Physical model tests are often conducted during the design process of coastal structures. The wave climate in such tests often includes short-crested nonlinear waves. The structural response is related to the incident waves measured in front of the structure. Existing methods for separation of incident and reflected short-crested waves are based on linear wave theory. For analysis of nonlinear waves, the existing methods are limited to separation of nonlinear long-crested waves. For short-crested waves, the only options so far have been to use estimates without the structure in place. The present paper thus presents a novel method for directional analysis of nonlinear short-crested waves: Non-Linear Single-summation Oblique Reflection Separation (NL-SORS). The method is validated on numerical model data, as for such data, the target is well defined as simulations may be performed with fully absorbing boundaries. Second- and third-order wave theory is used to demonstrate that small errors on the celerity of nonlinear components in the mathematical model of the surface elevation can be obtained if a double narrow-banded directional spectrum is assumed, ie the primary frequency and the directional spreading function must be narrow banded. As the increasing nonlinearity of the waves often arise from waves shoaling on a sloping foreshore, the directional spreading of the waves will decrease due to refraction, and a broad directional spreading function will thus not be experienced in highly nonlinear conditions. The new NL-SORS method is shown to successfully decompose nonlinear short-crested wave fields and estimate the directional spectrum thereof.
This paper presents the methods developed and key findings of the IWEC project performed by Ocean Harvesting Technologies AB (OHT). It aimed to reduce the levelized cost of energy (LCoE) of OHT’s wave energy converter InfinityWEC, by analysing how different key parameters impact cost and annual output using a model of a 100-MW array installation. Component-level cost functions were developed and mapped to key parameters and constraints of the system. A large number of system configurations were then evaluated with a numerically efficient 3 degree-of-freedom (DoF) nonlinear radiationdiffraction model in WEC-Sim along with OHT’s sea statetuned polynomial reactive control (PRC). The most promising configurations were identified and investigated in more detail. The configuration with the best LCoE were finally identified and analysed further, including estimation of the effect of changing the PRC to model predictive control, which resulted in 17-34% higher annual output and 12-23% lower LCoE. The final LCoE was found to be 93-162 EUR MWh at 100 MW installed capacity. An important finding from the study is that using simplified metrics such as CAPEX/ton was found to be irrelevant. Numerical wave tank testing, high-fidelity computational fluid dynamics (CFD), were used to tune the viscous drag of the 3 DoF WEC-Sim model. Applying verification and validation (V&V) techniques the CFD simulations showed a relatively large numerical uncertainty, but the average power and the motion responses were found to be sufficiently accurate.
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.
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.
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.
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.
For the assessment of experimental measurements of focused wave groups impacting a surface-piecing fixed structure, we present a new Fully Nonlinear Potential Flow (FNPF) model for simulation of unsteady water waves. The FNPF model is discretized in three spatial dimensions (3D) using high-order prismatic - possibly curvilinear - elements using a spectral element method (SEM) that has support for adaptive unstructured meshes. This SEM-FNPF model is based on an Eulerian formulation and deviates from past works in that a direct discretization of the Laplace problem is used making it straightforward to handle accurately floating structural bodies of arbitrary shape. Our objectives are; i) present detail of a new SEM modelling developments and ii) to consider its application to address a wave-body interaction problem for nonlinear design waves and their interaction with a model-scale fixed Floating Production, Storage and Offloading vessel (FPSO). We first reproduce experimental measurements for focused design waves that represent a probably extreme wave event for a sea state represented by a wave spectrum and seek to reproduce these measurements in a numerical wave tank. The validated input signal based on measurements is then generated in a NWT setup that includes the FPSO and differences in the signal caused by nonlinear diffraction is reported.
A 3D fully nonlinear potential flow (FNPF) model based on an Eulerian formulation is presented. The model is discretized using high-order prismatic – possibly curvi-linear – elements using a spectral element method (SEM) that has support for adaptive unstructured meshes. The paper presents details of the FNPF-SEM development and the model is illustrated to exhibit exponential convergence. The model is then applied to the case of focused waves impacting on a surface-piecing fixed FPSO-like structure. Good agreement was found between numerical and experimental wave elevations and pressures.
We present a high-order nodal spectral element method for the two-dimensional simulation of nonlinear water waves. The model is based on the mixed Eulerian–Lagrangian (MEL) method. Wave interaction with fixed truncated structures is handled using unstructured meshes consisting of high-order iso-parametric quadrilateral/triangular elements to represent the body surfaces as well as the free surface elevation. A numerical eigenvalue analysis highlights that using a thin top layer of quadrilateral elements circumvents the general instability problem associated with the use of asymmetric mesh topology.We demonstrate how to obtain a robust MEL scheme for highly nonlinear waves using an efficient combination of (i) global L2 projection without quadrature errors, (ii) mild modal filtering and (iii) a combination of local and global re-meshing techniques. Numerical experiments for strongly nonlinear waves are presented. The experiments demonstrate that the spectral element model provides excellent accuracy in prediction of nonlinear and dispersive wave propagation. The model is also shown to accurately capture the interaction between solitary waves and fixed submerged and surface-piercing bodies. The wave motion and the wave-induced loads compare well to experimental and computational results from the literature.
We present an arbitrary-order spectral element method for general-purpose simulation of non-overturning water waves, described by fully nonlinear potential theory. The method can be viewed as a high-order extension of the classical finite element method proposed by Cai et al. (1998)[5], although the numerical implementation differs greatly. Features of the proposed spectral element method include: nodal Lagrange basis functions, a general quadrature-free approach and gradient recovery using global L2projections. The quartic nonlinear terms present in the Zakharov form of the free surface conditions can cause severe aliasing problems and consequently numerical instability for marginally resolved or very steep waves. We show how the scheme can be stabilised through a combination of over-integration of the Galerkin projections and a mild spectral filtering on a per element basis. This effectively removes any aliasing driven instabilities while retaining the high-order accuracy of the numerical scheme. The additional computational cost of the over-integration is found insignificant compared to the cost of solving the Laplace problem. The model is applied to several benchmark cases in two dimensions. The results confirm the high order accuracy of the model (exponential convergence), and demonstrate the potential for accuracy and speedup. The results of numerical experiments are in excellent agreement with both analytical and experimental results for strongly nonlinear and irregular dispersive wave propagation. The benefit of using a high-order – possibly adapted – spatial discretisation for accurate water wave propagation over long times and distances is particularly attractive for marine hydrodynamics applications.