Driven by regulatory mandates, International Maritime Organization (IMO) decarbonization targets, market pressure, and evolving societal expectations, the maritime industry is undergoing a fundamental transition towards full decarbonization. This shift has renewed interest in Wind Propulsion Systems (WPSs) as viable propulsion alternatives, reflected in their increasing adoption. However, widespread implementation remains challenging. Each WPS installation design excels under specific conditions, which makes selecting the most cost-effective WPS installation complex. Failure to optimize design and placement can lead to suboptimal fuel savings or unprofitable deployments, limiting industry confidence, and slowing adoption.
To address these challenges, this PhD Thesis presents a novel modelling framework to optimize WPS installation designs by evaluating their cost-benefit trade-offs. The framework identifies the optimal WPS class, design, positioning, and arrangement to maximize fuel savings and emission reductions while minimizing investment costs, tailored to an operator’s specific profile. The study addresses three main objectives: (1) determining the most cost-effective WPS installation design, (2) enhancing industry understanding of WPS performance, and (3) supporting informed decision-making for shipowners and operators.
The results demonstrate that there is no on-size-fits-all WPS solution; instead, each optimal configuration requires a use-case-specific evaluation, accounting for factors such as ship type, route, wind conditions, emissions reduction targets, and operational constraints. However, general trends emerge. Higher emissions reduction ambitions – requiring larger WPS installations — favor high lift-to-drag ratio and lightweight technologies for costeffectiveness. In contrast, low lift-to-drag ratio systems are more sensitive to deck placement and wind conditions due to the resulting hydrodynamic penalties to counteract aerodynamic
forces, though these effects become less significant for lower emissions reduction targets. Installation viability is further constrained by factors such as maximum air draft and cargo space loss due to weight penalties, which may significantly impact economic feasibility.
Optimization of WPS installation design is found to be critical for maximizing economic returns and ensuring fair comparisons across different WPS classes, as each class has unique performance characteristics. The most cost-effective configurations generally involve max imizing unit spacing to reduce aerodynamic interactions and placing units near the hydrodynamic center of lateral resistance to minimize added resistance penalties. Suboptimal designs can extend payback periods by over 150% compared to optimized configurations. Additionally, while WPS-equipped vessels require higher upfront investment, they demonstrate rapid payback periods and strong profitability, particularly in favorable operational and economic conditions.
A critical threshold of limited return on investment is identified for retrofit installations, occurring when additional WPS units no longer yield increased fuel and emissions savings. This is due to hydrodynamic penalties required to maintain yaw moment balance, ultimately offsetting the WPS benefits. This also underscores the need for an optimized deployment strategy to maximize savings while minimizing investment costs, preventing unprofitable installations that could foster skepticism and hinder adoption.
The methods and findings presented in this PhD Thesis provide a foundation for unlocking the full potential of wind propulsion systems, supporting a more sustainable, cost-effective, and decarbonized shipping industry.
Coastal communities have ideas and plans on how to redirect the blue economy to
support thriving societies, but how can EU Member States better support bottom-up
transitions?
This is a policy brief included in D5.3 of EmpowerUs.
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.
Automated fish documentation processes are in the near future expected to play an essential role in sustainable fisheries management and for addressing challenges of overfishing. In this paper, we present a novel and publicly available dataset named AutoFish designed for fine-grained fish analysis. The dataset comprises 1,500 images of 454 specimens of visually similar fish placed in various constellations on a white conveyor belt and annotated with instance segmentation masks, IDs, and length measurements. The data was collected in a controlled environment using an RGB camera. The annotation procedure involved manual point annotations, initial segmentation masks proposed by the Segment Anything Model (SAM), and subsequent manual correction of the masks. We establish baseline instance segmentation results using two variations of the Mask2Former architecture, with the best performing model reaching an mAP of 89.15%. Additionally, we present two baseline length estimation methods, the best performing being a custom MobileNetV2-based regression model reaching an MAE of 0.62cm in images with no occlusion and 1.38cm in images with occlusion. Link to project page: https://vap.aau.dk/autofish/.
This chapter examines the development of the law of the sea at the time of the League of Nations with specific focus on the entitlement to the oceans and the use of the oceans. This chapter first addresses the entitlement to and jurisdiction over marine spaces by examining the issue of the territorial sea, the contiguous zone, bays and islands. The chapter then examines the issue of the use of the oceans, focusing on the regulation of fishing and navigational rights in straits. Finally, the chapter will conclude that the era of the League of Nations can be thought to be one in which the traditional paradigm of the law of the sea was being formulated. However, the paradigm was qualified by the absence of an agreement with regard to the breadth of the territorial sea and rules regarding the delimitation of the territorial sea. In this sense, the paradigm in that period remained incomplete. Furthermore, the time was not ripe to establish a global legal framework for the conservation of marine living resources. Overall the law of the sea at the time was characterised by the reconciliation of competing interests of individual states.
This book introduces a novel model to explain how the co-design and co-delivery of ocean science knowledge and solutions is influenced by ocean stakeholders with asymmetric power and resources, policy incentives and ocean conflict, ocean narratives, different knowledge systems, security concerns, principles, formal and informal rules, and communication competencies. Using the International Collaboration in Ocean Science model as a basis, the book advances with three lines of inquiry: ontological security of ocean science participants, the Ocean Decade and human well-being, and strategic narratives about international collaboration in ocean science. Through these, Carolijn van Noort shows the enabling and constraining conditions of co-creating ocean knowledge and solutions. Theoretically novel, the book provides a compelling framework for scholars to study ocean science collaboration.
Underwater radiated noise (URN) from ship propellers has attracted increasing interest in recent years due to its adverse environmental effects on marine life and their communication channels. The environmental concern to reduce shipping noise and the industrial requirements for faster computational tools are driving factors that promote research in the specialized domain of hydroacoustics. This thesis deals with the development of such a computationally efficient numerical tool, which can be used in the prediction of underwater radiated noise in the early design phase of propellers.
The numerical model is developed with two major objectives – versatility in assessing the relative contributions from the major propeller-noise generating mechanisms, and rapidity in prediction of overall noise behaviour. It uses the Farassat-1A solid-FWH formulation of the Ffowcs-Williams- Hawkings equation by defining equivalent acoustic sources on the propeller blade, sheet cavity and tip vortex cavity surfaces. In particular, the application of the solid-FWH formulation to the tip vortex cavity model is the major novelty in this thesis.
The hydrodynamic flow solution is obtained from a potential flow based solver ESPPRO, which includes analytical models of sheet cavitation and tip vortex cavitation. The hydroacoustic numerical model developed within this thesis, DoLPHiN, is a Python-based code that is primarily designed to accept input from ESPPRO; but during the research, the code has also been adapted to read input from the commercial, finite-volume-based Navier-Stokes solver, STAR-CCM+.
The numerical model implementations are verified through analytical case studies for simple geometrical shapes, such as a pulsating sphere and an oscillating cylindrical cavity. The verification study is further extended for propeller geometries by identifying approximate reference solutions in simplified operating conditions. The numerical tool is validated for industrial application through comparison of its noise prediction with model-scale and full-scale noise measurements. Specific characteristics of the propeller noise spectrum are identified in order to evaluate its noise prediction capabilities. The uncertainty factors involved when validating with experimental measurements are also explored in detail. Furthermore, a design study is presented, which shows potential use of the numerical tool in practical propeller design and optimization applications.
Global climate change, which is largely attributed to human activity, is one of the foremost challenges of the 21st century. In recent times, there have been notable alterations in the Earth's climate, resulting in profound impacts on ecosystems and biodiversity. These alterations are caused by greenhouse gas, such as carbon dioxide, methane, and nitrous oxide. Greenhouse gas emissions are caused by practices such as deforestation, industrial operations, and the combustion of fossil fuels in vehicles, vessels, aircraft, and manufacturing facilities. The maritime and aviation industry is currently responsible for approximately 6% of global greenhouse gas emissions. Due to logistical and economic constraints, these industries are heavily reliant on liquid fuels, making direct electrification options unavailable for large parts of these sectors. As a result, these sectors are considered ‘hard to abate’. Understanding the future climate mitigation challenges associated with the maritime and aviation sectors is crucial in shaping effective policy measures, avoiding stranded assets, and preserving the chance to meet Paris Agreement-compatible emission reduction pathways.
This thesis identifies three main challenges and proposes modelling approaches to address them when modelling decarbonization pathways for the aviation and maritime sectors. From these challenges, research gaps have been identified that this PhD thesis aims to fill. Three models have been developed for the thesis: a maritime optimization model, a maritime demand model, and an aviation demand model. The modelling landscape and methodology vary across models, ranging from econometrics and data science to mathematical optimization.
To overcome the challenges and fill in the research gaps, three corresponding modelling approaches have been successfully applied:
1. Developing a holistic decarbonization modelling landscape. This includes life-cycle representations of technology costs and emissions, the upscaling of bottleneck technologies, the availability of sustainable biomass, and consideration of competing demand from other industries, as well as representations of policy levers such as carbon pricing or improvements to fuel efficiency.
2. Developing demand models that interpret the underlying scenario narrative consistently (SSP framework).
3. Improving the representation of technological learning for low-carbon technologies in energy system models.
The findings acquired by applying these three modelling approaches are valuable for energy modellers, climate scientists, and policymakers and offer unique insights into the inherent system dynamics associated with decarbonization of hard-to-abate sectors. Utilizing this modelling landscape reveals that current decarbonization efforts for hard-to-abate sectors are insufficient.
This report includes a broad description of the findings from work package 2 in the EFFORT project and is made as the fulfillment of delivery L2.1 in the project. First an overall description of the Port of Hirtshals together with its infrastructure is given in chapter 1 together with some background aspect for the development of the Port of Hirtshals. In this chapter also the 5 companies who had shown their interest in participation in the project are described in more detail. Based on this as outcome of task 2.1 and described in chapter 2 an overall system architecture is set up for the existing industries at the Port of Hirtshals and next for the future expansion of the port. Based on the overall system architecture an adaptation of the system to the EU SGAM model is performed and explained. Then the overall set up of the data hub is briefly introduced, to see how it is related to the overall energy system set up. The final part documented for task 2.1 is two examples of sequence diagrams for first the processes in Forskerparken and next one which is valid for both the Fish Terminal, Lineage as well as Danish Salmon, since many of their electrical consuming processes here in an overall manner look the same.
In chapter 3 the base scenarios for the existing industries at Port of Hirtshals are set up. This is done based on information and wishes from the industries and the local Distribution System Operator (DSO), which is gained partly by bilateral discussions as well as on a workshop held with all the involved industries present at the same time. The scenarios will be described according to the IEC standard 62559-2, to ensure better utilization of the ideas in other projects, by applying a standard template known in this area.
Finally, in chapter 4 scenarios for the future expected extension of industries and activities at the Port of Hirtshals are set up. This is based on inputs from GPN, HH, NEN as well as Hjørring Municipality, Hirtshals Fjernvarme and from inputs from workshops with the existing industries at the port. Also here the IEC 62559-2 standard will be applied when describing the use cases.
The scenarios set up will later be used for the further development of the data hub, which is to be set up in the project, as well as for the model set up and control perspectives in the later WPs.