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The surface ocean is the main source of iodine to the atmosphere, where it plays a crucial role including in the catalytic removal of tropospheric ozone. The availability of surface oceanic iodine is governed by its biogeochemical cycling, the controls of which are poorly constrained. Here we show a near two-year time series of the primary iodine species, iodide, iodate and dissolved organic iodine (DOI) in inner shelf marine surface waters of the Western English Channel (UK). The median ± standard deviation concentrations between November 2019 and September 2021 (n=76) were: iodide 88 ± 17 nM (range 61-149 nM), iodate 293 ± 28 nM (198-382 nM), DOI 16 ± 16 nM (<0.12-75 nM) and total dissolved iodine (dIT) 399 ± 30 nM (314-477 nM). Though lower than inorganic iodine ion concentrations, DOI was a persistent and non-negligible component of dIT, which is consistent with previous studies in coastal waters. Over the time series, dIT was not conserved and the missing pool of iodine accounted for ~6% of the observed concentration suggesting complex mechanisms governing dIT removal and renewal. The contribution of excess iodine (I*) sourced from the coastal margin towards dIT was generally low (3 ± 29 nM) but exceptional events influenced dIT concentrations by up to ±100 nM. The seasonal variability in iodine speciation was asynchronous with the observed phytoplankton primary productivity. Nevertheless, iodate reduction began as light levels and then biomass increased in spring and iodide attained its peak concentration in mid to late autumn during post-bloom condITions. Dissolved organic iodine was present, but variable, throughout the year. During winter, iodate concentrations increased due to the advection of North Atlantic surface waters. The timing of changes in iodine speciation and the magnitude of I* subsumed by seawater processes supports the paradigm that transformations between iodine species are biologically mediated, though not directly linked. [ABSTRACT FROM AUTHOR]

As charismatic and iconic species, penguins can act as "ambassadors" or flagship species to promote the conservation of marine habitats in the Southern Hemisphere. Unfortunately, there is a lack of reliable, comprehensive, and systematic analysis aimed at compiling spatially explicit assessments of the multiple impacts that the world's 18 species of penguin are facing. We provide such an assessment by combining the available penguin occurrence information from Global Biodiversity Information Facility (>800,000 occurrences) with three main stressors: climate‐driven environmental changes at sea, industrial fisheries, and human disturbances on land. Our analyses provide a quantitative assessment of how these impacts are unevenly distributed spatially within species' distribution ranges. Consequently, contrasting pressures are expected among species, and populations within species. The areas coinciding with the greatest impacts for penguins are the coast of Perú, the Patagonian Shelf, the Benguela upwelling region, and the Australian and New Zealand coasts. When weighting these potential stressors with species‐specific vulnerabilities, Humboldt (Spheniscus humboldti), African (Spheniscus demersus), and Chinstrap penguin (Pygoscelis antarcticus) emerge as the species under the most pressure. Our approach explicitly differentiates between climate and human stressors, since the more achievable management of local anthropogenic stressors (e.g., fisheries and land‐based threats) may provide a suitable means for facilitating cumulative impacts on penguins, especially where they may remain resilient to global processes such as climate change. Moreover, our study highlights some poorly represented species such as the Northern Rockhopper (Eudyptes moseleyi), Snares (Eudyptes robustus), and Erect‐crested penguin (Eudyptes sclateri) that need internationally coordinated efforts for data acquisition and data sharing to understand their spatial distribution properly. [ABSTRACT FROM AUTHOR]

The surface ocean is the main source of iodine to the atmosphere, where it plays a crucial role including in the catalytic removal of tropospheric ozone. The availability of surface oceanic iodine is governed by its biogeochemical cycling, the controls of which are poorly constrained. Here we show a near two-year time series of the primary iodine species, iodide, iodate and dissolved organic iodine (DOI) in inner shelf marine surface waters of the Western English Channel (UK). The median ± standard deviation concentrations between November 2019 and September 2021 (n=76) were: iodide 88 ± 17 nM (range 61-149 nM), iodate 293 ± 28 nM (198-382 nM), DOI 16 ± 16 nM (

Ship heave motion measurement is crucial for ensuring vessel stability, navigation precision, and maritime engineering safety. In order to achieve accurate heave motion measurement, a method based on an adaptive digital high–pass filter is proposed. The approach involves constructing a ship heave motion model, conducting an analysis of heave motion, determining the optimal cutoff frequency for the adaptive filter based on an analysis of filtering and sensor errors, and designing an adaptive delay–free digital high–pass filter. Through simulation experiments in various sea conditions and platform tests, the method demonstrates superior performance. In comparison to fixed–parameter complementary filters, it exhibits a reduction of over 50% in maximum error and mean square error. [ABSTRACT FROM AUTHOR]

Turbidity currents often originate from relatively high‐temperature water bodies near the coast of the upper continental shelf. Turbidity currents are the main carriers that transport land sediments to the deep sea. Their impact on heat exchange and material transport in the deep‐sea ecosystem is receiving more attention. However, presently, there are few studies on heat transport by turbidity currents. This article presents a coupled model of multiphase flow and heat transfer through laboratory experiments and numerical simulations. The effects of sediment particle size, density, and Froude number on the characteristics of turbidity current heat transfer are analyzed, and the heat flux carried by turbidity currents transporting upper‐layer heat into the deep sea is reproduced. The results indicate that turbidity currents are carriers of shallow heat into the deep sea. The temperature structure within turbidity currents follows a Gaussian function and can effectively preserve heat. The efficiency of the long‐distance transport of heat carried by turbidity currents is negatively correlated with sediment particle size and the velocity of turbidity currents, and positively correlated with sediment concentration. Turbidity current heat shock events in the future may have significant and far‐reaching impacts on deep‐sea ecosystems. Plain Language Summary: Turbidity currents are the main carriers of terrestrial sediment to the deep‐sea plain, transporting large amounts of water and sediment along the seabed to the deep sea. Water temperature is a crucial environmental factor, and aquatic species highly depend on specific thermal conditions for effective reproduction. High‐temperature turbidity currents originating from shallow waters pose a risk of "thermal shock" to the water environment along their path, the extent and scope of which are not yet clear. In this study, a new coupled model of multiphase flow and heat transfer is established through laboratory experiments and numerical simulations, providing an opportunity to estimate the heat flux carried by turbidity currents into the deep sea in the marine environment. We found that turbidity events generated by high‐density river inflows into the sea can carry most of their own heat into the deep sea and significantly affect the temperature of the environmental water along the path. This, in turn, helps to understand the process of turbidity currents carrying upper‐layer heat into the deep sea, which is an essential part of the global system of heat transport and cannot be ignored. Key Points: A turbidity current model of multiphase flow and heat‐coupled transport is establishedParticle Size and Densimetric Froude Number largely explain the variability of transfer efficiency on turbidity heat transferThis model reproduces the turbidity current event that carries heat into the deep sea and evaluates the heat flux and impact range [ABSTRACT FROM AUTHOR]

Classifying habitat patches as sources or sinks and determining metapopulation persistence requires coupling connectivity between habitat patches with local demographic rates. While methods to calculate sources, sinks, and metapopulation persistence exist for discrete‐time models, there is no method that is consistent across modeling frameworks. In this paper, we show how next‐generation matrices, originally popularized in epidemiology to calculate new infections after one generation, can be used in an ecological context to calculate sources and sinks as well as metapopulation persistence in marine metapopulations. To demonstrate the utility of the method, we construct a next‐generation matrix for a network of sea lice populations on salmon farms in the Broughton Archipelago, BC, an intensive salmon farming region on the west coast of Canada where certain salmon farms are currently being removed under an agreement between local First Nations and the provincial government. The column sums of the next‐generation matrix can determine if a habitat patch is a source or a sink and the spectral radius of the next‐generation matrix can determine the persistence of the metapopulation. With respect to salmon farms in the Broughton Archipelago, we identify the salmon farms which are acting as the largest sources of sea lice and show that in this region the most productive sea lice populations are also the most connected. The farms which are the largest sources of sea lice have not yet been removed from the Broughton Archipelago, and warming temperatures could lead to increased sea louse growth. Calculating sources, sinks, and persistence in marine metapopulations using the next‐generation matrix is biologically intuitive, mathematically equivalent to previous methods, and consistent across different modeling frameworks. [ABSTRACT FROM AUTHOR]

Ship heave motion measurement is crucial for ensuring vessel stability, navigation precision, and maritime engineering safety. In order to achieve accurate heave motion measurement, a method based on an adaptive digital high–pass filter is proposed. The approach involves constructing a ship heave motion model, conducting an analysis of heave motion, determining the optimal cutoff frequency for the adaptive filter based on an analysis of filtering and sensor errors, and designing an adaptive delay–free digital high–pass filter. Through simulation experiments in various sea conditions and platform tests, the method demonstrates superior performance. In comparison to fixed–parameter complementary filters, it exhibits a reduction of over 50% in maximum error and mean square error.

Modern computers with specialised software are able to simulate oceans with waves and sea currents, and the action of wind, gravity, ships and other vehicles. The high-level programming languages that are used in this type of software can read information from navigation devices connected to the computer (e.g., via serial ports), and proceed to use the raw data in control algorithms. More and more desktop software and simulators can use data from additional electronic devices such as pressure sensors, temperature sensors, etc. Thus, it is possible to conduct real-time communication with a PLC (programmable logic controller) and use it in simulators. In this article, a user interface designed in Unity3d is presented. The user interface was able to read data from navigation devices, which were used in a ship positioning control algorithm. Verification of the algorithm occurred during research on a real ship, which used an anchor-based positioning system. Using data obtained on the real ship, a mathematical model of anchor winches was developed. Next, the mathematical model was implemented in the simulator developed in Unity3d. The simulator contained the same environmental conditions as during the research on the real ship. The mathematical model of anchor winches and implementation developed in the simulator will allow for future research on anchor-based positioning systems (e.g., in different environmental conditions). The research resulted in a shift of the ship's position by 26.3 m under 280 degrees. The difference in arrival time to the target point between the real ship and the virtual ship was 19%, and the difference in position deviation was 330%. [ABSTRACT FROM AUTHOR]

Identifying the provenance of marine animals yields fundamental data on a species’ ecology and life history and enables the geolocation of individuals for food forensic applications. However, many provenance methods are resource-intensive and developed on a species-specific basis. Here we discuss how natural chemical markers with predictable spatial patterns and common expression among species could be used as provenancing tools that are universally applicable to many species. To demonstrate the universal marker concept, we focus on stable oxygen isotopes bound within calcium carbonate biominerals. In doing so, we compiled a global database of oxygen isotope values to illustrate universal latitudinal patterns across key marine taxa. We then discuss how this concept could be integrated within a spatial modelling framework and applied to tackle the environmental challenge of seafood provenance. By developing universal markers we have the opportunity to trace a greater range of species to support their conservation and management.

This brief presents a robust nonlinear state estimator for autonomous surface vehicles, where the movement is restricted to the horizontal plane. It is assumed that only the vehicle position and orientation can be measured, being the former affected by bounded noises. Then, under some fair standard assumptions concerning the maximum velocities and acceleration rates of the vehicle, the estimator is able to reconstruct not only the velocities but also the lumped generalized disturbances that cluster external disturbances, nonlinearities, and unmodeled dynamics. The observer is easily tunable by the user, with a set of four scalars, two of them related to the velocity of convergence of the estimator, and other two parameters to set the desired tradeoff between noise sensitivity and disturbance rejection. Several simulations with a well-known test-bed craft are provided to show how the proposed algorithm outperforms previous ones in the literature under realistic environmental conditions. [ABSTRACT FROM AUTHOR]

In this work, the issue of obtaining consistent parameter estimators for nonlinear regression models where the regressors are second-order modulus functions is explored. It is shown that consistent instrumental variable estimators can be obtained by estimating first and second-order moments of non-additive environmental disturbances' probability distributions as nuisance parameters in parallel to the sought-after model parameters, conducting experiments with a static excitation offset of sufficient amplitude and forcing the instruments to have zero mean. The proposed method is evaluated in a simulation example with a model of a marine surface vessel. [ABSTRACT FROM AUTHOR]

Transient dynamics often differ drastically from the asymptotic dynamics of systems. In this paper we analyze transient dynamics in birth-jump metapopulations where dispersal occurs immediately after birth (e.g., via larval dispersal). We address the choice of appropriate norms as well as the effect of stage structure on transient dynamics. We advocate the use of the ℓ1 norm, because of its biological interpretation, and extend the transient metrics of reactivity and attenuation to birth-jump metapopulations in this norm. By way of examples we compare this norm to the more commonly used ℓ2 norm. Our focus is the case where transient dynamics are very different than asymptotic dynamics. We provide simple examples of metapopulations where this is the case and also show how increasing the number of habitat patches can increase this difference. We then connect the reactivity and attenuation of metapopulations to the source-sink classification of habitat patches and demonstrate how to meaningfully measure reactivity when metapopulations are stage-structured, with a focus on marine metapopulations. Our paper makes three primary contributions. First, it provides guidance to readers as to the appropriate norm and scalings for studying transients in birth-jump metapopulations. Second, it provides three examples of transient behavior in metapopulations involving slow-fast systems, crawl-bys, and high dimensionality. Third, it connects the concepts of reactivity and attenuation to the source-sink classification of habitat patches more commonly found in marine metapopulations [ABSTRACT FROM AUTHOR]

This paper presents a 3-D adaptive line-of-sight (ALOS) path-following algorithm for autonomous vehicles, marine craft, and aircraft. The origins of the cross- and vertical-track errors are proven to be uniform semiglobal exponential stable (USGES). The stability proof is based on a kinematic amplitude-phase representation of the North-East-Down (NED) positional rates instead of the classical Euler angle rotation matrix representation. Parameter adaption is used to obtain integral action such that the vehicle converges to the path in the presence of winds, waves, and ocean currents. Typical applications are guidance and path-following control systems for autonomous vehicles, marine craft, and aircraft, where the horizontal- and vertical-plane motions are strongly coupled. [ABSTRACT FROM AUTHOR]

Modern computers with specialised software are able to simulate oceans with waves and sea currents, and the action of wind, gravity, ships and other vehicles. The high-level programming languages that are used in this type of software can read information from navigation devices connected to the computer (e.g., via serial ports), and proceed to use the raw data in control algorithms. More and more desktop software and simulators can use data from additional electronic devices such as pressure sensors, temperature sensors, etc. Thus, it is possible to conduct real-time communication with a PLC (programmable logic controller) and use it in simulators. In this article, a user interface designed in Unity3d is presented. The user interface was able to read data from navigation devices, which were used in a ship positioning control algorithm. Verification of the algorithm occurred during research on a real ship, which used an anchor-based positioning system. Using data obtained on the real ship, a mathematical model of anchor winches was developed. Next, the mathematical model was implemented in the simulator developed in Unity3d. The simulator contained the same environmental conditions as during the research on the real ship. The mathematical model of anchor winches and implementation developed in the simulator will allow for future research on anchor-based positioning systems (e.g., in different environmental conditions). The research resulted in a shift of the ship’s position by 26.3 m under 280 degrees. The difference in arrival time to the target point between the real ship and the virtual ship was 19%, and the difference in position deviation was 330%.

Contaminants may affect ecosystem functioning by reducing the fitness of organisms and these impacts may cascade through ecosystems, particularly if the sensitive organisms are also habitat‐forming species. Understanding how sub‐lethal effects of toxicants can affect the quality and functions of biogenic habitats is critical if we are to establish effective guidelines for protecting ecosystems. We carried out a global systematic review and meta‐analysis critically evaluating contaminant effects on properties of habitat‐formers linked to ecosystem functioning. We reviewed a total of 95 publications. However, 40% of publications initially captured by the literature search were identified as having flaws in experimental design and ~11% did not present results in an appropriate way and thus were excluded from the quantitative meta‐analysis. We quantitatively reviewed 410 studies from 46 publications, of which 313 (~76%) were on plants and seaweeds, that is macro‐algae, saltmarsh plants and seagrasses, 58 (~14%) studied corals and 39 (~10%) looked at toxicant impacts on bivalves, with 70% of those on mussels and the remaining studies on oysters. Response variables analysed were photosynthetic efficiency, amount of chlorophyll a (as a proxy for primary production) and growth of plants, seaweeds and corals as well as leaf area of plants. We also analysed filtration, growth and respiration rates of bivalves. Our meta‐analysis found that chemical contaminants have a significant negative impact on most of the analysed functional variables, with the exception of the amount of chlorophyll a. Metals were the most widely harmful type of contaminant, significantly decreasing photosynthetic efficiency of kelps, leaf area of saltmarsh plants, growth of fucoids, corals and saltmarsh plants and the filtration rates of bivalves. Organic contaminants decreased the photosynthetic efficiency of seagrass, but had no significant effects on bivalve filtration. We did not find significant effects of polycyclic aromatic hydrocarbons on any of the analysed functional variables or habitat‐forming taxa, but this could be due to the low number of studies available. A meta‐regression revealed that relationships between concentrations of metal contaminants and the magnitude of functional responses varied with the type of metal and habitat‐former. Increasing concentrations of contaminants significantly increased the negative effects on the photosynthetic efficiency of habitat‐formers. There was, however, no apparent relationship between ecologically relevant concentrations of metals and effect sizes of photosynthetic efficiency of corals and seaweeds. A qualitative analysis of all relevant studies found slightly different patterns when compared to our quantitative analysis, emphasising the need for studies to meet critical inclusion criteria for meta‐analyses. Our study highlights links between effects of contaminants at lower levels of organisation (i.e. at the biochemical and/or physiological level of individuals) and ecological, large‐scale impacts, through effects on habitat‐forming species. Contaminants can clearly reduce the functioning of many habitat‐forming marine species. We therefore recommend the adoption of routine measures of functional endpoints in monitoring and conservation programs to complement structural measures. [ABSTRACT FROM AUTHOR]

In this paper, the automatic control of a single unmanned surface vehicle (USV) pushing a floating load is developed and theoretically analyzed. This represents a challenging control problem, since the manipulated load is underactuated and its open-loop dynamics is inherently unstable. Thus, a stabilizing controller must be designed. To this end, a scheme that combines partial feedback linearization with local linearization of the remaining nonlinear terms is proposed. Such scheme simplifies the design of a variable structure controller, that has robustness characteristics to parametric uncertainties and matched disturbances. The proposed closed-loop control system has local stability properties. Small-scale experimental results in calm waters, and simulation results, illustrate the performance of the proposed control system. [ABSTRACT FROM AUTHOR]

In marine systems, adult populations confined to isolated habitat patches can be connected by larval dispersal. Source–sink theory provides effective tools to quantify the effect of specific habitat patches on the dynamics of connected populations. In this paper, we construct the next-generation matrix for a marine metapopulation and demonstrate how it can be used to calculate the source–sink dynamics of habitat patches. We investigate the effect of environmental variables on the source–sink dynamics and demonstrate how the next-generation matrix can provide useful biological insight into transient as well as asymptotic dynamics of the model. [ABSTRACT FROM AUTHOR]

This work presents the results of an experimental verification of a coordinated path following strategy for underactuated marine vehicles. The coordinated path following strategy is presented, and is then experimentally verified using three autonomous underwater vehicles. The vehicles are required to coordinate their motion along spatially separated straight-line paths to obtain a desired formation. The vehicles are steered to the paths using an integral line-of-sight guidance approach that allows the vehicles to reject constant ocean currents. Simultaneously, the coordination is achieved by adjusting the velocity based on the along-path distance. First, simulation results are presented, which serve as benchmarks for the experimental results. Furthermore, the simulations are used to show the effect of changing different parameters. The simulation results are performed using high-fidelity hardware simulation models. The results obtained from experiments in the harbor of Porto are then presented and compared with the results of the simulation.

There is growing empirical evidence around the world demonstrating regime shifts of marine ecosystems. But generalizable criteria to detect and define regime shifts are elusive because of: (i) an incomplete scientific understanding of processes underlying regime shifts; (ii) because the baseline state and conditions are ill defined, and; (iii) due to an inherent ambiguity in the concept of system identity. We surveyed marine scientists in Tasmania, Australia, and determined the effect of changing conditions (including type of climate impact, species loss, species composition, spatio-temporal extent, and human intervention) on their perception of marine regime shift. We find, there is an objective difficulty in detecting regime shifts that goes beyond scientific uncertainty and there is disagreement on which configurations of change indeed constitute a regime shift. Furthermore, this difference of opinion was not related to the degree of confidence that scientists indicated when identifying regime shifts. This lack of consensus and seemingly unrelated scientific confidence, may be attributable to value ambiguity around people s attitudes, cognitive biases, and baseline shift. When applying evidenced-based reference points in well-reasoned Ecosystem Based Management, there should be scientific consensus on the manifestation and extent of specific regime shifts, and recognition of value ambiguities influencing scientific perceptions. [ABSTRACT FROM AUTHOR]

In this paper, a robust adaptive terminal sliding mode controller is proposed for dynamic positioning of a semi-submersible offshore platform. First, a state feedback controller is designed to stabilize the nominal system. Then a robust adaptive terminal sliding mode compensator is developed to eliminate the effects of uncertain dynamics and disturbances. It is shown, using Lyapunov methods, that the tracking error is driven to zero in finite time using the proposed control. The efficacy of the control algorithm is validated using simulation studies; it is shown that recent developments in the domain of robust exact differentiation are very helpful for controller implementation. [ABSTRACT FROM AUTHOR]

Abstract This paper describes the use of Kernel Ridge Regression (KRR) and Kernel Ridge Regression Confidence Machine (KRRCM) for black box identification of a surface marine vehicle. Data for training and test have been obtained from several manoeuvres typically used for marine system identification. Thus, a 20/20 degrees Zig-Zag, a 10/10 degrees Zig-Zag, and different evolution circles have been employed for the computation and validation of the model. Results show that the application of conformal prediction provides an accurate model that reproduces with large accuracy the actual behaviour of the ship with confidence margins that ensure that the model response is within these margins, making it a suitable tool for system identification. Highlights • Black box identification based on Conformal Predictors is used for marine vehicles. • Classical manoeuvres for marine vehicle identification are used to collect data. • A continuous-time model is trained and tested using data from real experiments. • Modelling with Kernel Ridge Regression and Kernel Ridge Regression Confidence Machine. • A confidence margin is proposed where the real behaviour of the vehicle should lie in. [ABSTRACT FROM AUTHOR]

As atmospheric CO2 levels continue to rise so too does the risk of severe impacts. Scientists clearly have an important role to play in preparing for and responding to climate change impacts; however, calls by scientists for global action have not led to the required changes. It is timely, therefore, for scientists to critically consider their own approach toward climate change research, particularly if we are to ameliorate or adapt to unwanted outcomes. Here we present three different pathways that allow scientists and scientific institutions to conceptualize the implications of their responses to climate change scenarios. These pathways are illustrated via three plausible futures for the marine environment under climate change. This approach allows future responsibilities, outcomes, and implication to be explored within and across pathways and can be applied to different scenarios for scientists and scientific institutions to anticipate and better prepare to contribute effectively to the future. Plain Language Summary: There is mounting evidence that impacts of climate change pose significant risks to society and human well‐being. The pace of large‐scale action on climate change is, however, insufficient to substantially reduce the likely future impacts. These are risks that this generation is imposing on future generations. In this context we outline a framework for scientists and scientific institutions to explore and assess the outcomes and implications of choosing different pathways (inactive, reactive, and proactive) in response to climate change. We developed three illustrative examples of plausible futures under climate change to demonstrate the implications of each of these pathways. We also outline a conceptual framework based on three factors: (i) potential to mitigate, (ii) impact of risk, and (iii) uncertainty in science that will assist scientists and scientific institutions to make informed decisions regarding their responses to global environmental change. Key Points: The implications of three pathways for scientists to respond to climate change are discussed such as maintaining trust in scienceA conceptual model is presented based on three factors: (i) potential to mitigate, (ii) impact of risk, and (iii) uncertainty in scienceA framework to assist scientists and scientific institutions to make informed decisions in response to global environmental change is outlined [ABSTRACT FROM AUTHOR]

Abstract This paper's objective is to analyze the main real-time risks in operation of autonomous marine systems, which follow from various levels of autonomy (LoA). High reliability management (HRM) is an established framework for assessing real-time operator performance in complex infrastructures. In this paper, the framework is applied to two cases representing different uses and autonomy levels: one on marine underwater robotics focusing on remotely operated vehicles (ROVs) and subsea intervention, and the other addressing operation of a complex marine surface vessel with a dynamic positioning (DP) system. Usually, autonomous systems are associated with unmanned systems, but several manned systems (for example, ships with complex automation and DP systems) have specific control functionality that can be characterized as autonomous. This paper focuses on manned and unmanned systems with different levels of autonomy and major hazard potential. The most important research finding is having identified multiple, different operational states that vary across two or three LoAs, each state of operations having significantly different risks to be managed in real time. The application of the HRM framework highlights the importance of enabling reliable operator control and online risk management in the development of next generation autonomous marine systems. Highlights • The objective is to analyze autonomy, operator control and risk in marine systems. • High reliability management (HRM) is a framework for assessing operator performance. • Two case studies with different levels of autonomy illustrate the HRM framework. • HRM demonstrates importance of safe operator control of autonomous marine systems. • The operator must be warned in advance that operational constraints may be exceeded. [ABSTRACT FROM AUTHOR]

This paper presents two novel results concerning the control allocation problem (CAP) for marine crafts with 2 azimuth thrusters. The first result is a novel closed form solution for the CAP which ensures Lipschitz continuity of the azimuth angle. The second result is a convex optimization reformulation of the CAP for the case of limited rate of changes for the actuators orientation which includes a novel regularization term that avoids anomalous behaviors due to underactuation. The effectiveness of the two methods are showcased through numerical simulations. • Novel closed-form solution enhances marine craft control with 2 azimuth thrusters. • Convex reformulation manages actuator rate of change, preventing anomalous behavior. • Simulations validate closed-form solution and convex optimization [ABSTRACT FROM AUTHOR]

Although the maritime industry has the potential to lead smart maintenance methodologies, current maintenance routines within the sector focus on either reactive or preventive maintenance approaches. These approaches are increasingly conservative and often prompted by an increase of large costs or unnecessary maintenance actions. Attempts are being made, however, to optimise these costs and actions through the application of novel practices, such as the employment of prognostic-based maintenance, which is an approach that aims to minimise risk while maximising the lifespan of a system. In this respect, Mar-RUL is introduced to support Operations & Maintenance (O&M) decision making and address some of the main challenges that the sector is currently experiencing, including the lack of fault data analysis and the formalisation of deep learning technologies for the implementation of the Remaining Useful Life (RUL) prediction. In response, a degradation data simulation module is developed in tandem with an ensemble model comprised of three distinct deep learning architectures: Markov-Convolutional Neural Network (CNN), 1D-CNN, and Long Short-Term Memory (LSTM) neural network. To evaluate the performance of Mar-RUL, a case study on the turbocharger of a diesel generator of a tanker ship is presented. The case study results demonstrated that the application of time series imaging and ensemble methods can provide promising outcomes for the enhancement of RUL prediction. [ABSTRACT FROM AUTHOR]

Recent developments in marine power systems, energy storage devices (ESDs) technology, and modification to rules and regulations increase the opportunities to improve efficiency and reduce emissions. One particular application is the strategic loading, where the ESD is charged and discharged cyclically, altering the instantaneous fuel consumption, thus aiming to reduce the average fuel consumption. Due to the ESD switching behavior, a hybrid simulation framework is an appropriate dynamic modeling tool. The hybrid simulation model is important in proper design and verification of control strategies for hybrid power plants. A hybrid model was derived, modeling transients as continuous-time events and modeling instantaneous behavior changes as discrete events. Due to the complexity of the system and its hybrid nature (continuous and discrete times), it is important to validate the derived model, such that are known its accuracy and limitations. The developed hybrid model was validated using experiments at the Hybrid Machinery Laboratory, Norwegian University of Science and Technology. The analyzed effects are the steady state, transient behavior, and losses. The transient behaviors include Generator-set (genset) dynamics and load ramps. The losses include the production losses, transmission losses, and ESD losses. The non-modeled effects include the load fluctuation, genset speed variation about the given set-point, and thermal effects on the genset and on the ESD. The results show good correlation between the hybrid model and the experiments. The fuel consumption estimation error stayed below 3% for all 15 analyzed cases, as well as having less than 9% deviation for the NOx gas emissions estimation. The model is considered as a good approximation for the real operation, enabling its use for design and research purposes.

The steady increase of the world population and economy leads to an increase in both types and amounts of goods transported over seas, which further inevitably leads to an increase of criminal activities in the maritime arena. In order to stifle criminal activities nations are forced to develop sophisticated sensor networks. The backbone of any sensor network is a communication network which connects all sensors with the command centers, most often located hundreds of kilometers away from the sensors. In developing countries, communication networks are very often poorly developed, leaving only satellite links as somewhat reliable means of communication. Henceforth, in this paper, a laboratory for the Internet of Things (IoT) communication infrastructure environment designed to facilitate maritime sensor network design process in areas where communication network is dependent on data transfer over satellite links is presented. In order to successfully describe and develop a laboratory for IoT communication infrastructure environment, necessary data are collected during the design and deployment of a maritime surveillance network in the Gulf of Guinea. The main advantage of the proposed laboratory environment is the inclusion of satellite link simulation in the IoT laboratory environment. This feature provides an opportunity to cover a much broader scope of IoT solutions compared to other IoT laboratories.

Highlights • A novel adaptive pitch control strategy is proposed. • Fuel consumption, CO 2 , NO x and PM emissions are reduced. • Improved acceleration and consistently limited thermal loading is demonstrated. • The approach can save 5–15% fuel and emissions and reduce acceleration time by 30%. • No more operator input is required to switch between fast and efficient sailing. Abstract Shipping urgently needs to reduce its impact on the environment, both due to CO 2 , NO x and particulate matter (PM) emissions and due to underwater noise. On the other hand, multifunction ships such as offshore support vessels, anchor handling and towing vessels, naval vessels and wind farm construction and support vessels require fast and accurate manoeuvring and need highly reliable systems to support reduced or no crew. Diesel mechanical propulsion with controllable pitch propellers provides high efficiency and low CO 2 emissions, but has traditionally been poor in manoeuvrability, can suffer from thermal overloading due to manoeuvring and requires significant measures to meet NO x and PM emission regulations. The control strategy of diesel mechanical propulsion with fixed combinator curves is one of the causes of the poor manoeuvrability, thermal overloading and cavitation noise during manoeuvring, such as slam start and intermediate acceleration manoeuvres. This paper proposes an adaptive pitch control strategy with slow integrating speed control that reduces fuel consumption, CO 2 , NO x and PM emissions and underwater noise, improves acceleration performance, limits engine loading and prevents engine under- and overspeed. A simulation study with a validated model of a case study Holland class Patrol Vessel demonstrates 5–15% reduction in fuel consumption and CO 2 emissions, compared to the baseline transit control mode in the ship speed range from 6 to 15 kts, during constant speed sailing. Moreover, the adaptive pitch control strategy reduces acceleration time from 0 to 15 kts with the slam start procedure by 32% compared to the baseline manoeuvre control mode and by 84% for an intermediate acceleration from 10 to 15 kts, while preventing thermal overloading of the engine, during straight line manoeuvres. Combining this control strategy with hybrid propulsion, running an electric drive in parallel with the propulsion diesel engine, can potentially further reduce fuel consumption at low speeds while also improving acceleration performance even more. Therefore, hybrid propulsion plants with controllable pitch propellers and adaptive pitch control can provide a significant contribution to the urgent reduction of environmental impact of shipping and to the need for more autonomous and reliable ship systems. [ABSTRACT FROM AUTHOR]

This paper proposes a regression Genetic Fuzzy System (GFS, FRULER) for a problem of sea wave parameters estimation from neighbor buoys, with application on wave energy systems. FRULER is a recently proposed, three-staged algorithm that combines an instance selection method for regression, a multigranularity fuzzy discretization of the input variables and an evolutionary algorithm to generate accurate and simple Takagi-Sugeno-Kant (TSK) fuzzy rules. We have applied FRULER to a real problem of significant wave height and energy flux prediction in one buoy of the West Coast of the USA (California), from values of other two neighbor buoys. In the case of the significant wave height, FRULER is able to obtain a robust prediction with only three rules, which in addition are fully interpretable, since they clearly separate swell situations from wind-sea in the prediction. In both cases, the variables used in the significant wave prediction are completely different and can be identified as relevant for the specific case (swell or wind-sea). In the case of the energy flux prediction, the interpretation of the rules provided by FRULER is more difficult, since eight rules are necessary to obtain the prediction. Even in this case, several rules can be clearly classified as swell predictors, and the rest of the rules describe local wind situation of waves. This study shows that the GFSs are useful tools to obtain robust and interpretable predictions in ocean wave parameter estimation problems. [ABSTRACT FROM AUTHOR]

Hybrid technology in marine vehicles can significantly reduce fuel consumption and local CO 2 emissions. It has been applied successfully to several ship-types, mostly with conventional, rule-based, strategies. To further improve performance, intelligent control strategies are necessary. This work, inspired by automotive research in Energy Management Strategies, applies the Equivalent Consumption Minimisation Strategy (ECMS) to a ship powered by a hybrid propulsion plant with hybrid power supply that can be recharged with renewable shore power. This hybrid configuration has the additional challenge to determine the optimal power-split between three or more different power sources, in real-time, and to optimally deplete the battery packs over the mission profile. To this end, a Mixed-Integer Non-Linear optimisation Problem is formulated and solved by combining Branch & Bound and Convex optimisation. Dynamic Programming (DP) is used to benchmark the real-time strategies, which are also compared to the current rule-based (RB) controller. Simulation results of a case study tugboat with validated models show that, with unknown load demand, 6% additional fuel savings can be achieved with ECMS. [ABSTRACT FROM AUTHOR]

Abstract For the emerging topic of automated and autonomous vehicles in all major sectors, reliable and accurate state estimation for navigation of these vehicles becomes increasingly important. Inertial navigation, aided with measurements from global navigation satellite systems (GNSS), allows high-rate and low-cost estimation of position, velocity and orientation in real-time applications. As the available satellite constellations for navigation are modernized and their number is rising, usage of multi-constellation, dual-frequency and integration of correction data lead to increased accuracy, especially in areas with partial shadowing. Different coupling methods, e.g. tightly- and loosely-coupled integrations, were developed to combine inertial and GNSS measurements. Also different error estimation filters were applied to the navigation problem, and evaluated against each other. For the typical navigation task, the objective is to choose a suitable algorithm for the specific requirements of the target application, and deploy it using an appropriate implementation strategy. This contribution gives a short introduction into the field of aided inertial navigation techniques, provides useful hints for implementation, and evaluates their performance in experiments using two different railway vehicles, an autonomous maritime vessel, and an unmanned aerial quadrotor. [ABSTRACT FROM AUTHOR]

Abstract Underwater navigation performance of Autonomous Underwater Vehicles (AUVs) strongly affects the quality of the collected data. Scientific literature extensively addresses the AUV tracking and self-localisation problems. However, no standard evaluation methods for vehicle navigation exist. Therefore, the authors' visionary perspective is to develop and implement an Underwater Test Range (UTR) to certify the vehicle compliance with long-term underwater navigation. This paper describes a first step along this research path represented by an in field validation of such conceived measurement network. Experiments are soundly based on extensive simulation analysis presented in previous works. In particular, an underwater network composed of acoustic modems with Ultra Short BaseLine capabilities is deployed as measurement rig. This setup, through bearing-only measurements, allows the tracking of an Autonomous Surface Vehicle (ASV) equipped with Differential GPS as position ground truth. Results show how the proposed methodology performs in a real marine scenario with challenging conditions due to shallow waters and magnetically noisy environment. [ABSTRACT FROM AUTHOR]

Abstract Over the last few decades, the robotics community has shown increasing interest in developing bioinspired swimming robots, driven by the need for more economical, more efficient, autonomous, highly flexible and maneuverable robotic systems for underwater operations. In this paper, we present a bioinspired underwater snake robot (USR) equipped with a passive caudal (tail) fin. In particular, a highly flexible USR configuration is presented that is capable of locomotion both on the ground and underwater due to its robust mechanical and modular design, which allows additional effectors to be attached to different modules of the robot depending on the requirements of the application. This provides flexibility to the operator, who can thus choose the proper configuration depending on the task to be performed in various uncertain environments on the ground and underwater. Experimental results on locomotion efficiency and path-following control are obtained for a physical USR to enable a comparison of the USR motion with and without the passive caudal fin, for both lateral undulation and eel-like motion patterns. Results comparing the locomotion efficiency in both simulations and experiments are presented in order to validate the proposed models for USRs. By means of fluid parameter identification, both a qualitative and a quantitative comparison between the simulated and experimental results are performed regarding the achieved forward velocity. Furthermore, the experimental results show that a path-following control approach that has previously been proposed for USRs without a caudal fin can be directly applied to solve the path-following control problem for this bioinspired USR with a passive caudal fin. In particular, it is shown that this path-following control approach successfully steers the robot toward and along the desired path, and furthermore, the results show that it is possible to almost double the forward velocity of the robot by using a passive caudal fin. [ABSTRACT FROM AUTHOR]

In the marine systems, engines represent the most important part of ships, the probability of the bearings fault is the highest in the engines, so in the bearing vibration analysis, early weak fault detection is very important for long term monitoring. In this paper, we propose a novel method to solve the early weak fault diagnosis of bearing. Firstly, we should improve the alternating direction method of multipliers (ADMM), structure of the traditional ADMM is changed, and then the improved ADMM is applied to the compressed sensing (CS) theory, which realizes the sparse optimization of bearing signal for a mount of data. After the sparse signal is reconstructed, the calculated signal is restored with the minimum entropy de-convolution (MED) to get clear fault information. Finally we adopt the sample entropy. Morphological mean square amplitude and the root mean square (RMS) to find the early fault diagnosis of bearing respectively, at the same time, we plot the Boxplot comparison chart to find the best of the three indicators. The experimental results prove that the proposed method can effectively identify the early weak fault diagnosis. [ABSTRACT FROM AUTHOR]

To obtain the complete operational picture of the maritime situation in the Exclusive Economic Zone (EEZ) which lies over the horizon (OTH) requires the integration of data obtained from various sensors. These sensors include: high frequency surface-wave-radar (HFSWR), satellite automatic identification system (SAIS) and land automatic identification system (LAIS). The algorithm proposed in this paper utilizes radar tracks obtained from the network of HFSWRs, which are already processed by a multi-target tracking algorithm and associates SAIS and LAIS data to the corresponding radar tracks, thus forming an integrated data pair. During the integration process, all HFSWR targets in the vicinity of AIS data are evaluated and the one which has the highest matching factor is used for data association. On the other hand, if there is multiple AIS data in the vicinity of a single HFSWR track, the algorithm still makes only one data pair which consists of AIS and HFSWR data with the highest mutual matching factor. During the design and testing, special attention is given to the latency of AIS data, which could be very high in the EEZs of developing countries. The algorithm is designed, implemented and tested in a real working environment. The testing environment is located in the Gulf of Guinea and includes a network of HFSWRs consisting of two HFSWRs, several coastal sites with LAIS receivers and SAIS data provided by provider of SAIS data. [ABSTRACT FROM AUTHOR]

Caffeine is an emerging contaminant considered to be an indicator of human contamination that has been widely detected in various aquatic systems, especially in continental waters. Nevertheless, the extent of its possible environmental impact is yet to be determined. This study determined the presence of caffeine, and evaluated the environmental hazard posed by this substance, in the “Rías Gallegas”, a series of costal inlets in north-west Spain which are of great ecological value and in which fishing and bivalve farming, are a significant source of income. Caffeine was found to be present at concentrations higher than the limit of quantification (LOQ = 3.07 ng L − 1 ) in 15 of the 23 samples analysed, with the highest seawater concentration being 857 ng L − 1 (the highest measured in seawater in Spain). Six out of 22 seawater samples resulted in a hazard quotient (HQ) from chronic exposure higher than 1 with the highest being 17.14, indicating a high probability of adverse effects in the aquatic environment. Environmental Exposure Distributions (EEDs) generated from a literature review of caffeine levels reported previously in four out of the five continents, showed that 28% of all seawater samples, and 69% of all estuary water samples where caffeine has ever been measured resulted in HQ > 1 for chronic exposure. Further studies into the potential adverse effects that may arise from exposure to caffeine in aquatic systems are still required. Indeed, the need to gain a more in-depth understanding of the long-term ecotoxicological effects of caffeine is essential to ensure the quality of our health and environment. [ABSTRACT FROM AUTHOR]