed with higher heat input, the complex oxide Mn2TiO4 was found to be around 7 wt%. Moreover, the solid solution formed with iron and manganese was observed. The hardness results obtained by indentation showed that the higher heat input resulted in higher hardness values (54 HRC) than for specimen performed with lower parameters (45 HRC). The impact test showed that the toughness of both pad-welded layers is greater than the toughness of the base material (40 kV for S2 and 34 kV for S1 about 27 kV for low-alloy steel). Moreover, it was observed that higher heat input results in increasing the impact strength of pad welds.

Detection of Small Objects in Side-Scan Sonar Images Using an Enhanced YOLOv7-Based Approach

Deep learning-based object detection methods have demonstrated remarkable effectiveness across various domains. Recently, there has been growing interest in applying these techniques to underwater environments. Conventional optical imaging methods face severe limitations when operating in underwater conditions, restricting their ability to identify objects with good visibility and at close distances. Consequently, side-scan sonar (SSS) has emerged as a common equipment choice for underwater detection due to its compatibility with the characteristics of sound waves in water. This paper introduces a novel method, termed the Enhanced YOLOv7-Based Approach, for detecting small objects in SSS images. Building upon the widely-adopted YOLOv7 method, the proposed approach incorporates several enhancements aimed at improving detection accuracy. First, a dedicated detection layer tailored for small objects is added to the original network architecture. Additionally, two attention mechanisms are integrated within the backbone and neck components of the network, respectively, to strengthen the network’s focus on object features. Finally, the network features are recombined based on the BiFPN structure. Experimental results demonstrate that the proposed method outperforms mainstream object detection algorithms. In comparison to the original YOLOv7 network, it achieves a Precision of 95.5%, indicating a significant improvement of 4.8%. Moreover, its Recall reaches 87.0%, representing an enhancement of 5.1%, while the mean Average Precision (mAP) at an IoU threshold of 0.5 (mAP@.5) reaches 86.9%, reflecting a 6.7% improvement. Furthermore, the mAP@.5:.95 reaches 55.1%, a 4.8% enhancement. Therefore, the method presented in this paper enhances the performance of YOLOv7 for object detection in SSS images, providing a fresh perspective on small object detection based on SSS images and contributing to the advancement of underwater detection techniques.

Multi-AUV Control Method Based on Inverse Optimal Control of Integrated Obstacle Avoidance Algorithm

Under complex underwater conditions, multiple AUVs work in one area and they need to cooperate for complicated missions. In this study, a design method was applied for multiple autonomous underwater vehicles (AUVs) that are distributed in an area and suddenly receive a command. Using this method, the AUVs work according to their own state and reach the target while avoiding obstacles automatically in the process of collection. A new optimal control method is proposed that achieves the consensus of multiple AUVs as well as offering obstacle avoidance capability with minimal control effort. A non-quadratic obstacle avoidance cost function was constructed from the perspective of inverse optimal control. The distributed analytic optimal control law depends only on the local information that can be generated by the communication topology, which guarantees the proposed behavior, so that the control law does not require information from all AUVs. A simulation and an experiment were performed to verify the consensus and obstacle avoidance effect.

Satellite-derived bathymetry from WorldView-2 based on linear and machine learning regression in the optically complex shallow water of the coral reef ecosystem of Kemujan island

Shallow coastal water bathymetry information is required for various navigation, management, conservation, and research purposes. Bathymetry data modeled through satellite remote sensing (SDB) is considered more effective and efficient because it is cheaper, can cover a large area, and can be done routinely. In this study, we assess the linear (LR) and machine learning regression performance of bathymetry mapping in the optically shallow water of a coral reef ecosystem. We selected random forest regression (RFR) and support vector machine regression (SVR) machine learning regression models. All three regression models were trained using field bathymetry data, and different tuning parameter scenarios were applied to each model to obtain the best bathymetry map. Independent field bathymetry data were used for the assessment, which included root mean squared error (RMSE), a plot between reference and predicted depths, and an underwater topographic profile in three unique areas. Each unique area represented different water depths, underwater topography, benthic cover variations, and water clarity. This highlights and provides a comprehensive insight into how each model performs under different underwater topographic conditions. Kemujan Island, which has various coral reef geomorphic classes and underwater topographic variations, was selected as the study site. The RMSE of the SDB mapping accuracy obtained in this research ranged from 0.82 to 0.87 m for RFR, 0.96–1.17 m for SVR, and 1.00–1.23 m for LR. Overall, RFR produced SDB with higher accuracy and precision compared to SVR and LR. RFR managed to estimate the depth that follows the underwater transverse profile accurately and precisely in three sites and does not require a band ratio to produce accurate SDB in areas with various benthic covers. LR competes well with RFR in predicting water depths of up to 6 m but cannot accurately predict depths beyond 6 m. The study results provide a comprehensive reference for developing robust automated mapping models for producing SDB, increasing the availability of optically shallow water bathymetry information worldwide while reducing the cost of conducting bathymetric surveys.

High turbidity underwater single-pixel imaging based on Unet++ and attention mechanism at a low sampling

Underwater environments contain significant scattering media, characterized by complex distributions of refractive index and reflectance within. These properties cause light to deviate from its original propagation direction and decrease the signal-to-noise ratio during it passes through the scattering media. Consequently, traditional imaging techniques are difficult to achieve clear underwater imaging. Single-pixel imaging (SPI) offers higher sensitivity and the ability to be imaged in extremely low-light conditions compared to traditional imaging methods, and it provides significant advantages for underwater imaging. This paper proposes a SPI system based on Unet++ that can reconstruct high-quality images under the low sampling rate in highly turbid water environments. Numerical simulations and physical experiments demonstrate that our approach can still achieve clear image reconstruction at a sampling rate of 3.125 % under the turbidity level of 80 NTU compared with other methods. Additionally, the network exhibits strong generalization capabilities, and our approach holds the capability to reconstruct high-quality images under low sampling in high turbidity underwater conditions.

Scaling law of deep-sea trinitrotoluene (TNT) explosion

Understanding the dynamic characteristics of deep-sea explosions is essential to improve the survivability and combat capability of deep-sea equipment. In this paper, by considering the practical underwater conditions, we investigated the mechanical effects of the deep-sea 1-kg-trinitrotoluene (TNT) explosion with charge depths ranging from 1 to 10 km through numerical simulation and dimensional analysis. The shock wave overpressure, the positive overpressure pulse, the bubble pulse, and the energy distribution for various depth explosions were analyzed systematically. The simulation results showed that the charge depth was negligible for the peak overpressure of the shock wave. However, the positive overpressure pulse, the shock wave energy, the maximum bubble radius, the bubble energy, and the bubble period decrease significantly with increasing the charge depth. Then, the dimensional analysis for deep-sea TNT explosion was performed to reveal the key dimensionless parameters, from which the scaling laws of the shock wave overpressure and the overpressure pulse were obtained. By fitting the simulation results, the dimensionless equations were proposed, providing an effective method for predicting the peak overpressure and the positive overpressure pulse of shock wave for underwater TNT explosion over a wide range of water depths.

Underwater Image Quality Assessment from Synthetic to Real-world: Dataset and Objective Method

The complicated underwater environment and lighting conditions lead to severe influence on the quality of underwater imaging, which tends to impair underwater exploration and research. To effectively evaluate the quality of underwater images, an underwater image quality assessment dataset is constructed from synthetic to real-world, and then a new objective underwater image assessment method based on the characteristics of the underwater imaging is proposed (UICQA). Specifically, to address the lack of a publicly available datasets and more accurately quantify the quality of underwater images, a subjective underwater image quality assessment dataset from synthetic to real-world underwater images, named USRD, is constructed. Considering that the transmission map can effectively reflect the characteristics of the underwater imaging, statistical features are effectively extracted from the transmission map for distinguishing underwater images of different quality. Further, considering that the transmission map negatively correlates with scene depth, a local-to-global transmission map weighted contrast feature is constructed. Additionally, the color features of human perception and texture features based on fractal dimensions are proposed. Finally, the experimental results show that the proposed UICQA method exhibits the highest correlation with ground truth scores compared to state-of-the-art UIQA methods.

Factors Governing the Failure of Subsea Critical Connector Bolts

Impressed current cathodic protection (ICCP) systems are commonly used to shield offshore drilling rigs, pipelines, and subsea equipment in the oil and gas industry. In underwater service conditions, water temperature, salinity and velocity play a major role in the longevity of subsea applications. Interactions between the preceding factors can induce catastrophic failure to critical systems while the underlying cause is unclear. This paper proposes an approach for elucidating the corrosion process accompanying underwater applications. The service conditions of underwater application are simulated in a multidisciplinary system that records various parameters such as water temperature, reference-electrode potential, and electric current at five-minute intervals during the 21 d of the experiment. This novel, experimental, and inexpensive ICCP system was developed on an “Arduino” microcontroller and applied to an actual ASTM A193 B7 bolt tightened on an ASTM A105 flange at different torque levels. Experimental results indicate a direct relationship between the water day-night temperature profile and the cathodic protection performance. Specifically, the ICCP performance declines with increasing temperature. When the ICCP system was activated, gas bubbles are generated on the metal surface. Presumably these bubbles could induce hydrogen embrittlement cracks which were observed in scanning electron microscope images of the bolt cross-sections.

A Novel Strategy for the Synthesis of High Stability of Luminescent Zero Dimensional-Two Dimensional CsPbBr3 Quantum Dot/1,4-bis(4-methylstyryl)benzene Nanoplate Heterostructures at an Atmospheric Condition.

Perovskite quantum dots (QDs), emerging with excellent bright-green photoluminescence (PL) and a large absorption coefficient, are of great potential for the fabrication of light sources in underwater optical wireless communication systems. However, the instability caused by low formation energy and abundant surface traps is still a major concern for perovskite-based light sources in underwater conditions. Herein, we propose ultra-stable zero dimensional-two dimensional (0D-2D) CsPbBr3 QD/1,4-bis(4-methylstyryl)benzene (p-MSB) nanoplate (NP) heterostructures synthesized via a facile approach at room temperature in air. CsPbBr3 QDs can naturally nucleate on the p-MSB NP toluene solution, and the radiative combination is drastically intensified owing to the electron transfer within the typical type-II heterostructures, leading to a sharply increased PLQY of the heterostructure thin films up to 200% compared with the pristine sample. The passivation of defects within CsPbBr3 QDs can be effectively realized with the existence of p-MSB NPs, and thus the obviously improved PL is steadily witnessed in an ambient atmosphere and thermal environment. Meanwhile, the enhanced humidity stability and a peak EQE of 9.67% suggests a synergetic strategy for concurrently addressing the knotty problems on unsatisfied luminous efficiency and stability of perovskites for high-performance green-emitting optoelectronic devices in underwater applications.

MO-CBACORP: A new energy-efficient secure routing protocol for underwater monitoring wireless sensor network

With the rapid progress of sensor technology, underwater monitoring wireless sensor network (UMWSN) equipped with water resource monitoring capabilities have surfaced. UMWSN is currently emerging as a popular research and application area, with a wide range of applications in various fields, including but not limited to disaster warning, pollutant monitoring and hydrological data monitoring. However, due to the limited size and computing power of wireless sensors, UMWSN are exceedingly susceptible to network security attacks by contaminating entities. In order to tackle the problems of inadequate security, elevated network energy consumption, and high system latency in existing QoS routing research, this paper puts forward an innovative multi-objective routing protocol named multi-objective chaotic Boltzmann ant colony optimization routing protocol (MO-CBACORP). MO-CBACORP can minimize the energy consumption of sensor nodes in UMWSN routing, thereby effectively diminishing system latency and significantly enhancing routing security. During the routing optimization process, MO-CBACORP proposed an innovative design of the chaos operator and Boltzmann selection strategy, which effectively avoids the issue of being stuck in local optimal solutions and greatly enhances the convergence speed of the algorithm. Additionally, a novel experiment for underwater monitoring environments is presented that precisely replicates underwater monitoring conditions and attack scenarios. According to the experimental results, MO-CBACORP exhibits superior performance compared to the latest state-of-the-art research including THOA-MHR, ACO-MCMC, and MAP-ACO, with a minimum improvement of 7.25%, 9.31%, and 7.68% in terms of route security, network energy consumption, and delay, respectively. All in all, MO-CBACORP exhibits superior performance compared to the three latest research algorithms.

Lessons learned from time reversal communications

Time reversal (TR) is a technique that utilizes spatial diversity to achieve spatial and temporal focusing in complex environments. This approach has been successfully applied to phase-coherent acoustic communications in time-varying multipath environments, providing an alternative to conventional adaptive multichannel equalizers (M-DFE). Essentially, the TR method involves combining multichannels as a spatial precombiner, effectively reducing channel complexities and achieving optimal performance. This presentation will discuss the insights gained from using the TR approach for underwater communications under diverse underwater conditions.

A Chattering-Suppression Sliding Mode Controller for an Underwater Manipulator Using Time Delay Estimation

Underwater manipulators are pivotal in diverse applications, encompassing underwater pipeline repairs, salvage operations, and scientific sampling missions. However, attaining high-precision control mandates the establishment of precise mathematical models. Specifically, developing an accurate dynamic model for the underwater manipulator affixed to underwater robots proves exceptionally demanding, primarily attributed to the uncertainties arising from water currents and the perturbations induced by the vehicle’s motion. This paper presents a novel sliding mode controller with time delay estimation for the high-precision control of an underwater manipulator mounted on an underwater vehicle. The presented controller circumvents the requirement for an exact mathematical model of the underwater manipulator, enhancing its control precision even without detailed modeling information. Moreover, the proposed controller guarantees robustness against uncertain water flow disturbances, effectively preserving the performance of the underwater manipulator under challenging underwater conditions. The proposed controller comprises two key elements. Firstly, a time delay estimator is employed to estimate the system states using feedback from intentional time-delayed control inputs and a pre-designed matrix. Additionally, a specially designed reaching law is incorporated to reduce reaching time and prevent chattering in the sliding mode control. The controller offers several advantages, including easy implementation, insensitivity to model uncertainties, and robustness in the underwater environment. Simulations and experiments demonstrate the ability of the proposed controller to effectively mitigate disturbances, eliminate chattering, and ensure precise trajectory-tracking performance. The experiments are conducted on a fully self-developed 2-degree-of-freedom (2-DOF) underwater manipulator, showcasing the superiority of the proposed controller over other alternatives.