Knowledge

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.

Slow steaming is being practised in many sectors of the shipping industry. It is induced principally by depressed shipping markets and/or high fuel prices. In recent years the environmental dimension of slow steaming has also become important, as ship emissions are directly proportional to fuel burned. The purpose of this chapter is to examine the practice of slow steaming from various angles. In that context, a taxonomy of models is presented, some fundamentals are outlined, the main trade-offs are analysed, and some decision models are presented. Some examples are finally presented so as to highlight the main issues that are at play.

This report provides a summary on the prospects for aerial drone applications for the smart inspection and maintenance for maritime and offshore industries. The report's findings are based on respondents' answers to surveys and focuses on when aerial drones will come into smart maintenance operations and their business potential. The report is produced by the PERISCOPE Group at Aarhus University for the PERISCOPE network.

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.

This work extends an existing seakeeping tool (OceanWave3D-seakeeping) to allow for the efficient and accurate evaluation of the hydroelastic response of large flexible ships sailing in waves. OceanWave3D-seakeeping solves the linearized potential flow problem using high-order finite differences on overlapping curvilinear body-fitted grids. Generalized modes are introduced to capture the flexural responses at both zero and non-zero forward speed, but we focus on the zero speed case here. The implementation of the hydroelastic solution is validated against experimental measurements and reference numerical solutions for three test cases. The ship girder is approximated by an Euler–Bernoulli beam, so only elastic bending deformation is considered and sheer effects are neglected. Some controversy has long existed in the literature about the correct form of the linearized hydrostatic stiffness terms for flexible modes, with Newman (1994) and Malenica and Bigot (2020) arriving at different forms. We provide here a complete derivation of both forms (including the gravitational terms) and demonstrate the equivalence of the buoyancy terms for pure elastic motions.

In this study, we employ a hydroelastic analysis to investigate the motion response of large ship hulls, treating them as either Euler–Bernoulli or Timoshenko beams to consider the influence of shear effects. To enhance clarity, we provide a detailed derivation of the equation of motion within the framework of Timoshenko beams. This work solves forward-speed radiation and diffraction problems for flexible bodies, utilizing linearized potential flow theory including generalized modes. Two common base-flow models, the Neumann-Kelvin and double-body base flows, are included in the solver. The solution is numerically implemented in the high-order finite difference and open-source seakeeping solver Oceanwave3D-seakeeping. The numerical implementation involves the discretization of the geometry using overlapping, boundary-fitted grids, which has been validated by three examples involving a barge and two Wigley hulls. The influence of the Doppler shift due to forward speed on the hydroelastic motion response is also discussed. Through the integration of hydroelastic analysis using potential flow theory and advanced numerical techniques, this work contributes to a deeper understanding of the complex interaction between large ship hulls and waves, offering valuable insights for the maritime industry.

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.

Offshore jacket foundations for wind turbine generators are in risk of metal fatigue at the weldedjoints due to the highly dynamic wind and wave loading. The complex multiaxial stresses occurringat the welded joints can be non­proportional and lead to increased fatigue damage as compared toproportional stresses. Furthermore, several random effects influence the response of the offshorestructures and the fatigue lives of the welded joints.

In this thesis, the fatigue response of welded joints in offshore jacket structures is assessed. The influence of non­proportional stress states on the fatigue life has been examined using experimental fatigue data from literature by modelling the published experiments using the finite element method (FEM) and assessing the stress states using the notch stress approach. The results show that a nonzero phase­shift between the governing normal and shear stress at the weld toe leads to increased damages at the weld. An approach for determining the non­proportionality penalty factors for obtaining correct fatigue life estimations has been proposed.

To quantify the level of non­proportionality in the stress states at welds a new quantification approach has been developed based on the principal component analysis (PCA). The approach is easy to implement and simple to interpret, which is often difficult for many of the already published methods. The PCA­based approach is furthermore extended to be used with variable amplitude stress states. By implementing the developed quantification approaches in the fatigue life calculation framework, it is possible to determine if non­proportionality occurs and to account for this in the fatigue life estimation automatically using the estimated penalty factors.

The stochastic finite element method (SFEM) has been used to implement approaches for considering the spatial variability occurring in the jacket structures and welds. Closed­form solutions to the stochastic stiffness and stress stiffness matrices have been proposed, making it possible to easily implement the spatial variability of the bending rigidity and other parameters in beam FE models. The matrices have been developed for both classical Euler­Bernoulli and Timoshenko beam theory and are based on the Karhunen­Loéve (KL) expansion for random field discretization. The KL expansion is then further used to formulate a stochastic size effect that takes into account that longer welds tend to fail earlier than shorter welds when considering fatigue. Other approaches for taking into account the size effect are often based on statistical evaluation of fatigue experiments which is used to determine a deterministic calibration factor. The stochastic size effect makes it possible to simulate the randomness in a full weld independently of the highest stressed zones. Using this method, the quality of the welding can be simulated and used to predict more accurate fatigue lives.

In order to design more fatigue resistant welded joints in offshore jacket structures, automatic optimization of the welded joints is required. Already published approaches to do so, often focus on only a few simple fatigue criteria. For an optimization framework to be efficient it has to take into account the complex multiaxial non­proportional fatigue and the stochastic effects of the welds. In the thesis, an optimization framework for fatigue life estimation using the developed PCA­based quantifier and the stochastic size effect has been developed. The framework is easy to use and based on simple formulations, making it possible to implement many types of fatigue criteria without having to reformulate the optimization procedure. The framework has been used to optimize the weld locations in a cast steel jacket insert and shows that considerable mass savings can be achieved by automatic
optimization.

Short-term variability of ship responses is investigated by cross-spectrum analysis. In a steady state condition, it is well known that a certain length of sampled data is required for stable results of the spectral analysis. However, the phase lag between responses, in terms of the phase angle of the cross-spectra, has not been discussed in detail. Using long stationary time series, the transition of amplitudes and relative phase angles of the cross-spectra has
been investigated by iterative analyzes with a few seconds of time shifting. In the results, the short-term variability of the relative phase angle was observed. In effect, the variability may compromise the accuracy of the wave buoy analogy.

Gathering real-world high-quality data from underwater environments is cost-intensive, as is labeling this data for machine learning. Given this, synthetic data represents a possible solution that delivers ground-truth training data. Nevertheless, rendering and modeling of underwater environments are challenging due to several factors, including attenuation, scattering, and turbidity. The focus of this study is on the creation of a simulated underwater environment constructed for the purposes of simulating marine growth on offshore structures. The main requirement is the creation of renderings of sufficient quality and quantity with respect to the representation of marine-species distribution and intra-class variation, and sufficiently accurate recreation of lighting and turbidity (Jerlov water type) conditions underwater. Underwater rendering has been implemented using Blender, with marine growth from 2D/3D scanned and hand-modelled entities combined with a CAD model of an actual offshore installation. The proposed approach provides for the generation of synthetic images usable for training computer vision models in marine-growth inspection applications as well as other related underwater applications. This has been demonstrated in a case study, wherein the utility of the rendered dataset has been briefly demonstrated in a neural network marine-growth segmentation task. The produced renderings are available as a dataset of 1038 scene renders, using varying poses and randomized representative marine growth; each render includes RGB images, ground-truth segmentation masks, water-free RGB images, and depth information. In future work, the expansion with additional species and objects in other oceanic and coastal environments is envisioned.