Autonomous unmanned underwater vehicles (UUVs) play a vital role in diverse underwater operations; localization is of great interest for UUVs mirroring the trend seen in self-driving surface and aerial vehicles. Unlike their land and aerial counterparts, underwater environments lack reliable Global Navigation Satellite Systems (GNSS) due to radio wave attenuation in water. Hence, alternative localization methods are imperative for both navigation and operational purposes. This study thoroughly reviews sensor technologies for underwater localization, including sonar, Doppler velocity log, cameras, and more. Different operations necessitate distinct localization accuracies and vehicle and sensor choices. Environmental factors, such as turbidity, waves, and sound disturbances, impact sensor performance. Conclusions are given on the coincidence between operational requirements and sensor specifications, with special attention to the open concerns. These considerations include aspects such as the line of sight for acoustic positioning systems and the requirement for a feature-rich environment for visual sensors. Lastly, a prediction for the future of underwater localization is given, where the tendencies indicate lower costs for sensors, making operation-specific vehicles more attractive, which aligns with an increased demand for cost-efficient autonomous offshore operations.
The DNV Nordic Maritime Universities Workshop is organized as a collaboration between DNV and universities in the Nordic region with a maritime related education or research line. The workshop covers all research topics related to naval architecture, maritime engineering and maritime transport, including safety, energy efficiency and environmental performance, environmental pressures, new technologies and digitalization. The 25th Nordic Maritime Universities Workshop was held on 30-31 January 2025 at the Technical University of Denmark (DTU), Lyngby Campus. The workshop has been organized and hosted by the Maritime Group at the Department of Civil and Mechanical Engineering (DTU Construct). In total we received 77 abstracts from 7 countries. This includes 23 abstracts from Denmark, 23 from Sweden, 16 from Norway, 10 from Germany, 3 from Finland, 1 from The Netherlands, and 1 from Poland. The presentation of the abstracts and the talks is carried out over two days of the workshop and in 10 sessions, distributed over 7 topics:
• Maritime Safety & Risk Reduction (17 talks)
• Structures & Ship Design (8 talks)
• Numerical Methods & Marine Hydrodynamics (14 talks)
• Ship Operations & Navigation (14 talks)
• Autonomous Shipping & Digitalization (8 talks)
• Alternative Marine Fuels (8 talks)
• Wind Assisted & Alternative Propulsion (8 talks)
This year a special issue has been initiated in International Shipbuilding Progress to commemorate the 25th Nordic Maritime Universities Workshop. All abstract presenters have been invited to submit a full paper, to be considered for publication in this journal after a peer-review process. This compendium includes the workshop program, the session details and the 77 abstracts arranged in alphabetical order.
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.
We present a machine learning model for calculation of wave added resistance. The model training is performed using a large set of pre-calculated added resistance curves covering a broad range of ship hulls and operational conditions, i.e. forward speed, draft and relative wave heading. The underlying hydrodynamic model is the classical strip-theory where the wave added resistance is computed according to a modified version of Salvesen’s formulation. It is concluded that the developed data-driven model is able to produce a non-linear mapping between a set of operational conditions as well as the ship’s main particulars to the wave added resistance coefficient.
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.
This study presents a detailed quantification of how flow orientation affects mass transfer and frictional resistance in periodically confined channels, offering novel insights into the physical similarity relations governing these phenomena. We constitute that the Sherwood number and friction factor adhere to universal scaling laws of the form Sh = A1+B sin(2α) Re1 2 and f = A1+B sin(2α) Re−1 2 , where α depicts the orientation of the periodically confined channel. It is found that the flow orientation and the cross flow velocity independently affect both, the Sherwood number and the friction factor. A key contribution of this work is the explicit characterization of the flow orientation: a 45° rotation of the flow relative to the spacer structure increases the Sherwood number by nearly 25%, while the friction factor rises by approximately 20%. These findings highlight a fundamental trade-off between mass transfer enhancement and flow resistance, suggesting that any process optimization must carefully balance the gains in mixing efficiency against the increased energy dissipation. This study provides a robust framework for further investigations into how periodic geometrical constraints influence transport processes in complex flow systems.
Due to limited access to domain knowledge and domain-relevant benchmark data, the Container Stowage Planning Problem (CSPP) is notably under-researched. In particular, previous models of the CSPP have lacked two key aspects of the problem: lashing forces and paired block stowage. The former may reduce vessel capacity by up to 10%, and the latter is NP-hard. The Representative CSPP (RCSPP), which captures all critical aspects of the problem is formulated. The presented RCSPP incorporates overlooked constraints such as paired block stowage and lashing, along with an innovative method for estimating lashing forces, all while maintaining simplicity. A heuristic method, STOW, has been developed to identify solutions for the RCSPP using a specially designed benchmark suite based on real-world scenarios. STOW algorithm is an advanced search heuristic employing a diverse range of solution modification strategies, each tailored to address specific aspects of stowage optimization. Feasible solutions were successfully identified for all instances within the benchmark suite. Our initial findings emphasize the importance of accurately modeling lashing forces and employing paired block stowage. Results show that removing the lashing constraint can increase the number of containers stowed by over 7% on average, while disabling paired block stowage can result in nearly a 5% increase.
A two-dimensional (2D) Reynolds-averaged Navier–Stokes (RANS) equations solver with k–ω turbulence closure is developed, employing immersed boundary (IB) technique on Cartesian grids. Generalized wall functions are introduced to enhance computational efficiency for problems with high Reynolds numbers. To address existing challenges in applying wall functions within IB methods, a novel, effective and easy-to-implement strategy is proposed. Another distinguishing feature of this turbulent-flow solver is that it employs the highly accurate immersed-boundary generalized harmonic polynomial cell (IB-GHPC) method to solve the Poisson equation for fluid pressure. The new solver is firstly validated by simulating channel flows on both hydraulically smooth and rough walls, achieving excellent agreement with benchmark experimental and numerical studies for various flow parameters including velocity, turbulent kinetic energy and shear stress. For channel flow simulations, our implementation of generalized wall functions using the proposed strategy results in a remarkable reduction of grid nodes by over 80%. Moreover, the solver is applied to simulate flow around both smooth and rough cylinders, producing promising results for drag, lift, and pressure coefficients. Our analysis demonstrates a robust performance of the developed solver in modeling turbulent flows based on Cartesian grids, offering a substantial improvement in computational efficiency for tackling problems involving large Reynolds numbers.
We consider the Tramp Ship Routing and Scheduling Problem (TSRSP) in which we plan routes for a fleet of tramp shipping vessels operating on a combined contract and spot market. Earlier research has been fragmented due to variations in the side constraints studied. Hence we present the first unified model that can handle speed optimization, chartering costs, bunker planning, and hull cleaning. The model is solved by column generation, where the columns represent the possible routes of a vessel, while the master problem keeps track of the binding constraints. The pricing problem is solved efficiently using a time–space graph and several dominance rules. Real-life instances with up to 40 vessels, 35 geographic regions, and four months planning horizon can be solved to optimality in less than half an hour. The optimized routes increase earnings by 7% compared to historical schedules. Furthermore, policy-makers can use the model as a simulation of a rational agent behavior.