Objective: To promote the physical and mental health of employees in a maritime setting and provide knowledge and tools to assist seafarers in managing daily challenges.
Materials and methods: The intervention drew on a goal-based approach, including workshops, coaching,health checks, interviews, and questionnaires.
Results: A process evaluation was used to explore intervention challenges and barriers. Results show that an intervention at sea is complex and needs flexibility. Findings varied, and the main challenges were low participation in one group and lack of continuity due to Covid-19. Data showed a significant positive shift in how the crew rated perceived stress and a statistically significant increase in intake of salad, fish, and vegetarian food.
Conclusions: Workplace interventions in poor health status settings are complex, necessary, and possible, and management’s participation is crucial. Increased awareness was achieved. Learning outcomes: The results showed some positive changes, such as lower stress levels and more intake of salad, fish, and vegetarian food. Flexibility is important for workplace interventions. Work place interventions contribute to health and wellbeing with appropriate management support.
The completeness and high predictability of hazardous scenarios by hazard identification methods are issues in risk analyses. A way to the improvement is to carry out both an exhaustive - to the extent possible - post-accident and predictive accident analysis. Currently, Natural Language Processing (NLP) allows quick processing of many accident reports. In combination with graphical tools, it is now even possible to automatically output causal diagrammatic models of accidents and visualize them on a multi-scenario accident diagram. A step forward is the application of NLP to support predictive analysis. Predictive accident analysis focuses on identifying deviations from expected or normal conditions, the subsequent events following these deviations, and their interactions leading to an accident. The expected or normal conditions are typically outlined in specifications and procedures. This paper demonstrates how NLP can assist hazard identification and predictive accident analysis during lifting operations on ships and offshore platforms.
This study investigates the complex and still insufficiently understood interactions between ocean currents and offshore wind farms (OWFs), with a focus on local-scale hydrodynamic effects near individual wind turbine foundations. Despite growing interest in the environmental impacts of OWFs, empirical field data on local-scale current dynamics within wind farms remain sparse. This technical report describes the results from a field campaign, which was conducted within the Anholt OWF in the Kattegat over a 9-day period in August 2024.
The expansion of Carbon Capture, Utilization, and Storage (CCUS) highlights the growing need for carbon dioxide (CO2) pipeline transportation. While pure CO2 is non-corrosive, impurities such as H2O and NO2 create a corrosive environment that risks pipeline integrity. This study investigates how H2O and NO2 concentrations, along with temperature, influence corrosion under CO2 pipeline conditions. The investigation was performed in an autoclave setup emulating a linear velocity of 0.96 m/s at 100 bar and temperatures of 5 °C and 25 °C, testing X52 and GR70, and a more corrosion-resistant 9Cr alloy. The results indicated that the presence of NO2 elevated the corrosion rate compared to scenarios without. Low H2O concentration led to a corrosion rate of up to five times higher at 5 °C, compared to at 25 °C, in the presence of NO2. Low to moderate corrosion was observed for the carbon steels without NO2 and with 70 ppmv H2O at both temperatures. Reducing the H2O concentration below 70 ppmv and removing NO2, while SO2 and O2 are present, will only result in low to moderate corrosion in the carbon steel CO2 pipeline. The corrosion rate for X52 and GR70 was 0.065 mm/y and 0.016 mm/y higher or 5 and 3 times greater, respectively, at 5 °C compared to 25 °C. The study concludes that H2O should be maintained below 70 ppmv and NO2 should be eliminated to prevent severe corrosion. Emphasizing the importance of CO2 specification compliance and the need for further research into CO2 compositions that align with the specifications.
This paper examines the stability of a weak island namely Sumbawa-Lombok of Indonesian grid, interconnected with two infeed HVDC links facilitating 2 x 120 MW power transfer from Sumba and Flores Island. Through power flow, short circuit, small signal stability, resonance stability, and transient stability analyses, it is demonstrated that the existing infrastructure fails to support such transfer due to voltage drops, overloading, and stability limitations. Upgrading to 150 kV and its subsequent component resolves the small-signal and transient stability constraint as its grid strength is increasing. The current findings underscore that the primary limitation lies in the grid's infrastructure, not in dynamic or control constraints. The current result establishes the need for strategic grid reinforcements to support HVDC integration in weak systems and sets the stage for future research on optimizing the extent of such reinforcements.
An efficient extreme ship response prediction approach in a given short-term sea state is devised in the paper. The present approach employs an active learning reliability method, named as the active learning Kriging + Markov Chain Monte Carlo (AK-MCMC), to predict the exceedance probability of extreme ship response. Apart from that, the Karhunen-Loève (KL) expansion of stochastic ocean wave is adopted to reduce the number of stochastic variables and to expedite the AK-MCMC computations. Weakly and strongly nonlinear vertical bending moments (VBMs) in a container ship, where the former only accounts for the nonlinearities in the hydrostatic and Froude-Krylov forces, while the latter also accounts for the nonlinearities in the radiation and diffraction forces together with slamming and hydroelastic effects, are studied to demonstrate the efficiency and accuracy of the present approach. The nonlinear strip theory is used for time domain VBM computations. Validation and comparison against the crude Monte Carlo Simulation (MCS) and the First Order Reliability Method (FORM) are made. The present approach demonstrates superior efficiency and accuracy compared to FORM. Moreover, methods for estimating the Mean-out-crossing rate of VBM based on reliability indices derived from the present approach are proposed and are validated against long-time numerical simulations.
This study proposes a novel tower damping system to enhance the structural performance of the NREL 5 MW semi-submersible wind turbine under operational and extreme load conditions. Environmental load data from the Norwegian MET center was analyzed to characterize the loading conditions for floating offshore wind turbines (FOWT). The probability density spectrum of sea state data was employed to identify operational load conditions. At the same time, the Inverse First-Order Reliability Method (IFORM) was used to derive the 50-year extreme sea state. Perform a fully coupled Aero-Hydro-Servo-Elastic simulation of the FOWT dynamic model with a damping system using OrcaFlex software. The results reveal that: Under operational sea states, the turbine tower-top displacement was reduced by 60–70%, and acceleration by 30–40%, enhancing tower-top stability. Under extreme loads, tower-top acceleration was reduced by 5–7%, and displacement by 6–8%. Cumulative damage assessments indicate a reduction in fatigue damage of up to 72%, with the effective fatigue life of the tower base extended by 136%. The proposed damping system significantly reduces vibration under fatigue and extreme load conditions.
The offshore oilfields in the North Sea area are increasingly employed for projects beyond oil production, like carbon capture and storage (CCS). Still, the fossil fuel production from mature fields is significant. It has raised environmental concerns associated with discharging produced waters (PW) and drilling mud into the sea. These discharges, which may be highly saline and contain production chemicals, vary significantly in metals and particulate content. Due to density and release depth, the plume is assumed to sink towards the seafloor. Also, a single oilfield can input up to 7.5 tons of Ba, 675 kg of Fe, and 619 kg of P into the water column through PW. Therefore, this study investigates the impact of these discharges on seafloor sediments around two Danish oilfields, assesses the mobility of metals within these sediments, and evaluates the environmental status. PW samples were collected at the discharge outlets from the platforms. Sediment cores were taken near the two oil platforms and from control sites. Using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and an optimized BCR sequential extraction, we analyzed the composition and distribution of 24 elements in sediment samples. The results revealed significant differences in total extracted concentrations between sediments near the platforms and those from distant locations and stratigraphically older samples, with relevant levels of Br, Ba, and Sn near the platforms (averaged 14, 27, and 0.1 ppb, respectively). Sediment quality indices showed considerable enrichment and geo-accumulation of toxic metals, particularly at one of the platform sites. However, cumulative indices did not display significant pollution anomalies. Therefore, our findings suggest that oil extraction activities may increase the availability of toxic metals in nearby sediments, potentially impacting marine ecosystems.
An issue that ROVs experience during operations is disturbances from the tether, making navigation and control more difficult as real-time measurements are not currently available. This paper proposes the development of an innovative sensor that can measure tether forces in multiple degrees of freedom. These tether forces apply an external disturbance during operation, which is difficult to model and predict. The sensor provides real-time input on the effect the tether has on the ROV, which can be utilized in feed-forward in the control system in combination with a feedback loop. There are 2 proposed designs: a 4 DOF sensor design using a plastic bottle and a 6 DOF version utilizing an aluminum cross with hollowed sections. Both designs use strain gauges to measure and determine the direction and magnitude of the force from the tether.
The sensors are implemented to a modified BlueROV2 using ROS. Station-keeping tests in a harbor and test basin are done for the 4 DOF version to evaluate performance. The sensor shows potential, improving response in heave but worsening it in yaw. It removes and adds oscillations both in frequency and amplitude depending on the orientation of the waves relative to the sensor. Indicating alternative control strategies might be more suitable. The 6 DOF version is not tested on the BlueROV2. In future work, additional development is required to ensure the viability of the tether force sensor as a commercial product.
Due to increased numbers of offshore structures and subsea cables, there is a high demand for underwater maintenance and monitoring. Common options to meet this demand are sonar mapping and imaging. Sonar mapping provides a reliable way for object detection with a high penetration depth, but it is not suitable for tasks that require a detailed insight into the material composition and color of the object. Imaging can provide in-depth, comprehensive information on material properties and external features. This makes it reasonable to investigate its use for object segmentation. Hyperspectral imaging is a subset of imaging which proved to be more effective for airborne object segmentation compared to RGB imaging. This stems from the fact that hyperspectral imaging contains a higher number of spectral bands, justifying the investigation of its applicability in underwater environments. However, underwater imaging faces major challenges such as a variable data quality which is strongly affected by water turbidity, color distortion and a narrow wavelength transmission window. Most of the prior studies conducted on underwater object segmentation relied on RGB images, such as the work carried out by AAU Energy on object segmentation relying on synthetic data [1]. The applicability of hyperspectral reliant object segmentation underwater is yet to be conclusively defined, however, the promising results obtained in airborne conditions are an encouraging prospect. The contribution of this paper is to investigate the applicability of hyperspectral data for underwater object segmentation. In particular, a segmentation algorithm, evaluated in an artificial environment, was researched.