Due to environmental and economic issues as well as the high performance of marine vessels, efficient energy using has been becoming more demanding. Also, in order to have a zero-emission ship, the utilization of a fuel cell combined with energy storage such as batteries gets more and more attention. In this work, a zero-emission hybrid energy system, including fuel cells, batteries, and cold-ironing, is employed to have an environmentally friendly vessel, and to create condition in which ship operates with high performance, both energy management and components sizing of fuel cells and batteries using real data of ferry boat and intelligent optimization method are done simultaneously. In addition, all constraints related to energy management and component sizing with the topography of the boat and electric power sources are represented and analyzed thoroughly. Ultimately, hourly energy management and component sizing for one specific day are considered in this work, and to optimize this problem, the Improved Sine Cosine Algorithm (ISCA) is utilized. According to obtained results, the proposed energy management and component sizing result in the high-performance ship which could be utilized in the marine industry.
This paper presents a study focused on wave spectrum estimation in practical scenarios where multiple ships operate in the same geographical area, potentially forming a network of wave recorders. A novel methodology is proposed to improve the accuracy and precision of the wave spectrum estimates, by combining sea state estimation methods and techniques for tuning the wave-to-motion transfer functions. The framework of the wave buoy analogy is used to derive estimates for each ship through the use of measured ship motion data and available initial estimates of transfer functions. Simultaneously, the wave-to-motion transfer functions of the individual ship are tuned by utilizing a weighted version of the wave data inferred on board the other ships in the network. The overall architecture of the procedure is modular, in the sense that various approaches may be implemented for obtaining sea state estimates and tuned transfer functions. The methodology is demonstrated through two case studies, one based on simulated vessel responses, and the other using model test data of ship motions in a wave tank. Both case studies consider a network of three ships in long-crested waves equipped with a dynamic positioning system. It is shown that the procedure provides good wave spectrum estimates, and leads to reduced uncertainty in the estimates via tuning of the vessel transfer functions.
Increasing developments in the offshore energy sector have led to demand for robotics use in inspection, maintenance, and repair maintenance tasks, particularly for the service life extension of structures. These robots experience slippage due to varying surface conditions caused by environmental factors and marine growth, leading to inconsistent traction forces and potential mission failures in single-drive systems. This paper explores control strategies and mechanical configurations both in simulation and on the physical industrial robot to mitigate slippage in offshore robotic operations, improving reliability and reducing costs. This study examines mechanical and control modifications such as multi-wheel drive (MWD), PID velocity control, and a feedback-linearized slip control system with an individual wheel disturbance observer to detect surface variations. The results indicate that a 3 WD setup with slip control handles the widest range of conditions but suffers from high control effort due to chattering effects. The simulations show potential for slip control; practically, challenges arise from low sampling rates compared to traction changes. In real-world conditions, a PID-controlled MWD system, combined with increased normal force, achieves better traction and stability. The findings highlight the need for further investigation into the mechanical design and sensor feedback, with the refinement of slip control strategies and observer design for the offshore environment.
Until now, wave-energy developers have focused on designing large machines for utility-scale electricity generation. While many concepts with good capture performance have been devised, significant commercial success has yet to be achieved in this market. Smaller wave energy converters (WECs) for specialist uses have received less attention. Emerging applications for these machines include powering sensors for ocean monitoring and providing energy for recharging maritime autonomous vehicles. Small reliable floating WECs can provide both the low levels of power required for these applications, and a surface platform for satellite
communications. Here, the key idea is to reduce costs and increase human safety by deploying small WECs to perform tasks that would otherwise require a ship. Developing small WECs for specialist uses provides a fast route to market, thereby creating a viable financial and technical base for the development of larger devices for applications where more power is required. This paper reports early results of time- and frequency-domain simulations of a compact WEC designed for monitoring the ocean environment.
The profile of small-scale fisheries has been raised through a dedicated target within the United Nations Sustainable Development Goals (SDG14b) that calls for the provision of 'access of small-scale artisanal fishermen to marine resources and markets'. By focusing on access to fisheries resources in the context of the European Union, in this article we demonstrate that the potential for small-scale fishing sectors to benefit from fishing opportunities remains low due to different mechanisms at play including legislative gaps in the Common Fisheries Policy, and long-existing local structures somewhat favoring the status quo of distributive injustice. Consequently, those without access to capital and authority are faced by marginalizing allocation systems, impacting the overall resilience of fishing communities. Achieving SDG14b requires an overhaul in the promulgation of policies emanating from the present nested governance systems.
Integrated community energy systems are an emerging concept for increasing the self-sufficiency and efficiency of local multi-energy systems. This idea can be conceptualized for the smart island energy systems due to their geographical and socioeconomic context, providing several benefits through this transformation. In this study, the energy system of the Ballen marina—located on the medium-sized Danish island of Samsø— is investigated. Particular consideration is given to the integration of PV, BESS, and—in the future—flexible loads. For this purpose, the BESS is modelled, incorporating the battery degradation process. The possibilities to improve energy utilization and maximize self-consumption from the marina's PV units are identified and evaluated, demonstrating a substantial enhancement of the local system operation.
This paper presents the design and development of a conceptual prototype of an autonomous self-driven inline inspection robot, called Smart-Spider. The primary objective is to use this type of robot for offshore oil and gas pipeline inspection, especially for those pipelines where the conventional intelligent pigging systems could not or be difficult to be deployed. The Smart-Spider, which is real-time controlled by its own on-board MCU core and power supplied by a hugged-up battery, is expected to execute pipeline inspection in an autonomous manner. A flexible mechanism structure is applied to realize the spider's flexibility to adapt to different diameters of pipelines as well as to handle some irregular situations, such as to pass through an obstructed areas or to maneuver at a corner or junction. This adaptation is automatically controlled by the MCU controller based on pressure sensors' feedback. The equipped devices, such as the selected motors and battery package, as well as the human-and-machine interface are also discussed in detail. Some preliminary laboratory testing results illustrated the feasibility and cost-effectiveness of this design and development in a very promising manner.
Each year maritime accidents occur at sea causing human casualties. Training facilities serve to reduce the risk of human error by allowing maritime teams to train safety procedures in cooperative real-size immersive simulators. However, they are expensive and only few maritime professionals have access to such simulators. Virtual Reality (VR) can provide a digital all-immersive learning environment at a reduced cost allowing for increased access. However, a key ingredient of what makes all-immersive physical simulators effective is that they allow for multiple participants to engage in cooperative social interaction. Social interaction which allows trainees to develop skills and competencies in navigating situational awareness essential for safety training. Social interaction requires social fidelity. Moving from physical simulators into digital simulators based upon VR technology thus challenges us as HCI researchers to figure out how to design social fidelity into immersive training simulators. We explore social fidelity theoretically and technically by combining core conceptual work from CSCW research to the design experimentation of social fidelity for maritime safety training. We argue that designing for social fidelity in VR simulators requires designers to contextualize the VR experience in location, artifacts, and actors structured through dependencies in work allowing trainees to perform situational awareness, coordination, and communication which are all features of social fidelity. Further, we identify the risk of breaking the social fidelity immersion related to the intent and social state of the participants entering the simulation. Finally, we suggest that future designs of social fidelity should consider not only trainees in the design, but also the social relations created by the instructors’ guidance as part of the social fidelity immersion.
Purpose This study aims to explore how operational resilience can be achieved within supply ecosystems in the delicate yet harsh natural environments of the Arctic. Design/methodology/approach An in-depth, multiple qualitative case study of offshore supply operations in Arctic oil and gas field projects is conducted. Data from semi-structured interviews, personal observations and archival materials are analyzed through institutional work and logics approaches. Findings The findings suggest that achieving social-ecological resilience depends on the interaction between social and natural (irreversible) systems, which are shaped and influenced by various institutional dynamics. Different resilience solutions were detected. Research limitations/implications This study develops a comprehensive understanding of how social-ecological resilience emerges in supply ecosystems through institutional dynamics. The study's empirical basis is limited to offshore oil and gas projects in the Arctic. However, due to anticipated future growth of Arctic economic activities, other types of supply ecosystems may benefit from the study's results.Originality/value This research contributes with empirical knowledge about how social-ecological resilience is created through institutional interaction within supply ecosystems to prevent disruptions of both social and ecological ecosystems under the harsh natural conditions of the Arctic.
High-fidelity models become more and more used in the wave energy sector. They offer a fully nonlinear simulation tool that in theory should encompass all linear and nonlinear forces acting on a wave energy converter (WEC). Studies using high-fidelity models are usually focusing on validation of the model. However, a validated model does not necessarily provide reliable solutions. Solution verification is the methodology to estimate the numerical uncertainties related to a simulation. In this work we test four different approaches: the classical grid convergence index (GCI); a least-squares version (LS-GCI); a simplified version of the least-square method (SLS-GCI); and the ITTC recommended practice. The LS-GCI requires four or more solutions whereas the other three methods only need three solutions. We apply these methods to four different high-fidelity models for the case of a heaving sphere. We evaluate the numerical uncertainties for two parameters in the time domain and two parameters in the frequency domain. It was found that the GCI and ITTC were hard to use on the frequency domain parameters as they require monotonic convergence which sometimes does not happen due to the differences in the solutions being very small. The SLS-GCI performed almost as well as the SL-GCI method and will be further investigated.