SINTEF Ocean

Abstract IntroductionStakeholder engagement is a principle that underpins ecological restoration. However, how stakeholder engagement processes are conducted in large part determines the success of their outcomes.ObjectivesIn this systematic review, we investigate how stakeholders are identified and subsequently engaged in the marine and coastal restoration peer‐reviewed literature.MethodsTo conduct this systematic review, we selected articles from two electronic databases with broad coverage relevant to the topic of marine restoration: Scopus and Web of Science. Following the PRISMA framework, we analyzed 538 articles, deeming 54 of them relevant for the review.ResultsTwo bodies of literature emerged from our analysis: articles where scholars investigate stakeholders' perceptions of restoration or aspects of restoration (e.g. techniques, governance) and articles where scholars describe stakeholders' participation in restoration projects and planning. Across these two bodies of literature, we found key similarities and differences with respect to stakeholder identification and engagement practice. Importantly, we found that scholars investigating stakeholders' perceptions of restoration are more likely to provide information about stakeholder identification and engagement methods than scholars describing stakeholders' participation in restoration.ConclusionsAs stakeholder engagement is a key principle underpinning restoration, it is important for scholars to be transparent about how stakeholders are identified and engaged. Transparency highlights how inclusive a process is and promotes learning for future restoration projects working to engage stakeholders.

The accurate prediction of vessel responses in waves is crucial for decision-making and contribute to the operational safety and risk minimization. Short-term predictions can be carried out by estimating the vessel’s motions and loads based on incident waves. Existing model-based approaches either require computationally intensive simulations that compromise real-time capability or use simplified models affecting the accuracy of the prediction. Therefore, this study explores the feasibility of using neural networks for mapping time signals of surface elevation data and a set of corresponding ship responses, i.e. the heave and pitch motions as well as the vertical bending moment. The approach followed here is built on the assumption that the wave profile amidships is known. For training purposes, a synthetic dataset was generated using a time-domain strip theory solver with considerations of non-linear effects on motions and loads due to large amplitude waves in a variety of irregular, long-crested sea state conditions. We propose two different neural network models, a multi-layer perceptron (MLP) and a fully convolutional neural network (FCNN), and compare their performances on measurement data obtained from model tests in a seakeeping basin. The evaluations also include the freak wave reproduction of the ‘new year wave’. The proposed networks are able to estimate the motions and bending moment accurately for a wide range of sea state conditions, outperforming current state-of-the-art models on the given data sets.

Slender marine structures, such as risers and power cables are subject to various loads, where Vortex-Induced Vibrations (VIV) is known to have a significant impact on accumulation of fatigue damage in the materials. The stochastic nature of VIV makes it challenging to do accurate fatigue predictions even when the underlying numerical model is deterministic. The current state-of-the-art is to model VIV response in the time-domain, where semi-empirical models have shown promising results. However, there are significant uncertainties in the fatigue prediction associated with assuming the values of the empirical model parameters. In the present paper, an efficient gradient-free optimization method is proposed to adapt the empirical parameters based on curvature measurements from model tests. Prior to the optimization problem, a global sensitivity analysis was applied to determine which parameters that have the largest influence on relevant quantities of interest. A variance-based sensitivity analysis method using Sobol’ indices was used together with a Polynomial Chaos Expansion to increase the computational efficiency of the method. The yearly fatigue damage was computed for model tests with a riser in sheared current and simulated using the optimal, adaptive parameters. Using adaptive parameters improved the prediction of curvatures, including both the maximum curvature and identification of the dominating frequency related to the given curvature. The predicted maximum fatigue damage was also improved, especially for the in-line direction.

Abstract Recent climate studies forecast violent weather events with impact on the safety of maritime transportation. For example, harsh weather may result in system failures such as blackouts or loss of steering capability. Problems met when performing planned maintenance at sea may lead to adverse events if the weather cause delays or makes it impossible to complete the planned work. A drifting vessel in general is a liability for collisions with offshore structures, groundings, and total loss due to capsizing. The increasing use of ocean structures for energy production at sea (coastal and deepwater windfarms) and the transfer of fish farming structures to more exposed locations increase the probability of collisions between drifting ships and ocean structures. To mitigate risks, several incidents and their consequences have been analysed by national administrations. In some cases, these analyses have recommended the use of dedicated emergency towing resources. The willingness of the national governments to fund such resources is directly related to the time since the last major incident in their territorial waters. This paper reviews some recent cases of emergency towing operations in Norwegian waters and highlights challenges interlinked to setting up an emergency towing connection between a drifting ship and an emergency towing vessel in harsh weather.

Composite coatings containing reduced graphene oxide (rGO) and 3-(aminopropyl)triethoxysilane functionalised rGO (APTES-rGO) were prepared by sol–gel technology and deposited on Al 2024 T-3. Covalent functionalisation of GO by APTES occurred by formation of amide bonds, accompanied by GO reduction. The thin sheets were retained. The hydrophilicity of the coating increased when APTES-rGO was added. The opposite was observed when GO was added. A key finding is that the rGO flakes agglomerate and lie in a random orientation in the coating, whereas the APTES-rGO flakes are more evenly distributed in the matrix and appear to lie along the plane of the substrate.

The present paper deals with a systematic study of the shear lag effect on the bending moment distribution in girders of representative pontoon-type floating bridges (PTFBs). Comparative and parametric studies for well-developed beam and linear shell models for representative structural components of a reference PTFB subject to representative static and dynamic loads, e.g. self-weight load condition, traffic loads, and wave-induced vertical dynamic loads on PTFB's pontoons are carried out. The study is partly based on a simplified, generic PTFB model, denoted GPTFB. The study shows that elementary beam element models, for which shear lag effects are not accounted for, might, to some extent, inaccurately predict the bending stiffness, eigenmode shapes and eigen frequencies of PTFBs with large width and relatively short span lengths (e.g. the ratio of span length to girder width of PTFBs is less than 7.24), while the inaccurate prediction of beam model in weak axis bending moment in girder of the PTFBs is related to the load pattern and dynamic load frequency range. A practical method is proposed to judge when caution is needed in using elementary beam model for estimating the weak axis global bending moments in girder of PTFBs. In addition, a case study presented in this paper, shows that the part of the girder near the bank abutment might be subjected to complex boundary conditions since the girder is supported by floating pontoons and bottom fixed columns. In this part of the bridge girder, a significant influence of shear lag on weak axis bending moments is observed. Further analysis by using shell elements is necessary to estimate the stresses, including the effect of shear lag, in this part of the girder.

Hyperspectral imaging is a powerful remote sensing technology, but its use in space is limited by the large volume of data it produces, which leads to a downlink bottleneck. Therefore, most payloads to date have been oriented towards demonstrating the scientific usefulness of hyperspectral data sporadically over diverse areas rather than detailed monitoring of spatio-spectral dynamics. The key to overcoming the data bandwidth limitation is to process the data on-board the satellite prior to downlink. In this article, the design, implementation, and in-flight demonstration of the on-board processing pipeline of the HYPSO-1 cube-satellite are presented. The pipeline provides not only flexible image processing but also reliability and resilience, characterized by robust booting and updating procedures. The processing time and compression rate of the simplest pipeline, which includes capturing, binning, and compressing the image, are analyzed in detail. Based on these analyses, the implications of the pipeline performance on HYPSO-1’s mission are discussed.