This work evaluates the hydrodynamic performance of an oscillating water column wave energy converter, with a focus on comparing conventional two-way energy capture to one-way energy capture where only the up- or down-stroke is used drive the turbine. Small-scale model test experiments are performed, and numerical calculations are made using weakly-nonlinear potential flow theory. The air turbine is represented experimentally by an orifice plate with a flow area equal to about 1% of the internal-chamber water-plane area. One-way energy capture by the experimental model is realized by incorporating a passive, low-inertia, non-return valve which vents the air inside the chamber on one half-cycle of the internal water-column oscillation. In the numerical calculations, there is little difference between the two venting configurations, due to the simplified weakly non-linear model. However, the experimental results show that up-stroke venting generally yields a higher power absorption than down-stroke venting and the two-way energy capture generally yields a higher power absorption compared to the one-way energy capture. The calculations agree well with the experiments for two-way absorption, but substantially over-predict the absorbed power in the one-way configuration. This is mainly attributed to the imperfect venting system in the physical model, but further tests and/or CFD calculations are needed to confirm this conclusion.
The approach documented in this paper employs system identification (SI), or data-based modelling, techniques as an alternative to model determination from first principles for modelling a vented oscillating water column wave energy converter, using real wave tank data gathered at Danmarks Tekniske Universitet. In SI, the parameters of the model are obtained from the experimental input/output data by minimizing a cost function, related to model fidelity. The main advantage of SI is its simplicity, as well as its potential validity range, where the dynamic model is valid over the full range for which the identification data was recorded. Furthermore, SI models are somewhat flexible, since they can be solely based on data (black-box models), or else can incorporate some physics-based information (grey-box models). However, a suitable excitation signal is of primary importance for the parametric model to be representative over a wide range of operating conditions.
The “Initial IMO Strategy” was adopted in the 72nd session of the Marine Environment Protection Committee (MEPC 72) of the International Maritime Organization (IMO) in April 2018. It has set, among other things, ambitious targets to reduce greenhouse gas (GHG) emissions from ships, and purports to express a strong political will to phase them out as soon as possible. The most ambitious of these targets is to reduce GHG emissions by 2050 at least 50% vis-à-vis 2008 levels, and there is also an intermediate target to reduce CO2 emissions per transport work by 2030 at least 40%, again vis-à-vis 2008 levels. More than three years since the adoption of the Initial IMO Strategy, this chapter takes stock at the status of shipping decarbonisation and attempts to assess prospects for the future. Obstacles towards achieving the IMO targets are identified and discussed.
This article examines the theoretical and practical implications of artificial intelligence (AI) integration in supply chain management (SCM). AI has developed dramatically in recent years, embodied by the newest generation of large language models (LLM) that exhibit human-like capabilities in various domains. However, SCM as a discipline seems unprepared for this potential revolution, as existing perspectives do not capture the potential for disruption offered by AI tools. Moreover, AI integration in SCM is not only a technical but also a social process, influenced by human sensemaking and interpretation of AI systems. This article offers a novel theoretical lens called the AI Integration (AII) framework, which considers two key dimensions: the level of AI integration across the supply chain and the role of AI in decision-making. It also incorporates human meaning-making as an overlaying factor that shapes AI integration and disruption dynamics. The article demonstrates that different ways of integrating AI will lead to different kinds of disruptions, both in theory and practice. It also discusses the implications of AI integration for SCM theorizing and practice, highlighting the need for cross-disciplinary collaboration and sociotechnical perspectives.
This article builds on rich empirical data following our unexpected discovery of a local practice to circumvent a stressful
and counterproductive work environment due to distrust at the Port of Tema in Ghana. Using theoretical work on networks,
trust, and humor, as well as extensive ethnographic feldwork, we found that the humorous atmosphere at the regularly
held physical berthing meetings fosters a sense of community, which enables competing professions, private companies,
and public institutions to manage their mutual distrust. In an environment where trust among competitors is unrealistic, we
argue that the objective of the performance of humor and transparency at the physical berthing meetings is the management
of distrust rather than the creation of trust. The meetings have, gradually, grown to serve as a pragmatic local stakeholder
adaptation to the challenges posed by universally perceived politicized, opaque, and corrupt business practices at the Port
of Tema and beyond. In conclusion, we posit that our empirical fndings allow us to identify the potential of and gaps in
theories about trust and humor in understanding the dynamics of coping strategies among competitors in business settings
that are characterized by unethical practices.
Design
Our data set, collected via surveys from top managers and project managers involved in 86 NPD projects in 85 firms, is analyzed using PLS structural equation modeling.
Purpose
This study examines how technical drivers as well as social drivers influence organic communication and top management involvement (TMI) in new product development (NPD) projects. Technical drivers are strategic importance and product innovativeness and social drivers are intrinsic and extrinsic relevance. Organic communication is defined as continuous, bi-directional, and informal communication between top management and the NPD teams. Further, arguing that TMI must be studied as multi-faceted construct, TMI is conceptualized to occur as guidance, active motivation, providing resources, and creating a tolerant climate. Subsequently, the effect of TMI and organic communication on NPD performance is investigated.
Findings
We show that the strategic importance of the project has a positive influence on TMI through active motivation, providing resources, and creating a tolerant climate for innovation, but does not have an effect on guidance. Results also show that active motivation and organic communication improve budget and schedule adherence, whereas providing guidance and stimulating a tolerant climate have detrimental effects. In summary, our results show that only active motivation enhances all types of performance while stimulating a tolerant climate appears to have the opposite effect. The results revealed that organic communication between top management and the NPD team has a strong positive effect on all elements of TMI (providing guidance, actively motivating the NPD team, providing resources, and creating a tolerant climate). In other words, when top management communicates with the NPD team throughout the project in an informal way and listens to the team in addition to engaging in a one-way communication, they are more likely to be seen by the team as being deeply involved in the project.
The PermaGov Deliverable focuses on exploring the EU policy landscape within the context of the European Green Deal (EGD), structured around four regime complexes: marine life, marine plastics, marine energy, and maritime transport. These complexes provide a framework for analyzing the EU's approach to achieving the EGD's vision for sustainable marine governance. This report aims to offer a descriptive overview of marine EU policies relevant to the PermaGov project, focusing on policies identified as relevant to the overarching goals set forth in the EGD. It also considers relevant initiatives at global and regional levels.
The marine life regime sees the EU Biodiversity Strategy for 2030 as its overarching strategy, essential for the EGD's element of preserving and restoring ecosystems and biodiversity. Tackling the challenges of marine waste pollution, the marine plastics regime is guided by the EU Circular Economy Action Plan and the EU Action Plan: Towards Zero Pollution for Air, Water, and Soil, targeting the EGD's elements of a mobilizing industry for a clean and circular economy and a zero-pollution ambition for a toxic-free environment. The marine energy regime is shaped by the European Climate Law and the Offshore Renewable Energy Strategy, which are the overarching instruments that contribute to the EGD's elements of increasing the EU's climate ambition for 2030 and 2050 and ensuring the supply of clean, affordable, and secure energy. Lastly, the maritime transport regime sees the'Fit for 55'Package and the'Sustainable and Smart Mobility Strategy'as the two main instruments to achieve the EGD's elements of increasing the EU.
Linear potential flow (LPF) models remain the tools-of-the-trade in marine and ocean engineering despite their well-known assumptions of small amplitude waves and motions. As of now, nonlinear simulation tools are still too computationally demanding to be used in the entire design loop, especially when it comes to the evaluation of numerous irregular sea states. In this paper we aim to enhance the performance of the LPF models by introducing a hybrid LPF-ML (machine learning) approach, based on identification of nonlinear force corrections. The corrections are defined as the difference in hydrodynamic force (viscous and pressure-based) between high-fidelity CFD and LPF models. Using prescribed chirp motions with different amplitudes, we train a long short-term memory (LSTM) network to predict the corrections. The LSTM network is then linked to the MoodyMarine LPF model to provide the nonlinear correction force at every time-step, based on the dynamic state of the body and the corresponding forces from the LPF model. The method is illustrated for the case of a heaving sphere in decay, regular and irregular waves – including passive control. The hybrid LPF model is shown to give significant improvements compared to the baseline LPF model, even though the training is quite generic.
From the process control point of view, any reliable and online Oil-in-Water (OiW) measurement could provoke a brand new control paradigm for produced water treatment. However, the real-time OiW monitoring is still an open and ad-hoc situation in recent decades. The fundamental issue, ie, the OiW measurement is methodology dependent, leads to numerous challenges, such as (i) how to verify the reliability and accuracy of a specific methodology/instrument; (ii) how to handle and interpret the measured data in a most objective manner; and (iii) how to keep a cost-effective on-site calibration and maintenance under the harsh offshore conditions etc. The paper reports our latest achievements and observations in usage of fluorescence- and microscopybased OiW monitoring technologies for advanced Produced Water Treatment (PWT) control and evaluation, particularly by focusing on the de-oiling hydrocyclone installations.
Tropical marine ecosystems provide a wide range of provisioning, regulating, supporting and cultural services to millions of people. They also largely contribute to blue carbon sequestration. Mangroves, seaweeds, and seagrass habitats are important because they store large amounts of organic carbon while fish play a fundamental role in the carbon transport to deep waters. Protecting and restoring tropical marine ecosystems is of great value to society because their decline impairs the vital services they provide, such as coastal protection and seafood supplies. In this marine policy paper, we present options for enhancing blue carbon sequestration in tropical coastal areas. In addition, we outline the economic value of four components of coastal ecosystems (mangroves, seagrass beds, seaweed forests and fish) and discuss the economic levers society can apply to ensure the end of the current gross mismanagement of tropical blue carbon ecosystems. Market-based solutions, such as carbon taxes or fines for violations that use the ‘polluter pays' principle, can be very effective in achieving national or international climate agreements. Private investment can also finance the preservation of blue carbon ecosystems. One widely known financing method for blue carbon conservation, particularly of mangroves, is the use of municipal bonds, which can be issued like traditional bonds to finance the day-to-day obligations of cities, states and counties. Non-philanthropic investments can also be used in order to protect these ecosystems, such as debt-for-nature swaps and the improved application of regulatory frameworks. Overall, the protection of tropical marine ecosystems is an ecological imperative and should also be seen as an opportunity for new revenue streams and debt reduction for countries worldwide.