Ship air emissions are recognized as one of the key concerns of the maritime industry. Competent authorities have issued various regulations to manage air emissions from ships. Although the authorities are policy makers, the effectiveness of policies is up to the shipping industry who operates the vessels and terminals to fulfill maritime transportation works. Given this characteristic, bi-level optimization model has been widely adopted in studies that optimize policy design or evaluate its effectiveness. The framework of a typical bi-level optimization model for ship emission management problem is given to show the basic structure of similar issues. A series of applications of bi-level optimization model in managing ship emissions is reviewed, including cases of Energy Efficiency Design Index, Emissions Control Area, Market Based Measure, Carbon Intensity Indicator, and Vessel Speed Reduction Incentive Program. We hope this paper can enlighten scholars interested in this area and provide help for them.
Underwater radiated noise (URN) from ship propellers has attracted increasing interest in recent years due to its adverse environmental effects on marine life and their communication channels. The environmental concern to reduce shipping noise and the industrial requirements for faster computational tools are driving factors that promote research in the specialized domain of hydroacoustics. This thesis deals with the development of such a computationally efficient numerical tool, which can be used in the prediction of underwater radiated noise in the early design phase of propellers.
The numerical model is developed with two major objectives – versatility in assessing the relative contributions from the major propeller-noise generating mechanisms, and rapidity in prediction of overall noise behaviour. It uses the Farassat-1A solid-FWH formulation of the Ffowcs-Williams- Hawkings equation by defining equivalent acoustic sources on the propeller blade, sheet cavity and tip vortex cavity surfaces. In particular, the application of the solid-FWH formulation to the tip vortex cavity model is the major novelty in this thesis.
The hydrodynamic flow solution is obtained from a potential flow based solver ESPPRO, which includes analytical models of sheet cavitation and tip vortex cavitation. The hydroacoustic numerical model developed within this thesis, DoLPHiN, is a Python-based code that is primarily designed to accept input from ESPPRO; but during the research, the code has also been adapted to read input from the commercial, finite-volume-based Navier-Stokes solver, STAR-CCM+.
The numerical model implementations are verified through analytical case studies for simple geometrical shapes, such as a pulsating sphere and an oscillating cylindrical cavity. The verification study is further extended for propeller geometries by identifying approximate reference solutions in simplified operating conditions. The numerical tool is validated for industrial application through comparison of its noise prediction with model-scale and full-scale noise measurements. Specific characteristics of the propeller noise spectrum are identified in order to evaluate its noise prediction capabilities. The uncertainty factors involved when validating with experimental measurements are also explored in detail. Furthermore, a design study is presented, which shows potential use of the numerical tool in practical propeller design and optimization applications.
In global liner shipping networks, a large share of transported cargo is transshipped at least once between container vessels, and the total transportation time of these containers depends on how well the corresponding services are synchronized. We propose a problem formulation that integrates service scheduling into the liner shipping network design problem. Furthermore, the model incorporates many industry-relevant modeling aspects: it allows for leg-based sailing speed optimization, it is not limited to simple or butterfly-type services, and it accounts for service-level requirements such as cargo transit time limits. The classic liner shipping network design problem is already a hard problem, and to solve the extended version, we propose a column-generation matheuristic that uses advanced linear programming techniques. The proposed method solves LINER-LIB instances of up to 114 ports and, if applied to the classic liner shipping network design problem, finds new best solutions to all instances, outperforming existing methods reported in the literature. Additionally, we analyze the relevance of scheduling for liner shipping network design. The results indicate that neglecting scheduling and approximating transshipments instead may result in the design of liner shipping networks that underestimate cargo transit times and their implications.
Having a well-designed liner shipping network is paramount to ensure competitive freight rates, adequate capacity on trade-lanes, and reasonable transportation times. The most successful algorithms for liner shipping network design make use of a two-phase approach, where they first design the routes of the vessels, and then flow the containers through the network in order to calculate how many of the customers’ demands can be satisfied, and what the imposed operational costs are. In this article, we reverse the approach by first flowing the containers through a relaxed network, and then design routes to match this flow. This gives a better initial solution than starting from scratch, and the relaxed network reflects the ideas behind a physical internet of having a distributed multi-segment intermodal transport. Next, the initial solution is improved by use of a variable neighborhood search method, where six different operators are used to modify the network. Since each iteration of the local search method involves solving a very complex multi-commodity flow problem to route the containers through the network, the flow problem is solved heuristically by use of a fast Lagrange heuristic. Although the Lagrange heuristic for flowing containers is 2–5% from the optimal solution, the solution quality is sufficiently good to guide the variable neighborhood search method in designing the network. Computational results are reported, showing that the developed heuristic is able to find improved solutions for large-scale instances from LINER-LIB, and it is the first heuristic to report results for the biggest WorldLarge instance.
When a ship navigates at sea, the slamming impact can generate significant load pulses which move up along the hull plating. The effect of the moving pressure has so far not been explicitly considered in the Rules and Regulations for the Classification of Ships. Based on a modal superposition method and the Lagrange equation, this paper derives analytical solutions to study the elastic dynamic responses of fully clamped rectangular plates under moving pressure impact loads. The spatial variation of the moving slamming impact pressure is simplified to three types of impact loads, i.e. a rectangular pulse, a linearly decaying pulse and an exponentially decaying pulse. The dynamic responses of fully clamped rectangular plates under the moving slamming impact pressure are calculated in order to investigate the influence of the load pulse shapes and moving speed on the plate structural behaviour. It is found that the structural response of the plate increases with the increase of the moving speed. The response of the plate subjected to a moving pressure impact load is smaller than the case when the plate is subjected to a spatially uniform distributed impact load with the same load amplitude and load duration. In order to quantify the effect of the moving speed on the dynamic load, a Dynamic Moving Load Coefficient (DMLC) is introduced as the ratio between the dynamic load factor for the moving impact load and that under the spatially uniform distributed impact load. An expression for DMLC is proposed based on analyses of various scenarios using the developed analytical model. Finally an empirical formula which transforms the moving impact loads to an equivalent static load is proposed.
A conceptual design framework for collision and grounding analysis is proposed to evaluate the crashworthiness of double-hull structures. This work attempts to simplify the input parameters needed for the analysis, which can be considered as a step towards a design-oriented procedure against collision and grounding. Four typical collision and grounding scenarios are considered: (1) side structure struck by a bulbous bow, (2) side structure struck by a straight bow, (3) bottom raking, (4) bottom stranding. The analyses of these scenarios are based on statistical data of striking ship dimensions, velocities, collision angles and locations, as well as seabed shapes and sizes, grounding depth and location. The evaluation of the damage extent considers the 50- and 90-percentile values from the statistics of collision and grounding accidents. The external dynamics and internal mechanics are combined to analyse systematically the ship structural damage and energy absorption under accidental loadings.
This work presents a comparative study of two signal processing methods for the estimation of the roll natural frequency towards the real-time transverse stability monitoring of fishing vessels. The first method is based on sequential application of the Fast Fourier Transform (FFT); the second method combines the Empirical Mode Decomposition (EMD) and the Hilbert-Huang Transform (HHT). The performance of the two methods is analysed using roll motion data of a stern trawler. Simulated time series from a one degree-of-freedom nonlinear model, and experimental time series obtained from towing tank tests are utilized for the evaluation. In both cases, beam waves are considered but, while irregular waves are adopted in the simulated data, the towing tank tests are made in regular waves. Based on the available data the performance of both estimation methods is comparable, but the EMD-HHT method turns out slightly better than the sequential FFT. Finally, the use of a statistical change detector, together with the EMD-HHT methodology, is proposed as a possible approach for the practical implementation of an onboard stability monitoring system.
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.
Performance data from ships is subject to distributional shifts, sometimes referred to as concept drift. In this study, synthetic monitoring data is simulated for the KVLCC2, considering publicly available reference data and a semi-empirical simulation framework. Neural networks are trained to predict the required shaft power and to overcome the deterioration in model accuracy due to concept drift, three methods of incremental learning are applied and compared: (1) Layer freezing, (2) regularization, and (3) elastic weight consolidation. Furthermore, an implicit methodology for quantifying the changing hull and propeller performance is presented. In addition, a generic feature engineering framework is used for eliminating insignificant features. In two investigations, sudden and incremental concept drift scenarios are examined, and the effect of different uncertainty categories on model performance is studied in parallel based on three different datasets. As a main finding, it is confirmed that data quality is of great importance for accurate machine learning-driven performance monitoring — even in simulated environments. Furthermore, the study shows that freezing layers during incremental learning proves to be most robust and accurate, but it will be part of future work to examine this on actual sensor data.
A practical estimation methodology of the mean added resistance in irregular waves is shown, and the present paper provides statistical analyses of estimates for ships in actual conditions. The study merges telemetry data of more than 200 in-service container vessels with ocean re-analysis data from ERA5. Theoretical estimates relying on spectral calculations of added resistance are made for both long- and short-crested waves and are based on a combination of a parametric expression for the wave spectrum and a semi-empirical formula for the added resistance transfer function. The theoretical estimates are compared to predictions from an indirect calculation of added resistance relying on shaft power measurements and empirical estimates of the remaining resistance components. Overall, the comparison reveals a bias in bow oblique waves and higher sea states of the spectral estimates as well as the large variance of the empirically derived predictions — particularly in beam-to-following waves. One of the study’s main findings, confirming previous studies but based on a much larger dataset than in earlier similar studies, is that added resistance assessment based on in-service data is complex due to significant associated uncertainties.