Sensing data from vessel operations are of great importance in reflecting operational performance and facilitating proper decision-making. In this paper, statistical analyses of vessel operational data are first conducted to compare manual noon reports and autolog data from sensors. Then, new indicators to identify data aberrations are proposed, which are the errors between the reported values from operational data and the expected values of different parameters based on baseline models and relevant sailing conditions. A method to detect aberrations based on the new indicators in terms of the reported power is then investigated, as there are two independent measured power values. In this method, a sliding window that moves forward along time is implemented, and the coefficient of variation (CV) is calculated for comparison. Case studies are carried out to detect aberrations in autolog and noon data from a commercial vessel using the new indicator. An analysis to explore the source of the deviation is also conducted, aiming to find the most reliable value in operations. The method is shown to be effective for practical use in detecting aberrations, having been initially tested on both autolog and noon report from four different commercial vessels in 14 vessel years. Approximately one triggered period per vessel per year with a conclusive deviation source is diagnosed by the proposed method. The investigation of this research will facilitate a better evaluation of operational performance, which is beneficial to both the vessel operators and crew.
Accurate estimation of the roll damping of a ship is important for reliable prediction of roll motions. In particular, characterization and prediction of parametric roll incidence and other events associated with large roll angles require detailed knowledge about the damping terms. In the present paper, an approach to identify the stability parameters, i.e. linear and nonlinear roll damping coefficients in conjunction with the natural roll frequency, based on onboard response measurements is proposed. The method starts by estimating the encountered wave profile using wave-induced response measurements other than roll, e.g., heave, pitch, and sway motions. The estimated wave profile is then fed into a physic-based nonlinear roll estimator, and then the stability parameters that best reproduce the measured roll motion are identified by optimization. In turn, in-situ identification can be achieved while simultaneously collecting the response measurements. A numerical investigation using synthetic response measurements is made first, then follows an experimental investigation using a scaled model ship. Good results have been obtained in both long-crested and short-crested irregular waves.
The hybrid combination of hydrogen fuel cells (FCs) and batteries has emerged as a promising solution for efficient and eco-friendly power supply in maritime applications. Yet, ensuring high-quality and cost-effective energy supply presents challenges. Addressing these goals requires effective coordination among multiple FC stacks, batteries, and cold-ironing. Although there has been previous work focusing it, the unique maritime load characteristics, variable cruise plans, and diverse fuel cell system architectures introduce additional complexities and therefore worth to be further studied. Motivated by it, a two-layer energy management system (EMS) is presented in this paper to enhance shipping fuel efficiency. The first layer of the EMS, executed offline, optimizes day-ahead power generation plans based on the vessel's next-day cruises. To further enhance the EMS's effectiveness in dynamic real-time situations, the second layer, conducted online, dynamically adjusts power splitting decisions based on the output from the first layer and instantaneous load information. This dual-layer approach optimally exploits the maritime environment and the fuel cell features. The presented method provides valuable utility in the development of control strategies for hybrid powertrains, thereby enabling the optimization of power generation plans and dynamic adjustment of power splitting decisions in response to load variations. Through comprehensive case studies, the effectiveness of the proposed EMS is evaluated, thereby showcasing its ability to improve system performance, enhance fuel efficiency (potential fuel savings of up to 28%), and support sustainable maritime operations.
This study addresses a critical gap in environmental assessments by focusing on petrochemical port operations, an area traditionally overlooked in life cycle assessments (LCAs) of material supply chains. This study investigates various methods of loading for 22 petrochemical products i.e., gas, liquid, container, tanker, and bulk loading; at the biggest petrochemical port in the world situated in the Persian Gulf with a loading capacity of 35 MMt/yr. Twelve scenarios were developed to enhance environmental efficiency based on hotspots defined in LCAs of port loading operations of petrochemicals in their present state. Scenarios 1 through 5 consider electricity savings of 2%–10%, scenarios 6 through 10 consider renewable photovoltaic energy mix of 10%–50%, and scenarios 11 and 12 consider no flaring and rejection of ash waste from ships.
To prioritize these scenarios based on environmental efficiency gains, a comprehensive LCA-GRM hybrid model has been introduced. This integrated model combines life cycle assessment and gray relational modeling, providing a robust framework for evaluating and ranking the scenarios. The Best Worst Method (BWM) is implemented for weighing multiple environmental criteria, contributing to informed decision-making.
The findings underscore the substantial impact of electricity consumption and gas flaring in petrochemical port operations, prompting the identification of the 'no flaring' scenario (S11) as the most preferred option. Implementing this scenario could lead to significant reductions in climate change impacts (22.14%), ozone formation and human health impacts (16.73%), and photochemical oxidant formation (15.98%).
The study's significance lies in emphasizing the environmental implications of port operations and urging policymakers to integrate port impacts into broader supply chain assessments. We advocate for targeted strategies to enhance electricity efficiency and reduce gas flaring in petrochemical ports, aligning with global sustainability goals. The Comprehensive LCA-GRM hybrid approach offers valuable insights for decision-makers involved in the global transportation of goods through ports.
Power-to-X plants can generate renewable power and convert it into hydrogen or more advanced fuels for hard-to-abate sectors like the maritime industry. Using the Bornholm Energy Island in Denmark as a study case, this study investigates the off-grid production e-bio-fuel as marine fuels. It proposes a production pathway and an analysis method of the oil with a comparison with e-methanol. Production costs, optimal operations and system sizing are derived using an open-source techno-economic linear programming model. The renewable power source considered is a combination of solar photovoltaic and off-shore wind power. Both AEC and SOEC electrolyzer technologies are assessed for hydrogen production. The bio-fuel is produced by slow pyrolysis of straw pellet followed by an upgrading process: hydrodeoxygenation combined with decarboxylation. Due to its novelty, the techno-economic parameters of the upgraded pyrolyzed oil are derived experimentally. Experimental results highlight that the upgrading reaction conditions of 350 °C for 2h with one step of 1h at 150 °C, under 200 bars could effectively provide a fuel with a sufficient quality to meet maritime fuel specifications. It requires a supply of 0.014 kg H2/kgbiomass. Modeling results shows that a small scale plant constrained by the local availability of and biomass producing 71.5 GWh of fuel per year (13.3 kton of methanol or 7.9 kton of bio-fuel), reaches production costs of 54.2 €2019/GJmethanol and 19.3 €2019/GJbio-fuel. In a large scale facility, ten times larger, the production costs are reduced to 44.7 €2019/GJmethanol and 18.9 €2019/GJbio-fuel (scaling effects for the methanol pathway). Results show that, when sustainable biomass is available in sufficient quantities, upgraded pyrolysis oil is the cheapest option and the less carbon intensive (especially thanks to the biochar co-product). The pyrolysis unit represents the main costs but co-products revenues such as district heat sale and biochar as a credit could decrease the costs by a factor three.
The cold ironing system is gaining interest as a promising approach to reduce emissions from ship transportation at ports, enabling further reductions with clean energy sources coordination. While cold ironing has predominantly been applied to long-staying vessels like cruise ships and containers, feasibility studies for short-berthing ships such as ferries are limited. However, the growing demand for short-distance logistics and passenger transfers highlights the need to tackle emissions issues from ferry transportation. Incorporating electrification technology together with integrated energy management systems can significantly reduce emissions from ferry operations. Accordingly, this paper proposes a cooperative cold ironing system integrated with clean energy sources for ferry terminals. A two-stage energy management strategy combining sizing and scheduling optimization is employed to reduce the port's emissions while minimizing system and operational costs. The proposed system configuration, determined through the sizing method, yields the lowest net present cost of $9.04 M. The applied energy management strategy managed to reduce operational costs by up to 63.402 %, while significantly decreasing emissions from both shipside and shoreside operations. From the shipside, emissions reductions of 38.44 % for CO2, 97.7 % for NOX, 96.69 % for SO2, and 92.1 % for PM were achieved. From the shoreside, the approach led to a 28 % reduction across all emission types. Thus, implementing cold ironing powered by clean energy sources is a viable solution for reducing emissions generated by ferry operations. The proposed energy management approach enables emissions reduction and delivering cost-effectiveness at ferry terminals.
Unmanned surface vehicles (USVs) are increasingly appealing for gathering metocean data, including directional sea spectra. This paper presents new developments towards estimating the response amplitude operators (RAOs) of surface vehicles equipped with inertial sensors. The novel approach undertakes the data-driven estimation of vehicle models of the wave-induced heave, roll, and pitch motion dynamics, as required to perform subsequent seakeeping computations. Specifically, a genetic algorithm executes the calibration of available closed-form RAOs for a simplified geometry. The algorithm makes a population of model-fitting parameters evolve towards minimising discrepancies between the predicted and measured response spectra in stationary operational conditions. Trust in the model is eventually increased by screening and merging the best-fitting solutions. Resulting response predictions using high-resolution spectral wave data for the AutoNaut USV demonstrate satisfactory accuracy and robustness in heave and pitch but a worse fidelity in roll, thereby motivating follow-up studies to improve the estimation of roll RAOs.
An adaptive machine learning framework is established for an implicit determination of the performance degradation of a ship due to marine growth, i.e., biofouling. The framework is applied in a case study considering telemetry data of a cruise ship operating predominantly in the Caribbean Sea. The dataset encompasses seven years including three dry-docking intervals and several in-water cleaning events. The COVID-19 period receives special focus due to the drastic change in the operational profile. A main outcome of the study is a comparison of the derived performance estimate to the corresponding results of the industry standard ISO 19030. Additional aspects of the present study include the use of special regularization techniques for incremental machine learning and the increase of transparency through the implementation of prediction intervals indicating model uncertainty. Overall, it is found that the developed machine learning framework shows good agreement with the industry standard underlining its plausibility.
The BBNJ Agreement will affect legal frameworks for the conservation of marine biological diversity in various regions of the world ocean and the marine Arctic is no exception. As biological diversity in the marine Arctic is particularly vulnerable, the implications of the BBNJ Agreement for the conservation of biological diversity in the marine Arctic deserves serious consideration. Of particular note is the procedure for an environmental impact assessment (EIA). Given that damage to the environment may be irreversible, it is a prerequisite to conduct an EIA before authorizing planned activities, with a view to preventing environmental harm. An EIA constitutes a crucial element in the conservation of the marine environment, including biological diversity. Hence, this article examines the potential implications of the procedure for an EIA as set out under the BBNJ Agreement for the conservation of biological diversity in the marine Arctic beyond national jurisdiction.
This study examines how the work of the International Law Commission (ILC) has contributed to the ‘progressive development’ of general international law relevant to regulating rescue and disembarkation of refugees and migrants found at sea. It explores the ILC’s texts on interpretation and implementation of international obligations, state responsibility, fragmentation and harmonization of international law, and the status of certain principles of general international law, including jus cogens general principles of law and the principle of good faith, which present legal parameters for regulation of maritime search and rescue operations. In conducting doctrinal examinations of international law and gathering evidence of the practice of States and other relevant actors, the ILC contributes by analysing, clarifying, and systemising important topics of general international law. However, state implementation frequently falls short of the legal interpretations of the ILC, particularly as they relate to respect for and protection of human rights at sea. Therefore, while the ILC needs new strategies to directly connect with States and international organisations, it remains reliant on the mutual following of national and international courts and tribunals, and its mutual contribution in scholarship.