Sea Exploration Research Articles

Compression of Multibeam Echosounders Bathymetry and Water Column Data

Over the past decade, Multibeam Echosounders (MBES) have become one of the most used techniques in sea exploration. Modern MBES are capable of acquiring both bathymetric information on the seafloor and the reflectivity of the seafloor and water column. Water column imaging MBES surveys acquire significant amounts of data with rates that can exceed several GB/h depending on the ping rate. These large file sizes obtained from recording the full water column backscatter make remote transmission difficult if not prohibitive with current technology and bandwidth limitations. In this paper, we propose an algorithm to decorrelate water column and bathymetry data, focusing on the KMALL format released by Kongsberg Maritime in 2019. The pre-processing stage is integrated into FAPEC, a data compressor originally designed for space missions. Here, we test the algorithm with three different datasets: two of them provided by Kongsberg Maritime and one dataset from the Gulf of Mexico provided by Fugro USA Marine. We show that FAPEC achieves good compression ratios at high speeds using the pre-processing stage proposed in this paper. We also show the advantages of FAPEC over other lossless compressors as well as the quality of the reconstructed water column image after lossy compression at different levels. Lastly, we test the performance of the pre-processing stage, without the constraint of an entropy encoder, by means of the histograms of the original samples and the prediction errors.

Probabilistic Framework Allocation on Underwater Vehicular Systems Using Hydrophone Sensor Networks

This article emphasis the importance of constructing an underwater vehicle monitoring system to solve various issues that are related to deep sea explorations. For solving the issues, conventional methods are not implemented, whereas a new underwater vehicle is introduced which acts as a sensing device and monitors the ambient noise in the system. However, the fundamentals of creating underwater vehicles have been considered from conventional systems and the new formulations are generated. This innovative sensing device will function based on the energy produced by the solar cells which will operate for a short period of time under the water where low parametric units are installed. In addition, the energy consumed for operating a particular unit is much lesser and this results in achieving high reliability using a probabilistic path finding algorithm. Further, two different application segments have been solved using the proposed formulations including the depth of monitoring the ocean. To validate the efficiency of the proposed method, comparisons have been made with existing methods in terms of navigation output units, rate of decomposition for solar cells, reliability rate, and directivity where the proposed method proves to be more efficient for an average percentile of 64%.

The Features of Distribution of Chemical Elements, including Heavy Metals and Cs-137, in Surface Sediments of the Barents, Kara, Laptev and East Siberian Seas

Over the recent few decades, due to climate warming and the continuing exploration of Arctic seas’ mineral resources, the scientific interest in contamination problems has deepened significantly. In this study, for the first time, we characterize the distribution features of 47 elements (major and trace elements, including heavy metals, metalloid As, and Cs-137 technogenic radionuclide) in surface bottom sediments from some areas of the Barents, Kara, Laptev, and East-Siberian Seas. The lithogenic material was the main factor that controlled variability in many elements (Be, Al, Ti, Cr, Ga, Rb, Sr, Y, Zr, Nb, Ba, REE, Pb, Th, U, W, and Cs). Among the hydrogenic processes, the formation of Fe and Mn oxyhydroxides has the greatest impact on the Mn, Fe, Co, Ni, Cu, Ge, and Mo, and insignificantly V and Sb, variability in sediments. These, along with minor to moderate values of enrichment factor (EF) for most elements, allowed us to conclude that the observed element distribution is related to predominantly natural processes of thermal abrasion, river-run, and atmospheric input. The exception is As, which exhibited the elevated EF (up to 20) in the western and central Kara Sea, as well as in the Vilkitsky Strait. Since no significant relationship between As and Fe andMn oxyhydroxides distribution was found, we may assume primarily an anthropogenic source of As, related to the peat and/or coal combustion. According to the criteria of Ecological Risks assessment, all the examined areas have a low degree of risk. Data on the specific activity of Cs-137 correspond to the background average values characteristic for these regions. The highest levels of Cs-137 concentration (Bq/kg) were detected in the sediments of the Ob and Yenisei Rivers’ estuaries.

Robot Grip Robustness Prediction using a Hybrid Deep Learning Approach

Humans have been using robots now for over a decade. With the latest developments in Electrical and Computer Engineering robots now can perform very critical tasks with high degrees of precision which was not possible in earlier times. Today robots perform various tasks such as industrial welding, space exploration, deep sea exploration, human surgery, bio-mechatronics etc. Now robot manufacturers have a wide variety of options to choose from while designing and developing their robots, from the mechanical parts to the software capabilities of the robot. One of the most common application of robots is to perform pick-and-place operations. The aim of this study is to predict the robustness in gripper robots using Deep Learning models so that the robot can be designed according to their robustness in safety critical environments. This is an important area as the robustness of the grip is a critical feature that must be ensured if the robot is to work with pick and place operations. The type of gripper to be used and its effectiveness determines the true value and efficiency of the robot. We have performed the analysis on shadow dataset obtained through Shadow Robot. The robot used in this study has a 3-finger gripper which is used to pick and place a ball. The proposed approach using an Artificial Neural Network (ANN) to extract features and Linear regression to predict the robustness factor of the grip. The model provides us an R-Squared score of 0.86 and an RMSE value of 18.12 which is sufficiently good and can help determine efficiently the robustness of the grip of the robot.

Self-management of the umbilical of a ROV for underwater exploration

This article focuses on passive self-management of the umbilical of a Remotely Operated Vehicle (ROV) for underwater exploration. The goal is to give a predictable shape to the umbilical, using moving ballasts and buoys to stretch the umbilical and so to avoid entanglement of the cable itself or with surrounding obstacles. The ballasts and buoys move by themselves to maintain the cable taut without a motorized system. A model of the umbilical is proposed. The presence of waves, as well as thecases with and without currents are considered. Three configurations of the umbilical are proposed, each one to be the most adapted to ROV exploration missions: near the surface, sea exploration, and diving in presence of large obstacles.

An Evaluation of the Performance of Sea Ice Thickness Forecasts to Support Arctic Marine Transport

In response to declining sea ice cover, human activity in the Arctic is increasing, with access to the Arctic Ocean becoming more important for socio-economic reasons. Accurate knowledge of sea ice conditions is therefore becoming increasingly important for reducing the risk and operational cost of human activities in the Arctic. Satellite-based sea ice charting is routinely used for tactical ice management, but the marine sector does not yet make optimal use of sea ice thickness (SIT) or sea ice concentration (SIC) forecasts on weekly timescales. This is because forecasts have not achieved sufficient accuracy, verification and resolution to be used in situations where maritime safety is paramount, and assessing the suitability of forecasts can be difficult because they are often not available in the appropriate format. In this paper, existing SIT forecasts currently available on the Copernicus Marine Service (CMS) or elsewhere in the public domain are evaluated for the first time. These include the seven-day forecasts from the UK Met Office, MET Norway, the Nansen Environmental and Remote Sensing Center (NERSC) and the European Centre for Medium-Range Weather Forecasts (ECMWF). Their forecast skills were assessed against unique in situ data from five moorings deployed between 2016 and 2019 by the Barents Sea Metocean and Ice Network (BASMIN) and Barents Sea Exploration Collaboration (BaSEC) Joint Industry Projects. Assessing these models highlights the importance of data assimilation in short-term forecasting of SIT and suggests that improved assimilation of sea ice data could increase the utility of forecasts for navigational purposes. This study also demonstrates that forecasts can achieve similar or improved correlation with observations when compared to a persistence model at a lead time of seven days, providing evidence that, when used in conjunction with sea ice charts, SIT forecasts could provide valuable information on future sea ice conditions.

AutoFac: The Perpetual Robot Machine

Robotics currently lacks fully autonomous capabilities, especially where task knowledge is incomplete and optimal robotic solutions cannot be pre-engineered. The intersection of evolutionary robotics, artificial life and embodied artificial intelligence presents a promising paradigm for generating multitask problem-solvers suitable for adapting over extended periods in unexplored, remote and hazardous environments. To address the automation of evolving robotic systems, we propose fully autonomous, embodied artificial-life factories and laboratories, situated in various environments as multi-task problem-solvers. Such integrated factories and laboratories would be adaptive solution designers, producing fit-for-purpose physical robots with accelerated artificial evolution that experiment to continually discover new tasks. Such tasks would be stepping-stones towards accomplishing given mission objectives over extended periods (days to decades). Rather than being purely speculative, prerequisite technologies to realize such factories have been experimentally demonstrated. Currently, vast scientific and enterprise opportunities await in applications such as asteroid mining, terraforming, space and deep sea exploration, though no suitable solution exists. The proposed embodied artificial-life factories and laboratories, termed: AutoFac, use robot production equipment run by artificial evolution controllers to collect and synthesize environmental information (from robotic sensory systems). Such information is merged with current needs and mission objectives to create new robot embodiment and task definitions that are environmentally adapted and balance task-oriented behavior with exploration. AutoFac is thus generalist (deployable in many environments) but continually produces specialist solutions within such environments a perpetual robot machine.

Oil and gas perspectives of the Ordoviksky-Nizhnefransky mega-complex of the Pechorsk Sea shelf

A fundamentally important result of offshore exploration is the identification of a new oilbearing region in the eastern part of the Pechomorsk shelf. Large oil fields have been discovered here: Prirazlomnoye, Varandey-more, Medynskoye-more, Dolginskoye. The explored reserves and resources of hydrocarbons (HC) suggest that in the near future a new oil-producing region will be formed on the shelf of the Pechora Sea. According to the State Balance, the total initial raw oil resources in the Pechora Sea are 3273.2 million tons. The main task of our work is the desire of the authors to draw attention to the problem of accelerating the pace of searches for promising objects on the shelf of the Pechora Sea and additional exploration of already discovered deposits in the Ordovician-Lower Fransk oil and gas megacomplex in the Varandey-Adzvinskaya structural zone (VASZ).The prevailing disproportion between the plans for the development of the fuel and energy complex, its resource availability and the rate of replenishment of the hydrocarbon raw material base of the Pechora Sea shelf may turn into serious problems for the energy security of the country.The further development of a large oil production cluster on the shelf of the Pechora Sea is primarily associated with the prospecting and development of hydrocarbon resources of the relatively deep-lying oil and gas bearing predominantly carbonate Ordovician-Lower Fransky megacomplex (MC) on the VASZ shelf and adjacent areas, especially at the Prirazlomnoye and Medynskoye-more fields.

Art Feature: “Precipice of Discovery”

Aboard the R/V Atlantis, ALVIN awaits deployment with one pilot and two scientists within its hull excited for the unknowns they may encounter on the sea floor. ALVIN, a human-occupied submersible owned by the U.S. Navy and operated by the Woods Hole Oceanographic Institution, represents the leading edge of exploration. This is exemplified by its use in the discovery of the Titanic’s location and deep-sea hydrothermal vents, key habitats in an environment without light. Our understanding of the deep sea and its inhabitants remains limited, especially compared to more accessible marine communities. Fortunately, there are marine biologists, including those at the University of Oregon, dedicated to exploring and advancing our knowledge about the deep sea. The Young Lab at the Oregon Institute of Marine Biology, the UO’s satellite campus in Coos Bay, Oregon, is dedicated to bringing undergraduates on research cruises that use ALVIN and other deep sea exploration vehicles to participate in multi-institutional, multi-disciplinary research. Undergraduate research allows students the opportunity to gain invaluable skills in bench work, scientific writing, networking, and field-specific methodologies, but it can also instill wonder. Working at sea with leading scientists, I have realized that there is so much we don’t know and that there are so many questions left to be answered by the next generation of researchers. By conducting research as undergraduates, we are developing our skills and curiosity to be trailblazers in our respective fields at the precipice of discovery, just like ALVIN has been for the last 58 years.

Dual closed loop AUV trajectory tracking control based on finite time and state observer.

The three-dimensional trajectory tracking of AUV is an important basis for it to complete its task. Due to many uncertain disturbances such as wind, wave and current on the sea, it is easy to cause problems such as slow convergence speed of the controller and saturation of the controller output in the three-dimensional trajectory tracking control of AUV. And the dynamic uncertainty of AUV's own model will have a great negative impact on AUV's trajectory tracking control. In order to solve the problem of slow convergence speed of the above controller, the finite time control method is introduced into the designed position controller. In order to solve the problem of AUV controller output saturation, an auxiliary dynamic system is designed to compensate the system control output saturation. In order to solve the uncertainty of AUV model, a reduced order extended observer is designed in the dynamic controller. It can observe the motion parameters of AUV at any time, and compensate the uncertainty of model uncertainty and external environment disturbance in real time. The control method in this paper is simulated in a three-dimensional model. The experimental results show that the convergence speed, control accuracy, robustness and tracking effect of AUV are higher than those of common trajectory tracker. The algorithm is loaded into the "sea exploration Ⅱ" AUV and verified by experiments in Suzhou lake. The effect of AUV navigation basically meets the task requirements, in which the mean value of pitch angle and heading angle error is less than 8 degrees and the mean value of depth error is less than 0.1M. The trajectory tracker can better meet the trajectory tracking control needs of the AUV.

Refractive geometry for underwater domes

Underwater cameras are typically placed behind glass windows to protect them from the water. Spherical glass, a dome port, is well suited for high water pressures at great depth, allows for a large field of view, and avoids refraction if a pinhole camera is positioned exactly at the sphere’s center. Adjusting a real lens perfectly to the dome center is a challenging task, both in terms of how to actually guide the centering process (e.g. visual servoing) and how to measure the alignment quality, but also, how to mechanically perform the alignment. Consequently, such systems are prone to being decentered by some offset, leading to challenging refraction patterns at the sphere that invalidate the pinhole camera model. We show that the overall camera system becomes an axial camera, even for thick domes as used for deep sea exploration and provide a non-iterative way to compute the center of refraction without requiring knowledge of exact air, glass or water properties. We also analyze the refractive geometry at the sphere, looking at effects such as forward- vs. backward decentering, iso-refraction curves and obtain a 6th-degree polynomial equation for forward projection of 3D points in thin domes. We then propose a pure underwater calibration procedure to estimate the decentering from multiple images. This estimate can either be used during adjustment to guide the mechanical position of the lens, or can be considered in photogrammetric underwater applications.

Design and Control Strategy of Bio-inspired Underwater Vehicle with Flexible Propulsor

Biomimetics aims to take inspiration from nature and develop new models and efficient systems for a sustainable future. Bioinspired underwater robotics help develop future submarines that will navigate through the water using flexible propulsor. This research has focused on the Manta Ray species as batoid has a unique advantage over other species. This study also aims to improve AUV (Autonomous Underwater Vehicle) efficiency through biomimetic design, the purpose of which is to observe and study the marine environment, be it for sea exploration or navigation. The design and prototyping process of bioinspired AUVs have been mentioned in this study, along with testing a propulsive mechanism for efficient swimming and turning capabilities. The Robot was designed taking structural considerations from the actual Manta-Ray locomotion and body design. The propulsion mechanism and control circuit were then implemented on the developed systems. The prototype of the Manta Ray was able to generate a realistic swimming pattern and was tested in an acrylic tank. The experimental results obtained in the tank basin are very close to the results we observe in the real-world scenario in terms of the vehicle's forward and turning motion.

Comparative analysis of fibre rope (polyester) and steel (wire) rope for a Floating Production Storage and Offloading (FPSO) terminal

The use of FPSO for deep sea exploration of hydrocarbon resources has been on trend. Thus, there is a need for ensuring safety with regards to station keeping. However, there are mainly two materials used for mooring line fabrication: fiber(synthetic) and Steel ropes. Polyester rope is regarded as a good synthetic option for deep water mooring application. This is as a result of its durability in cyclic tensile fatigue loading. This work compares the end forces between the proposed polyester (with top and bottom chains) rope with that of steel-wire rope (with top and bottom chains) from existing systems. From the dynamic analysis of the mooring lines with joint criteria for extremes dominated sea states, the maximum value of the end tension for wire rope is 1668.5722 kN of S-1 (Starboard-1) and the total force is 1668.5799 kN. Conversely for polyester rope, the maximum value of the end tension is 1130.0381 kN of S-1 (Starboard-1) and the total force is 1130.0511 kN. This result shows that the force and tension in polyester rope are lower than those of steel wire rope: indicating the effects of reduced vertical (gravity) forces of mooring rope on the FPSO with an associated improvement in horizontal restoring force. The substantial decrease in rope weight also reduces the complexity during installation, and increases the vessel's payload capacity. The latter enhances its capaciousness for crude oil cargo which consequently boosts its economic viability. Also, the fatigue life of the polyester rope is more than that of steel rope because of its low frequency load.

Abstract of: Paradise Fallen: Islands, Archipelagos and Xenoepistemics

Abstract of: Paradise Fallen: Islands, Archipelagos and Xenoepistemics

Research on the wettability of localized pulse electrolytic machining mold steel (GCr12)

As one of the most widely used metal materials, steel takes on an important role in deep sea and space exploration fields. However, the annual economic loss caused by steel corrosion is immeasurable. To resolve the problem, the localized pulse electrochemical machining (PECM), an efficient, fast and environment-friendly method, was introduced to fabricate microstructures on the surface of mold steel (GCr12). Results show that a super-hydrophobic surface has been obtained and its corrosion resistance has been significantly enhanced without the need to modify the surface by low surface energy solution. Thanks to the optimal working parameters (7.9 V and 2 ms) identified from the processing, the water contact angle of 161.8° was obtained. After fabrication by PECM, the surface microstructure, chemical element, and wettability were characterized and analyzed by scanning electron microscope (SEM), laser scanning confocal microscope (LSCM), EDS energy spectrometer, and optical contact angle measuring instrument, respectively. According to the experimental results, the surface honeycomb structure (micro/nano binary structure) is proven to be the main factor affecting wettability. Next, durability tests and corrosion resistance tests were carried out and the contact angle decreased by 4.4% and 6.7% respectively compared with the original contact angle, indicating that the surface after PECM has strong durability and good corrosion resistance, which can effectively solve the corrosion problem of steel. Therefore, using localized PECM technology to prepare microstructure on the surface of mold steel has a good application prospect in industry.

All-silica fiber-optic temperature-depth-salinity sensor based on cascaded EFPIs and FBG for deep sea exploration.

Using fusion splicing and hydroxide catalysis bonding (HCB) technology, an all-silica inline fiber-optic sensor with high-pressure survivability, high-resolution salinity measurement capability, and corrosion resistance for deep sea explorations is proposed and experimentally demonstrated. Two extrinsic Fabry-Perot interferometers (EFPIs) and a fiber Bragg grating (FBG) are cascaded in one single-mode fiber (SMF), enabling structural integration of single lead-in fiber and versatility of the sensing probe for temperature, depth, and salinity monitoring. The HCB technology offers a polymer adhesive-free assembly of one open-cavity EFPI for refractive index (RI) (salinity) sensing under normal pressure and temperature (NPT) conditions, showing obvious advantages of strong bonding strength, reliable effectiveness, and no corrosive chemicals requirements. The other EFPI formed by a fused structure is designed for pressure (depth) measurement. The cascading of EFPIs, especially the open-cavity EFPI immersed in water, will result in large light transmission loss and bring challenges to signal interrogation. Graded-index fiber (GIF) micro-collimators and reflective films are added to prevent dramatic degradations of signal intensity and fringe visibility underwater. Thereby, a Fabry-Perot (FP) cavity of several hundreds of microns in length and an open cavity of a thousand microns can be cascaded for underwater applications, effectively enhancing sensitivities and underwater signal readout simultaneously. Results show that the proposed sensor can well operate in the deep-sea pressure range of 0∼2039.43 mH2O, RI range of 1.33239∼1.36885 RIU, and temperature range of 23∼80 °C, with resolutions of 0.033 MPa, 4.16×10-7 RIU, and 0.54 °C, respectively. With the multi-parameter measurement capability, all-silica construction, and inline compact structure, the proposed sensor could be a potential candidate for deep sea exploration.

Review on Unmanned Underwater Robotics, Structure Designs, Materials, Sensors, Actuators, and Navigation Control

Since its beginning, around the 50s decade, until present days, the area of unmanned underwater vehicles (UUV) has considerably grown through time; those have been used for many tasks and applications, from bomb searching and recovery to sea exploration. Initially, these robots were used mainly for military and scientific purposes. However, nowadays, they are very much extended into civils, and it is not hard to find them being used for recreation. In this context, the present research is an effort to make a walkthrough of evolution in this area, showing a diversity of structure designs, used materials, sensor and instrumentation technologies, kinds and the number of actuators employed, navigation control techniques, and what is new in development trends. The paper gives a clear starting point for those who are initializing into this research area; also, it brings some helpful knowledge for those who already have experience.

The Reason for the Darkness of the Night: Edgar Allan Poe and the Forging of American Science

The Reason for the Darkness of the Night: Edgar Allan Poe and the Forging of American Science

The Reason for the Darkness of the Night: Edgar Allan Poe and the Forging of American Science

The Reason for the Darkness of the Night: Edgar Allan Poe and the Forging of American Science

Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN’s SDGs

Catch-only models (COMs) have been the focus of ongoing research into data-poor stock assessment methods. Two of the most recent models that are especially promising are (i) CMSY+, the latest refined version of CMSY that has progressed from Catch-MSY, and (ii) SRA+ (Stock Reduction Analysis Plus), one of the latest developments in the field. Comparing COMs and evaluating their relative performance is essential for determining the state of regional and global fisheries that may be lacking necessary data that would be required to run traditional assessment models. In this paper we interrogate how performance of COMs can be improved by incorporating additional sources of information. We evaluate the performance of COMs on a dataset of 48 data-rich ICES (International Council for the Exploration of Seas) stock assessments. As one measure of performance, we consider the ability of the model to correctly classify stock status using FAO’s 3-tier classification that is also used for reporting on sustainable development goals to the UN. Both COMs showed notable bias when run with their inbuilt default heuristics, but as the quality of prior information increased, classification rates for the terminal year improved substantially. We conclude that although further COM refinements show some potential, most promising is the ongoing research into developing biomass or fishing effort priors for COMs in order to be able to reliably track stock status for the majority of the world’s fisheries currently lacking stock assessments.