Ocean Exploration Research Articles (Page 1)

Abstract The growing demand for renewable energy has driven advancements in ocean exploration technologies involving floating structures. These structures are exposed to waves, requiring careful design to ensure safety. To enhance protection, the present research focuses on floating breakwaters designed to mitigate wave action. When considering regular waves, the wave transmission coefficient (K t ) for two-dimensional (2D) box-type floating breakwaters is well-defined in the literature. However, the wave transmission coefficient computation for three-dimensional (3D) floating breakwaters still requires a standardized method. In this context, this study conducts a parametric analysis of a box-type floating breakwater, using numerical models based on potential flow theory to determine the 3D wave transmission coefficient. Results reveal that, unlike 2D cases, different K t levels emerge for a given 3D scenario. These findings suggest that breakwaters featuring high relative breakwater beam ratios are likely to present convergent mean wave transmission coefficients. Furthermore, the research demonstrates that the wave-shelter area is highly dependent on the breakwater beam ratio, with larger ratios leading to lower K t levels. The sheltered area changes exponentially with the K t levels. In addition, a practical application is introduced, leveraging machine learning techniques to predict the wave-shelter area and optimize breakwater dimensions. The proposed design minimizes construction costs while ensuring effective wave attenuation for a one megawatt-peak floating solar photovoltaic system. These findings enhance understanding of the wave transmission coefficient for 3D floating breakwaters, highlighting that variations in breakwater dimensions and wave conditions significantly influence the sheltered area, which impacts the protection of offshore structures.

Manipulating the interfacial and surface carrier dynamics within nanostructured semiconductors is pivotal for advancing the electrical and optical performances of photoelectrochemical (PEC) photodetectors (PDs), particularly for durable underwater optical communication systems. Herein, a highly responsive and robust self-powered PEC UV PDs based on SiC/Au heterojunction nanoarrays is explored, by leveraging the synergistic effect from localized surface plasmon resonance (LSPR) of Au nanoparticles (NPs), heterojunction interfacial engineering, integrated self-supporting photoelectrode architecture, 1D nanoarray benefits, and inherent chemical stability of SiC. SiC nanowire (NW) arrays are fabricated via anodic oxidation and subsequently decorated with tailored densities of Au NPs using controlled sputtering. The as-assembled SiC-based PEC PDs demonstrate exceptional UV (375nm) photodetection behaviors with rapid response (τr/τd, 86.5/170.95ms), high responsivity (Rλ, 1244.95mAW-1), excellent detectivity (D*, 6.35 × 1011 Jones), and remarkable external quantum efficiency (EQE, 412.45%). Moreover, they exhibit broad pH tolerance and excellent long-term stability against full aquatic environments. This work provides a strategic approach for designing high-performance self-powered PEC PDs for reliable underwater optical communication, such as liquid environmental monitoring, ocean exploration, and biomedical detection.

As ocean exploration deepens, new demands on propulsion methods are proposed due to the complex underwater environments. Marine animals exhibit excellent locomotion properties, which provide a promising direction for the development of high-performance underwater robots. The unique hydrofoil-paddle propulsion mode of the sea lions foreflippers is a key contributor to their efficient locomotion. Inspired by this, the present work simulates the hydrofoil motion of California sea lion foreflippers with a transient computational fluid dynamic model using dynamic mesh technology to investigate its hydrodynamic characteristics and performance. The result shows that thrust generation during the recovery and power phases is dominated by lift-based propulsion, while during the paddle phase it is dominated by drag-based propulsion. Maximum thrust in a stroke cycle occurs in the power phase, while maximum efficiency at the same motion speed of the hydrofoil is achieved in the paddle phase. The effects of the motion parameters, including Strouhal number (St) and the dimensionless flapping amplitude (h), on the hydrodynamic performance are also investigated. Analysis results show that the optimal thrust and efficiency are achieved in the St range of [0.220, 0.293] and h range of [1.0, 1.864], with the highest efficiency of 25.27% occurring at St = 0.293 and h = 1.846. The present work provides valuable theoretical guidance for designing the bionic robotic foreflippers.

Wireless Sensor Networks (WSNs) are dynamic environments of sensor nodes that run on batteries, made possible by artificial intelligence (AI). WSN applications have increased due to recent developments in processing power and network connectivity. Applications for ocean exploration, including pollution detection, ocean resource management, underwater device maintenance, and ocean monitoring, have made underwater acoustic sensor networks (UASNs) increasingly significant. Researchers find routing protocol design to be an appealing issue in underwater acoustic sensor networks because it ensures dependable and efficient data transfer from the source node to the target node. In the last few years, numerous routing algorithms have been put out. We run comprehensive simulations in miscellaneous underwater environments to evaluate the effectiveness of these AI-based routing protocols. The findings show that AI-aided protocols outperform traditional approaches, especially when there are resource constraints and complex environmental dynamics. More dependable and effective underwater operations are made possible by this study's insightful analysis of the incorporation of AI technology into underwater communication networks. Our results lay the groundwork for future developments in underwater communication systems and add to the expanding corpus of knowledge in this area.

ABSTRACTAs a key technology in ocean exploration, underwater wireless sensor networks (UWSNs) are persistently constrained by challenges stemming from limited node energy, namely short network lifespan and low transmission efficiency. Existing routing protocols often fall into local optima due to their inability to effectively balance global exploration and local exploitation. To address these issues, this study proposes a hybrid optimization routing protocol, HFFO‐ACRP (hybrid fruit fly optimization‐ant colony routing protocol). Its core innovation lies in a synergistic division of labor: the fruit fly optimization algorithm (FOA) performs a global search to generate initial routes by integrating path length, node density, and residual energy. Subsequently, the ant colony optimization (ACO) algorithm conducts local optimization to refine these paths, considering data priority and node energy efficiency. Finally, a unique bidirectional feedback mechanism enables the two algorithms to mutually enhance their search breadth and precision, collectively improving the accuracy and efficiency of route selection. Experimental results demonstrate that, compared to representative protocols, the proposed protocol extends the network lifespan by 9.69%, 16.21%, and 18.68%, respectively, and significantly increases the residual network energy in the later stages of operation. This hybrid strategy provides an efficient and robust routing solution for resolving the critical energy consumption and longevity bottlenecks in UWSNs.

Abstract Europa, one of the celestial bodies most likely to harbor life in the solar system, is a vital target for China’s deep space exploration mission in the future. Compared to orbital missions, exploring Europa’s sub-surface ocean is of greater scientific significance and engineering challenges. This paper introduces the science and engineering objectives, mission profile, and scheme of the submarine prober, especially the design of the Gravity Center Regulation System, Manipulator System, and Power System. Additionally, this paper provides a fresh idea and reference for China’s future plans of Europa’s ocean exploration mission

Water is the liquid of life. It cycles endlessly from air, land, and sea, and makes life on planet Earth possible. The average adult human is made up of roughly 60% water and consumes around 50,000 liters of water in a lifetime. However, this miracle solution can pose its fair share of problems—dangerous currents at sea, flooding on land when too much falls from the sky too fast, and crushing pressures at depths that can hinder ocean exploration. Still, water is a commodity, and no one may know that better than the oil and gas business, where millions of gallons of water are used every day to stimulate complex shale wells into giving up their hydrocarbon resource. In some regions, oil and gas wells do not return nearly the water that is pumped into them. But in areas like the crucial Permian Basin in west Texas, a given well can return up to 12 barrels of produced water for every single barrel of oil. While the oil eventually heads to the sales pipeline, the produced water—a briny mix of injected water, oilfield fluids, and chemicals—has no well-defined, single destination. Some will go into saltwater disposal wells, but regulators have been clamping down on disposal well use and have been resistant to permit for new ones given the levels of seismic activity some believe is related to reinjection. Other volumes will go to recycling centers to be filtered and prepared for reuse in future fracturing jobs. And it just keeps coming. In 2024, the Permian Basin produced more than 20 million B/D of water, a figure projected to exceed 26 million by 2030, according to researchers at B3 Insights. A potential answer to the produced water glut could be on the horizon in the form of data centers. A number of these large scale, AI-driven server farms are currently under construction or coming online in west Texas. The facilities consist of multi-building complexes filled with IT infrastructure for use with cloud storage, data distribution, and artificial intelligence (AI). The AI boom has fueled several new, massive data center projects across the globe. Produced water typically contains total dissolved solids (TDS) concentrations of 30,000 to 300,000 mg/L, making it unfit for reuse as is. However, treatment technologies, including ceramic membrane filtration, electrocoagulation, and ion exchange, can bring the water to spec for industrial cooling applications. For the US, the Permian makes a lot of sense: The water resource is available there for cooling, and the natural gas resource is available for off-grid power. The land is available that these sprawling campuses require. Low population density means fewer neighbors are adversely affected during the construction phase and beyond. If you’ve ever done any home computing that is memory-intensive—something as simple as upscaling an old photo—you likely heard your computer’s fan kick on. The fan is designed to keep things cool as your system accesses more computing power to accomplish the task. AI needs exponentially more computing power to achieve its end product, thus the size of the current crop of data centers.

Abstract With the advancement of technology, the exploration of underwater environment has received widespread attention in recent years. However, achieving excellent overall performance underwater remains a challenge due to the vast differences between aquatic and terrestrial environments. The ionogel composed of ionic liquid and polymer with hydrophobic group has good hydrophobicity and can avoid the influence of water as much as possible. Here, for the first time an ionic ocean structure is reported that consists of polymer chains with the same ion groups as the ionic liquid. The ion groups in ionic ocean can rapidly repair and replenish the polymer chains during the stretching and healing process without the need for polymer chain movement or covalent bond reorganization, thus enabling ionogel to obtain super stretching and excellent self‐healing capabilities. Moreover, the ionogel shows excellent underwater adhesion properties. These excellent mechanical properties and reliable underwater performance demonstrate enormous potential in ocean exploration and protection.

MCLORA: Maritime ad-hoc communication system based on LORA

Underwater biomimetic robotic fish are emerging as vital platforms for ocean exploration tasks such as environmental monitoring, biological observation, and seabed investigation, particularly in areas inaccessible to humans. Central to their effectiveness is high-precision fish pose estimation, which enables detailed analysis of swimming patterns and ecological behavior, while informing the design of agile, efficient bio-inspired robots. To address the widespread scarcity of high-quality motion datasets in this domain, this study presents a custom-built dual-camera experimental platform that captures multi-view sequences of carp exhibiting three representative swimming behaviors—straight swimming, backward swimming, and turning—resulting in a richly annotated dataset. To overcome key limitations in existing pose estimation methods, including heavy reliance on labeled data and inadequate modeling of temporal dependencies, a novel Semi-supervised Temporal Context-Aware Network (STC-Net) is proposed. STC-Net incorporates two innovative unsupervised loss functions—temporal continuity loss and pose plausibility loss—to leverage both annotated and unannotated video frames, and integrates a Bi-directional Convolutional Recurrent Neural Network to model spatio-temporal correlations across adjacent frames. These enhancements are architecturally compatible and computationally efficient, preserving end-to-end trainability. Experimental results on the proposed dataset demonstrate that STC-Net achieves a keypoint detection RMSE of 9.71, providing a robust and scalable solution for biological pose estimation under complex motion scenarios.

Synthetic Aperture Radar (SAR), renowned for its all-weather monitoring capability and high-resolution imaging characteristics, plays a pivotal role in ocean resource exploration, environmental surveillance, and maritime security. It has become a fundamental technological support in marine science research and maritime management. However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. To address these challenges, this paper proposes AC-YOLO, a novel lightweight SAR ship detection model based on YOLO11. Specifically, we design a lightweight cross-scale feature fusion module that adaptively fuses multi-scale feature information, enhancing small target detection while reducing model complexity. Additionally, we construct a hybrid attention enhancement module, integrating convolutional operations with a self-attention mechanism to improve feature discrimination without compromising computational efficiency. Furthermore, we propose an optimized bounding box regression loss function, the Minimum Point Distance Intersection over the Union (MPDIoU), which establishes multi-dimensional geometric metrics to accurately characterize discrepancies in overlap area, center distance, and scale variation between predicted and ground truth boxes. Experimental results demonstrate that, compared with the baseline YOLO11 model, AC-YOLO reduces parameter count by 30.0% and computational load by 15.6% on the SSDD dataset, with an average precision (AP) improvement of 1.2%; on the HRSID dataset, the AP increases by 1.5%. This model effectively reconciles the trade-off between complexity and detection accuracy, providing a feasible solution for deployment on edge computing platforms. The source code for the AC-YOLO model is available at: https://github.com/He-ship-sar/ACYOLO.

This study aims to improve student learning outcomes on the basic competency of geographical conditions and ocean exploration through the guided inquiry learning model in Grade VIII of SMP Negeri 1 Peusangan. Using a two-cycle Classroom Action Research (CAR) method, each cycle involved planning, implementation, observation, and reflection. Data were collected through learning outcome tests, observations of teacher and student activities, and documentation. Results showed an increase in learning mastery from 70% in Cycle I to 90% in Cycle II. Teacher activity rose from 81.11% to 91.11%, while student activity increased from 75.56% to 86.67%. The guided inquiry model effectively enhanced learning outcomes, encouraged critical thinking, and increased student engagement and interest in the learning process.

ABSTRACT ‘Kelp Forest – Enhancing Biodiversity and Mitigating Climate Change’ explores the use of contemporary art to promote climate awareness and action. The project aims to make ocean exploration accessible to urban communities, particularly those without direct access to diving experiences. It encompasses an immersive art installation, ‘Kelp and Critters’ creative workshop, and a panel discussion ‘What Kelp Does for Us’. The installation, constructed entirely from found and recycled materials, including debris collected from inland and coastal water systems and donations from The Port of London Authority, creates a striking sensory experience. Some versions incorporate living plants, visually demonstrating the parallels between kelp forests and terrestrial forests in oxygen production and carbon sequestration. The work invites audiences to engage with an underwater environment by walking among enormous sculptures of plastic algae. This project underscores the ecological significance of kelp forests as critical marine habitats that store carbon, provide food and shelter, produce oxygen, and protect coastlines. By linking art, science, and community engagement, it fosters public understanding of how kelp forests mitigate climate change and support biodiversity.

BACKGROUND: As technology advances and the need for ocean exploration increases, unmanned underwater vehicles with manipulators are becoming critical tools for complex underwater missions. Efficient manipulator control systems ensure high operational precision, reliability, and safety in hard-to-reach locations, making their development a relevant science and technology objective. AIM: This study aims to compare different manipulator motion control systems used in unmanned underwater vehicles. METHODS: The study uses modelling techniques for kinematic diagrams of manipulators based on 3D technologies and graphic designs. The study reviews open and closed loop control algorithms with pick position feedback. A PI controller is used to stabilize the position. RESULTS: The model showed that the manipulator moves harmonically with open loop control, but the system becomes unstable with permanent load. The introduction of pickup position feedback results in self-oscillations. However, they can be avoided by using a PI controller. The resulting transient curve shows improved stability and controllability of the manipulator. CONCLUSION: The closed-loop and controller approach to manipulator control enables consistent and accurate underwater operations.

The following research paper presents a comprehensive evaluation of augmented reality (AR) games and educational tools, hence AR games, implemented in the Greek primary education system, focusing on the design and creation of a graded criteria scale (Rubric) for selecting and evaluating AR educational games–applications utilized by the students. The study aims to determine, through evaluation approaches, the basic criteria for developing an effective Rubric, by the students, on specific issues such as the main functionality and effectiveness of the games in regard to cognitive areas and skills development, steered through these AR applications. A mixed-method approach was adopted, employing qualitative and quantitative analyses, assessing AR tool utilization in classroom settings, and evaluating the applications’ educational impact. The study entails collecting data from AR tool usage in Greek primary schools and the design and construct, by the students, of a Rubric based on educational and functional effectiveness. This Rubric provides a framework for assessing various aspects of AR educational games, such as Educational Value, Content Quality, Design, Usability, and Technical Features. Key findings include AR games’ effectiveness in enhancing student engagement, understanding, and retention of information through interactive experiences. A notable facet is the integration of student input in Rubric creation, which contextualizes the evaluation process within the cognitive and developmental scope of primary education learners. Four case studies detail practical implementation and evaluation of selected AR applications: <i>Mondly</i> for English language learning, <i>Clever Book AR Geometry</i>, <i>Google Expeditions AR </i>for ocean exploration, and<i> Banun Ruang AR Geometry</i> for 3D geometry comprehension. The cases highlight the educational benefits of the specified AR games, such as visualization, active and kinesthetic learning, fostering motivation and collaboration. Constraints discussed include limitations in sample size, geographic reach, device type, and infrastructure barriers. Despite these boundaries, the study proposes a structured model for evaluating and effectively integrating AR games into educational practices, signaling a shift towards STEM-enhanced learning environments.

Marine flexible structures are essential components of marine equipment, playing a pivotal role in ocean exploration and research. The lumped mass method is a critical tool for studying these structures, particularly in hydrodynamics, where both accuracy and efficiency are of utmost importance. Through extensive research in this field, the author has found that the number of segments used in the lumped mass method significantly impacts its precision and computational efficiency when applied to marine flexible structures. This paper presents a thorough review from two key perspectives: the fundamental principles of the lumped mass method and relevant research applications. Based on this review, it offers a comprehensive summary of optimal segment selection strategies for various marine flexible configurations. Furthermore, the paper explores potential interdisciplinary directions and future developments, particularly highlighting the integration of artificial intelligence technology. To some extent, these insights serve as a valuable reference for advancing research and applications in this field.

Abstract The shipboard atomic interferometric gravimeter is a high-precision gravity measurement instrument applied broadly in geophysics, ocean exploration, inertial navigation, and other precision measurement physics fields. However, environmental vibration noise has been one of the most serious factors limiting its performance. Based on the above, this paper developed an empirical wavelet transform technique. It optimizes the minimum value of the trend boundary and utilizes it to extract features from vibration signals of shipboard atomic gravimeters. The boundary of the segmented spectrum is determined by calculating the minimum value of the trend component, and the key spectral negentropy is employed to filter each initial frequency band to extract the frequency band containing vibration information. The left and right demarcations of the extracted frequency bands are adopted as the ultimate boundaries for reconstruction, after which the components containing vibration information can be obtained. This method improves how the empirical wavelet transforms complexly segments the boundary and reduces the problem of too many invalid components. Validation of the vibration interference signals from simulated signals and shipboard atomic gravimeters in dynamic environments showed that our method could accurately decompose the signal components and improve the decomposition efficiency. It provides a theoretical basis for the design of the active vibration isolation system of shipboard atomic gravimeters.

Underwater vehicles serve as critical assets for global ocean exploration and naval capability enhancement. The marine environment exhibits intricate hydrodynamic phenomena that significantly threaten underwater vehicle navigation safety, particularly in four prevalent complex conditions: surface waves, oceanic currents, stratified fluids, and internal waves. This comprehensive review systematically examines the impacts of these four marine environments on underwater vehicles through critical analysis and synthesis of contemporary advances in theoretical frameworks, experimental methodologies, and numerical simulation approaches. The identified influences are categorized into five primary aspects: hydrodynamic characteristics, dynamic response patterns, load distribution mechanisms, navigation trajectory optimization, and stealth performance. Particular emphasis is placed on internal wave interactions, with rigorous analysis derived from experimental investigations and numerical modeling of internal wave dynamics and their coupling effects with underwater vehicles. In addition, this review points out and analyzes the shortcomings of the current research in various aspects and puts forward some thoughts and suggestions for future research directions that are worth further exploration, including enriching the research objects, upgrading the experimental techniques, and introducing artificial intelligence methods.

NOAA Ocean Exploration. "Deep-Sea Biological Discoveries: Celebrating 20 Years of NOAA Ocean Exploration." NOAA Ocean Exploration, https://oceanexplorer.noaa.gov/20years/biology.html. Accessed 1 June 2025. Singh , Ravindra Pratap. “Technology and Culture: Ruminations on Marshall Mc Luhan’s ‘The Mechanical Bride’”. IJLHE: International Journal of Language, Humanities, and Education, vol. 7, no. 1, June 2024. Singh , Ravindra Pratap. “Reading Taboos as Allegory in O.P. Vijayan’s The Saga of Dharmapuri”. Journal of Applied Cultural Studies, Institute of Cultural Studies Adam Mickiewicz University Poznań. Poland. Vol.1/2015. Tripathi, Sukriti. “The Underwater Giants and Other Stories”. Shabdankur Prakashan, New Delhi, 2024.

The importance of underwater robots is evident in ocean exploration, resource development, and environmental monitoring. However, the harsh underwater environment requires higher efficiency, stability, and intelligence from their propulsion systems. The challenges faced by operational underwater robots today include low propulsion efficiency, poor adaptability to extreme environments, and a lack of sufficient autonomous control capabilities. To address these issues, this paper reviews the definition, requirements, core technologies, and key performance indicators of underwater robot propulsion systems by analyzing relevant literature from 2016 to 2024. It emphasizes optimization strategies aimed at enhancing propulsion efficiency, fault diagnosis and identification, reliability, durability, and adaptive control. Besides, it summarizes the current technical challenges and provides a reference for subsequent research. The results show that optimizing the propulsion system of operational underwater robots relies primarily on bionic design, new materials, adaptive control, deep learning, and fault diagnosis technologies to enhance propulsion efficiency, stability, durability, and environmental adaptability. However, optimizing the propulsion system involves challenges such as energy control, cost, and multi-objective optimization. Future research should prioritize efficient, low-energy propulsion, multi-modal perception, and intelligent adaptive control to advance underwater robot technology.