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.
Considering 91 countries with seaports, this study conducted an empirical inquiry into the broader economic contribution of seaborne trade, from a port infrastructure quality and logistics performance perspective. Investment in quality improvement of port infrastructure and its contribution to economy are often questioned by politicians, investors and general public. A structural equation model (SEM) is used to provide empirical evidence of significant economic impacts of port infrastructure quality and logistics performance. Furthermore, analysis of a multi-group SEM is performed by dividing countries into developed and developing economy groups. The results reveal that it is vital for developing countries to continuously improve the quality of port infrastructure as it contributes to better logistics performance, leading to higher seaborne trade, yielding higher economic growth. However, this association weakens as the developing countries become richer.
This study introduces a state-of-the-art volatility forecasting method for container shipping freight rates. Over the last decade, the container shipping industry has become very unpredictable. The demolition of the shipping conferences system in 2008 for all trades calling a port in the European Union (EU) and the global financial crisis in 2009 have affected the container shipping freight market adversely towards a depressive and non-stable market environment with heavily fluctuating freight rate movements. At the same time, the approaches of forecasting container freight rates using econometric and time series modelling have been rather limited. Therefore, in this paper, we discuss contemporary container freight rate dynamics in an attempt to forecast for the Far East to Northern Europe trade lane. Methodology-wise, we employ autoregressive integrated moving average (ARIMA) as well as the combination of ARIMA and autoregressive conditional heteroscedasticity (ARCH) model, which we call ARIMARCH. We observe that ARIMARCH model provides comparatively better results than the existing freight rate forecasting models while performing short-term forecasts on a weekly as well as monthly level. We also observe remarkable influence of recurrent general rate increases on the container freight rate volatility.
This study investigates the appropriate port governance model for implementation of green port management (GPM) practices. Relying on social systems engineering principles, we propose a multi-criteria decision-making (MCDM) framework considering four port governance models and five major GPM practice indicators. We validate the MCDM framework using survey data collected from top management executives of three ports in the Indian Ocean Rim — Bangladesh, Sri Lanka and Tanzania. We compare the Analytic Network Process (ANP) method with more recently developed Best-Worst Method (BWM) in analysis of the MCDM problem of finding the right port governance model for GPM. We collect data using the ANP and BWM survey in January 2019 and August 2019, respectively, from the same respondents. While participating in the study in January 2019, the respondents did not know that they would respond to the same MCDM problem using a different model, which corresponds to a repeated measures experimental design. In both analyses, we find that increasing privatization in port governance would enhance the implementation of GPM practices. Our study furthermore suggests that BWM is a reliable MCDM method with greater applicability than ANP, as it requires significantly lower number of judgement comparisons.
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.
The paper presents a comprehensive review of the current status of integrated high temperature proton exchange membrane fuel cell (HT-PEMFC) and methanol steam reformer (MSR) systems. It highlights the advantages and limitations of the technology and outlines key areas for future improvement. A thorough discussion of novel reformer designs and optimizations aimed at improving the performance of the reformer, as well as different integrated MSR-HT-PEMFC system configurations are provided. The control strategies of the system operation and system diagnosis are also addressed, offering a complete picture of the integrated system design. The review revealed that several processes and components of the system should be improved to facilitate large-scale implementation of the MSR-HT-PEMFC systems. The lengthy system startup is one area that requires improvements. A structural design that is more compact without sacrificing performance is also required, which could possibly be achieved by recovering water from the fuel cell to fulfill MSR's water needs and consequently shrink the fuel tank. Reformer design should account for both heat transfer optimizations and reduced pressure drop to enhance the system's performance. Finally, research must concentrate on membrane materials for HT-PEMFC that can operate in the 200–300 °C temperature range and catalyst materials for more efficient MSR process at lower temperature should be investigated to improve the heat integration and overall system efficiency.
As maritime technology advances, multi-energy ship microgrids (MESMs) are widely used in large cruise tourism. In this context, studying cost-effective and highly reliable energy system planning methods for MESMs in their entire lifespan becomes paramount. Therefore, this paper proposes a joint planning method for a MESM during its lifetime. Firstly, a long timescale coordinated planning and operation scheme is formulated with the aim of maximizing the Net Present Value (NPV) value, thereby reducing both project investment and energy supply cost. In addition, this paper introduces novel operation models that incorporate customer thermal comfort levels, considering thermal inertia, and ship navigation, accounting for the effects of waves and wind. These models enhance the flexibility and practicality of the planning process. Finally, to ensure the safe operation of vessels and alleviate the negative effects of uncertain wind and waves during ship navigation, a robust optimization (RO) approach is employed. A case study demonstrates the effectiveness of the proposed method, with several comparison analyzes further highlighting its advantages.
Efficient control schemes of Autonomous underwater vehicle (AUV) are challenging due to uncertainties and highly nonlinearities. In this paper, improved fractional order PID controller is proposed for the control of AUV motion with six degrees of freedom (DOF). Genetic algorithm and Particle Swarm Optimization (PSO) are employed to find suboptimal coefficients of FOPID controller to improve performance of the AUV motion. These optimal adjusted coefficients of FOPID controllers minimize the step response characteristics such as maximum deviation and settling time. Simulation results are presented to verify the advantages of the FOPID with respect to the previous works specially proportional-integral-derivative controller (PID).
Why should we look to the past to understand privacy and the ways we can protect it? Privacy, as a contemporary concept, already seems to be challenging to define and regulate enough. With the ever-speeding technological developments we face today, it is hard to catch up with all the different ways in which our privacy can be breached. In the case of the maritime context, the complexity increases. Issues of jurisdiction, as well as the maritime control of the mobility of goods, information, and people, make tackling ‘privacy at sea’ a difficult task. Regulating forces, such as the European Maritime Safety Agency, need to be clear on their security measures, which must include a balance between surveillance for safety and personal data protection on the one hand and general privacy for people in vessels on the other.1 Looking back to history could, therefore, appear counterproductive, adding intricacies to an already convoluted issue. However, shifting perspectives to understand the historical roots of how such issues developed and to pay heed to what people continuously try to protect when advocating for privacy helps us break those dichotomies that make the balance between public safety and privacy harder to reach.
In recent years, shipboard microgrids (MGs) have become more flexible, efficient, and reliable. The next generations of future shipboards are required to be equipped with more focuses on energy storage systems to provide all-electric shipboards. Therefore, the shipboards must be very reliable to ensure the operation of all parts of the system. A reliable shipboard MG should be pro-tected from system faults through protection selectivity to minimize the impact of faults and facili-tate detection and location of faulty zones with the highest accuracy and speed. It is necessary to have an across-the-board overview of the protection systems in DC shipboards. This paper provides a comprehensive review of the issues and challenges faced in the protection of shipboard MGs. Furthermore, given the different types of components utilized in shipboard MGs, the fault behavior analysis of these components is provided to highlight the requirements for their protection. The protection system of DC shipboards is divided into three sub-systems, namely, fault detection, lo-cation, and isolation. Therefore, a comprehensive comparison of different existing fault detection, location, and isolation schemes, from traditional to modern techniques, on shipboard MGs is presented to highlight the advantages and disadvantages of each scheme.