Underwater Investigations Research Articles

Optimisation of underwater acoustic sensor networks

The oceans are the scene of intense economical and industrial activities. It is becoming even more competitive with recent military activities and the upcoming development of marine renewable energies. All of these activities have a significant impact on marine ecosystems and must be carefully evaluated for any maritime planning. The marine environment is also a very effective medium for the propagation of acoustic waves over long distances, depending on the frequency, the source level, the static (bathymetry) and the dynamic (hydrology) oceanographic conditions. Such conditions make acoustic sensors primary candidates for underwater investigations and the distribution of mixed sensors with various sensitivities, frequency bandwidths or positioning can be optimized for detection, localization or monitoring purposes. This contribution aims to present a methodology based on evolutionary algorithms which considers the overall physical state of the marine environment and determines the optimal configurations of mixed underwater acoustic networks. The relevance of various objectives, or metrics, can be discussed, as well as specific search operators for crossover and mutation based on preliminary results.

Integrating Widespread Coral Reef Monitoring Tools for Managing both Area and Point Annotations

Abstract. Large-area image acquisition techniques are essential in underwater investigations: high-resolution 3D image-based reconstructions have improved coral reef monitoring by enabling novel seascape ecological analysis. Artificial intelligence (AI) offers methods for significantly accelerating image data interpretation, such as automatically recognizing, enumerating, and measuring organisms. However, the rapid proliferation of these technological achievements has led to a relative lack of standardization of methods. Remarkably, there are notable differences in procedures for generating human and AI annotations, and there is also a scarcity of publicly available datasets and shared machine-learning models. The lack of standard procedures makes it challenging to compare and reproduce scientific findings. One way to overcome this problem is to make the most used platforms by coral reef scientists interoperable so that the analyses can all be exported into a common format. This paper introduces functionality to promote interoperability between three popular open-source software tools dedicated to the digital study of coral reefs: TagLab, CoralNet, and Viscore. As users of each platform may have different analysis pipelines, we discuss several workflows for managing and processing point and area annotations, improving collaboration among these tools. Our work sets the foundation for a more seamless ecosystem that maintains the established investigation procedures of various laboratories but allows for easier result sharing.

Undersea Water Objects Detection and Classification Using Optimized Region-Based Convolutional Neural Network

Underwater autonomous operation is becoming increasingly crucial to avoid the hazardous in the environment of high-pressure deep-sea due to the significance of underwater investigation. The most crucial piece of technology for underwater-based task is intelligent computer vision. In an underwater environment, underwater vision requires good image quality, and illumination with better classification of sea objects. This work presented a novel technique of Optimized Region-based Convolutional Neural Network (ORCNN). For this work, the Gaussian filter is used to remove the noise and enhance the image quality during pre-processing and the Improved Affinity Propagation Clustering (IAPC) model segments the objects. After that, the Region-based Convolutional Neural Network (RCNN) model classifies various objects such as urchins, seagrass, fishes, and rocks in which the RCNN parameters are tuned via a light spectrum optimizer algorithm (LSOA). can also input the segmentation prediction images and the labeled images into the discriminant convolutional network and improve the segmentation accuracy of underwater images by further enhancing the essential characteristics of learning data through the confrontation training of generators and discriminators. The experimental results demonstrate that higher performance is provided by the newly developed ORCNN -Net predictive model when compared to other comparative algorithms while considering the negative and positive metrics.

Garnys: An underwater riverine site with delayed Neolithisation in the southeastern Baltic

This paper presents the first results of both dryland and underwater investigations at the multi-period Garnys riverine site situated on the Žeimena River in eastern Lithuania. There, during 2017–2020 a professional diver and amateur archaeologist collected hundreds of Mesolithic-Neolithic archaeological finds made of wood, bone, antler, stone, and ceramic from the riverbed and on its bank. Moreover, in eroded places of the riverbed, the wooden remains of several fish weirs were observed. In 2021 professional archaeologists continued the research, including field investigations followed by various laboratory analyses. These included AMS 14C dating of 16 various ecofacts, artefacts and wooden constructions, wood and animal taxa determinations, and the results of traceological analysis of the flint and osseous artefacts. Our research demonstrates that the site was intensively used for hunting, gathering and fishing during the Mesolithic and subsequent Subneolithic and Neolithic. Intriguingly, there was no evidence for agriculture, while the numerous Neolithic ceramics largely follow the Subneolithic traditions. The Garnys site is therefore unique and a clear example for delayed Neolithisation in a forested and lacustrine area in the eastern Baltic region. During the Metal Ages, the site had been used exclusively for stationary fishing.

Structural design evaluation for Underwater Remotely Operated Vehicle (ROV), case study: Madura Straits

Using Remotely Operated Vehicles (ROV) is very important, especially in underwater investigations. The Madura Strait, located between the Java islands and Madura, is used as an industrial area, especially for oil and gas sources. Therefore, the ROV structure must be designed in such a way that it can withstand the hydrostatic loads it receives during operations in the deep sea. The study was conducted to determine the ROV’s ability to withstand hydrostatic loads using materials such as steel, aluminium, and HDPE. The pre-designed ROV is converted and modeled in 3D. The model formed and detailed as the basic form of the ROV is imported to the Finite Element Analysis tools to obtain the value of the stress and deformation of the ROV. Therefore, the load is adjusted to the hydrostatic pressure, with the seawater depth up to 200 m. The study structural design evaluation is able used as a reference for selecting materials used in the ROV.

Automated Fish Detection and Tracking System Using Pre-Trained Mask R-CNN for Ecological Biodiversity

Introduce a new dynamic classifying algorithm in this paper to recognize and monitor fish activity to simultaneously better comprehend their synapomorphies. The pre-trained Mask Regional Convolutional Neural Network (Mask-R-CNN) is trained using a set of test models extracted from recorded video recording. The approach suggested subsequently yields well-enhanced feature vectors. The system’s automatic fish detection and tracking capabilities are improved, enhancing underwater investigation for supervising ecological biodiversity. The publicly accessible field-truth dataset assesses recall, F1-score, and classification and tracking precision. Utilizing current tracking R-CNN algorithms like Lowest Output Sum of Siamese Mask (SiamMask), Sequential Non-Maximum Suppression (Seq-NMS), and Squared Errors (MOSSE), comparative performance testing is conducted. In comparison to Siam-Mask (84%), Seq-NMS (78%) and MOSSE (75%), more than 120 of 170 specific bream were detected using the pre-trained Mask-R-CNN of the proposed algorithm (87%). This pre-trained Mask R-CNN system was used in the evaluation, and it was discovered that detection and tracking accuracy had increased significantly. This suggests that the ocean ecosystem could benefit from applying the proposed approach for management of ecology.

Hydrographic Drone Non-Invasive Underwater Investigations: New Archaeological Discoveries in Valle Fossa di Porto (Comacchio—FE, Italy)

During forensic archaeological research conducted in 2021 in the Comacchio Lagoon (FE), we detected new data concerning the ancient local hydrography to the west of Argine Agosta, an ancient bank, in Valle Fossa di Porto. A systematic campaign of geophysical surveys for heritage and archaeology was conducted with a hydrographic drone equipped with a single-beam bathymetric sensor echo sounder, sub-bottom profiler, and side-scan sonar. In combination with the indirect non-invasive investigations, systematic surveys of the walkable areas were also completed. These remote-sensing studies have relocated the River Vatrenus palaeo-watercourse, while visual census have brought to light a system of wooden palisades with floors made of wood associated with some scattered finds belonging to the material culture dating back to the Mediaeval and Renaissance periods. A preview of the results of this case study is presented here, contributing to the reconstruction of the ancient landscape and waterscape area of the Valle Fossa di Porto.

Roman ‘Well-cisterns’, Navigational Routes, and Landscape Modifications in the Venice Lagoon and Northeastern Adriatic

Underwater investigations in the lagoon of Venice have revealed a partially preserved structure interpreted as a Roman ‘well-cistern’. It is indeed very similar to another, better-preserved building excavated in the same area. The analysis of the mortar, the evaluation of the depth of the structure base in relation to relative sea level, and the absence of foundation poles in the underlying soft lagoon mud support such interpretation. A comparison with other poorly-studied Roman buildings of the same type located along the North Adriatic littoral suggests that they were probably used to supply ships with fresh water. In the Middle Ages, similar structures were used in the islands of the lagoon for sustenance of its residents and became a characteristic of the small squares (campi) of Venice.

Maritime Cultural Heritage, Coastal Change and Threat Assessment in Syria

Syria’s coastal and nearshore zone contains a significant, but under-researched, record of maritime cultural heritage (MCH) ranging from prehistory to the present. This is exemplified by a lack of underwater investigations, but also limited investigation of key onshore maritime sites such as ports and harbours. There is also a lack of specialist in-country management regarding maritime cultural heritage research and protection. This situation has been worsened by the ongoing conflict (since 2011), which has reduced (already limited) field investigation. To assist in the advancement of Syrian maritime archaeology, this paper presents a baseline assessment which makes use of a geospatial database generated from satellite imagery as well as both published and grey literature. This assessment reviews past coastal environment changes affecting the Syrian littoral, and then highlights past disturbances and potential future threats impacting the MCH. This is done through analysis of all coastal/nearshore sites documented to date and showcased in more detail using two case studies: Tabbat al-Hammam and Ras Ibn Hani. This enables discussion of the current state of Syrian maritime archaeology and suggests ways forward for its future management and investigation.

Preliminary forensic assessment of the visualised fingerprints on nonporous substrates immersed in water using the green and optimised novel nanobio-based reagent

The discovery of forensic evidence (e.g. weapons) during forensic underwater investigations has seen an increasing trend. To date, small particle reagent (SPR) has been one of the routinely used methods for visualising fingerprints on wet, non-porous substrates. However, the long term use of SPR is detrimental to humans and environment due to the use of toxic chemicals. Although previously we have successfully developed and optimised a greener nanobio-based reagent (NBR), its suitable practical use in a more realistic scene (e.g. outdoor pond) was not evaluated. Therefore, this present research is aimed at (1) investigating the performance of NBR against the benchmark SPR in visualising fingerprints immersed in a natural outdoor pond and (2) evaluating the greenness of NBR against the analytical Eco-Scale. Results showed that the performance of the optimised NBR was mostly comparable (University of Canberra (UC) comparative scale: 0) with SPR at visualising fingerprints on three different non-porous substrates immersed in a natural outdoor pond. Observably, the NBR had higher preference towards aged fingerprints (up to 4 weeks of immersion). In addition, its greenness assessment revealed 76 points, indicating ‘excellent green analysis’. The findings gathered here further supported the practical use of the NBR in forensic investigations.

Detection of Weak and Small Targets in Forward-Looking Sonar Image Using Multi-Branch Shuttle Neural Network

Autonomous Underwater Vehicle (AUV) is an automated navigation device, which can independently complete the underwater investigation and detection without supervision. However, the marine environment is getting increasingly severe, and the garbage in the ocean and fishnets cast by fishermen have a great negative influence on the work of AUV. To solve the problems of low precision and slow speed in the state-of-the-art network detection of weak and small targets in underwater sonar images, Yolo5 was improved by building the multi-branch shuttle neural network The dataset is collected by multi-beam forward-looking sonar Gemini720i, and includes “fishnet” and two representative types of knitted and plastic garbage, i.e., “cloth” and “plasticbag”. The original dataset is enhanced and balanced, and the effect of dataset distribution on the model performance is studied. Utilizing pre-training, the effects of Yolo5 family, i.e., Yolo5s, Yolo5m, Yolo5l and Yolo5x are compared using the balanced dataset, to explore the impacts on detecting weak and small targets of the deeper and wider networks of this family. In addition, the combinations of Yolo5s with lightweight networks, i.e., MobileNet3 and ShuffleNet2 are experimented, which further illustrates the effectiveness of the proposed network, and can satisfy the high accuracy and real-time requirements of AUV.

전산유체역학을 이용한 수중 예인운동체 자세안정화를 위한 파라미터 연구

A towed underwater body is connected to a towing vessel by a cable and operated for underwater investigation. The shape of the towed underwater body is consisted of the upper and lower hemisphere on a cylindrical body. An anti-reversing pin is positioned on the behind of the body to reduce yaw and sway motions and two guide vanes are positioned to reduce yaw, pitch and sway motions. OpenFOAM was used for computational studies. For the validation of numerical methods, the fluid flow around a sphere was simulated by computational fluid dynamics (CFD). The predicted drag force of a sphere was compared with the experimental data. A parameter study for various towed speeds, guide vane area, and guide vane located angle, was carried out using selected numerical methods. The forces and moments acting on the one guide vane were compared for various parameters.

Non-Uniform Non-Orthogonal Multicarrier Underwater Communication for Compressed Sonar Image Data Transmission

Efficient and reliable underwater sonar image transmission is increasingly desired for underwater investigation by autonomous underwater vehicles (AUV). However, it is extremely challenging due to the severe interference nature of underwater acoustic channels and the large data size of sonar images. In this paper, we first combine multicarrier modulation techniques with characteristics of compressed sonar image data to improve the transmission performance, where in previous research, image compression and multicarrier modulation were investigated separately. The compressed bitstream of sonar images is regarded as a new type of image with unique frequency characteristic. A non-uniform non-orthogonal multicarrier modulation scheme based on frequency characteristics of compressed sonar image data (F-NNMC) is proposed to meet the requirements of efficient and reliable sonar image transmission. The non-orthogonality between subcarriers improves the spectrum efficiency, and the non-uniform subcarrier structure can carry more effective information of the transmitted compressed data to improve the reliability. The simulation and experiment show that the proposed F-NNMC needs less frequency resource and has better peak signal-to-noise ratio (PSNR), structural similarity (SSIM), as well as lower bit error rate (BER) compared to orthogonal and non-orthogonal modulations.

Development of an Easy-to-Operate Underwater Raman System for Deep-Sea Cold Seep and Hydrothermal Vent In Situ Detection.

As a powerful in situ detection technique, Raman spectroscopy is becoming a popular underwater investigation method, especially in deep-sea research. In this paper, an easy-to-operate underwater Raman system with a compact design and competitive sensitivity is introduced. All the components, including the optical module and the electronic module, were packaged in an L362 × Φ172 mm titanium capsule with a weight of 20 kg in the air (about 12 kg in water). By optimising the laser coupling mode and focusing lens parameters, a competitive sensitivity was achieved with the detection limit of SO42− being 0.7 mmol/L. The first sea trial was carried out with the aid of a 3000 m grade remotely operated vehicle (ROV) “FCV3000” in October 2018. Over 20,000 spectra were captured from the targets interested, including methane hydrate, clamshell in the area of cold seep, and bacterial mats around a hydrothermal vent, with a maximum depth of 1038 m. A Raman peak at 2592 cm−1 was found in the methane hydrate spectra, which revealed the presence of hydrogen sulfide in the seeping gas. In addition, we also found sulfur in the bacterial mats, confirming the involvement of micro-organisms in the sulfur cycle in the hydrothermal field. It is expected that the system can be developed as a universal deep-sea survey and detection equipment in the near future.

A PORTABLE OPTO-ACOUSTIC SURVEY SOLUTION FOR MAPPING OF UNDERWATER TARGETS

Abstract. During underwater investigations, whatever the mission objective and the type of vehicle, obstacles detection and avoidance are essential tasks. They can either represent a target of interest that is the object of the mission or, on the contrary, represent obstacles that can hinder or affect the navigation of the vehicle. The underwater optical cameras that are usually fitted to underwater vehicles only offer a narrow field of view. The absorption of electromagnetic waves in the first few meters and the diffusion of light by the particles limit the use of these sensors to only a few meters range. The use of acoustic sensors, such as the forward looking sonar (FLS), is then necessary to enlarge the volume in which a target can be detected during the progression of the vehicle. Traditionally, sonars featured mechanical rotating parts, but lately bidirectional forward looking sonar, which directly produces a 2D image of the area, are becoming more and more common. Although these sonars can operate at frequency higher than 1MHz, their spatial resolution remains much lower if compared to current optical sensors and can be insufficient to identify and characterize a target. The combination of these two sensors in an operational scenario is essential to take advantage of each technology. In this paper we describe a low cost, multi-sensor, underwater survey solution for the identification, tracking, and 3D mapping of targets. After a description of the architecture of the opto-acoustics data acquisition and processing platform, we will focus on the calibration of the rigid transformation between the two sensors.

A drowned Mesolithic shell midden complex at Hjarnø Vesterhoved, Denmark and its wider significance

Anthropogenic shell accumulations (shell middens), often of great size, occur in their tens of thousands around the world’s coastlines. They mostly date from the Mid-Holocene onwards and are frequently taken as symptomatic of a Postglacial ‘revolution’ involving world-wide population growth and intensification in exploitation of marine resources. However, the comparative rarity of earlier deposits may have as much to do with Postglacial sea-level rise and the loss of evidence from earlier palaeoshorelines as with genuine socio-economic trends. Here we investigate the underwater Mesolithic (Ertebølle) shell midden of Hjarnø Vesterhoved in Denmark, one of the first underwater shell middens to be systematically verified as an anthropogenic shell deposit in a region world-famous for its many hundreds of Ertebølle shell mounds on the present shoreline. We show how a combination of geophysical survey, coring, excavation, stratigraphic interpretation and macroscopic analysis of midden contents can be used to identify underwater deposits, to unravel their taphonomic and post-depositional history in relation to surrounding sediments, and to distinguish between cultural and natural agencies of shell accumulation and deformation. We demonstrate the presence of an intact underwater shell-midden deposit dated at 5400–5100 cal BC, one of the earliest in Denmark. We demonstrate the usefulness of such material in giving new information about early coastal subsistence economies and greater precision to the measurement of palaeo-sea levels. We discuss the implications of our results for an improved understanding of the Mesolithic record in Denmark and of biases in the archaeological record of Late Pleistocene and Early-to-Mid Holocene coastal contexts. We emphasise the importance of researching more fully the geomorphological and taphonomic processes that affect the accumulation, destruction, burial, preservation and visibility of underwater archaeological deposits, the need to extend underwater investigations more widely and to more deeply submerged palaeoshorelines, and the combination of methods required to advance such investigations.

Numerical investigation of marine propeller Underwater Radiated Noise using acoustic analogy part 1: The influence of grid resolution

This study investigates the effects of grid resolution on hydroacoustic performance of the benchmark INSEAN E779A propeller operated in uniform flow, open water and non-cavitating conditions. In the numerical calculations, an incompressible hydrodynamic solver together with the porous FW-H (Ffowcs-Williams Hawkings) equation is used to predict the propeller URN (Underwater Radiated Noise). The first aim within this study is to explore the sensitivity of the grid resolution on the prediction of propeller hydroacoustic performance. Furthermore, amongst the contribution of nonlinear noise sources on overall acoustic pressure, the role of the tip vortex is believed to be dominant under non-cavitating conditions. The inadequate extension of the tip vortex is one of the drawbacks in the RANS (Reynolds-averaged Navier-Stokes) solver for accurate prediction of propeller URN, especially at the receivers located in the propeller's slipstream. Thus, the second aim within this study is to examine the contribution of tip vortex on overall acoustic pressure. In order to visualise the numerical noise and determine the realistic extension of the vortex distributions in the propeller's slipstream, the time derivative of the pressure technique is proposed in this study. The results indicate that insufficient grid resolution in the numerical simulations causes unphysical numerical noise which is attributed to the sliding interfaces, and it leads to contamination of the overall acoustic pressures. Moreover, an increase in grid resolution reduces numerical diffusion in the RANS solver, allowing for an extended tip vortex distribution. However, an increase in tip vortex extension and intensity alongside the downstream of the propeller is not adequate itself to make a reliable prediction of propeller URN by using RANS. Consequently, a more realistic prediction of propeller URN requires the use of advanced models (i.e. LES (Large Eddy Simulation) and DES (Detached Eddy Simulation)) together with the porous FW-H equation, particularly if the receivers located in the downstream are of great interest.

Numerical investigation of marine propeller underwater radiated noise using acoustic analogy Part 2: The influence of eddy viscosity turbulence models

The present study focuses on the impact of eddy viscosity turbulence models on the benchmark INSEAN E779A marine propeller hydroacoustic performance under non-cavitating and open water conditions. In the numerical calculations, Realisable k-epsilon (k-ε), k-ω Shear Stress Transport (k-ω SST) and Spalart-Allmaras turbulence models, which are widely used in hydrodynamic fields, are selected. Hydroacoustic performance of the model propeller is predicted with the porous FW-H formulation coupled with Reynolds-averaged Navier Stokes (RANS) solver. This study aims to show the effects of different turbulence models on marine propeller hydroacoustic performance at high and low blade loading conditions both in the near and far-fields. The numerical results show that the underwater radiated noise (URN) levels, which are predicted by using different eddy viscosity turbulence models together with the porous FW-H formulation, are found to be similar at low blade loading conditions. The reason behind this similarity is due to the analogous wake structure and hydrodynamic field. However, when the propeller loading is high, the propeller's wake loses its stability; hence, the coherent vortex structures break-up and evolve into the far-field of the propeller's slipstream. The instability process of the propeller's wake is predicted in a different manner by eddy viscosity turbulence models, and these differences cause dissimilar prediction of the URN in the far-field. Consequently, the underwater pressure field is considerably affected by the instability of the vortex structures (as a non-linear noise source) for far-field noise estimations. As a result, vortex instability in the propeller's slipstream might be the main noise source of the URN for far-field noise estimations under non-cavitating and high blade loading conditions.

New evidence from Bouldnor Cliff for technological innovation in the Mesolithic, population dispersal and use of drowned landscapes

Investigation of underwater prehistoric sites during the twenty-first century has been gathering momentum. This has been a positive development for the discipline that has been strengthened by research into human occupation of the drowned lands around the British coastline, particularly the submerged forests of the Solent seaway on the south coast of England as well as the North Sea. Over the last two decades underwater investigations at the Mesolithic site of Bouldnor Cliff, off the isle of Wight has revealed advanced wood working technological capabilities, the presence of sedimentary DNA from einkorn and outstanding levels of organic preservation including string, worked timbers, and most recently, a wooden platform. The timber assemblage represents the most extensive collection of Mesolithic worked wood in the country including previously unknown methods of timber working and wooden artefacts. The material evidence indicates links across Europe, while the wooden structures suggest some degree of sedentism. The site was occupied just prior to the severance of Great Britain from continental Europe, therefore, similar sites could remain in comparable landscapes before they were drowned by the emergent North Sea. This paper presents new evidence from Bouldnor Cliff to support previous interpretations, demonstrates how shallow underwater sites near the modern coastline can reveal new information about patterns of land use, population contacts and dispersal patterns over wide areas. It highlights their significance as a complement to large scale mapping of more deeply submerged landscapes and as a model for the discovery of archaeological sites in deeper water, and emphasises the need for more intensive investigation given the constant threat of erosion and destruction of such evidence.

Underwater Investigation and Analysis of Upstream Face for a Built 40 years’ and 6 km Long Embankment Dam in Africa

The world’s hydropower has experienced considerable development. With the coming of the post hydropower era, the business of new projects will gradually decrease, and meanwhile, the business of hydropower station renovation and dam maintenance will gradually increase. This paper introduces the methodology and the finding of the underwater investigation, analyses the upstream face stability and recommends solutions of rehabilitation for a built 40 years’ and 6 km long embankment dam in Africa, aiming to provide a reference for similar projects of dam maintenance.