Search Results (4)

This study compares four carbon intensity indicators applicable to harbor tugboats to identify the most representative greenhouse gas emissions management. Using operational data from SAAM Towage’s fleet, the indicators evaluated traveled distance, operating time, energy consumption, and average engine load demand. Statistical analyses revealed that the energy consumption-based indicator exhibited lower variability and greater capacity to reflect the operational particularities of tugboats. In contrast, indicators based on average load presented high dispersion, limiting their applicability. These conclusions highlight the importance of considering vessel-specific characteristics when selecting indicators. This work provides tools to improve environmental monitoring and facilitates the implementation of sustainability strategies aligned with the maritime industry’s emission reduction objectives. Full article

The scheduling of harbor tugboats is a crucial task in port operations, aiming to optimize resource allocation and reduce operational costs, including fuel consumption of tugboats and the time cost of vessels waiting for operations. Due to the complexity of the port environment, traditional scheduling methods, often based on experience and practice, lack scientific and systematic decision support, making it difficult to cope with real-time changes in vessel dynamics and environmental factors. This often leads to scheduling delays and resource waste. To address this issue, this study proposes a mathematical model based on fuzzy programming, accounting for the uncertainty of the arrival time of target vessels. Additionally, we introduce the NRPER-DDPG algorithm (DDPG Algorithm with Prioritized Experience Replay and Noise Reduction), which combines a prioritized replay mechanism with a decaying noise strategy based on the DDPG algorithm. This approach optimizes the time for tugboats to reach the task location as a continuous action space, aiming to minimize the total system cost and improve scheduling efficiency. To verify the effectiveness of the mathematical model and algorithm, this study conducted experimental validation. Firstly, the optimal algorithm hyperparameter combinations were adjusted through random examples to ensure the stability and reliability of the algorithm. Subsequently, large-scale examples and actual port cases were used to further verify the performance advantages of the algorithm in practical applications. Experimental results demonstrate that the proposed mathematical model and algorithm significantly reduce system costs and improve scheduling efficiency, providing new insights and methods for the sustainable development of port operations. Full article

Determining the key characteristics of a ship during the concept and preliminary design phases is a critical and intricate process. In this study, we propose an alternative to traditional empirical methods by introducing a model to estimate the main particulars of diesel-powered Z-Drive harbor tugboats. This prediction is performed to determine the main particulars of tugboats: length, beam, draft, and power concerning the required service speed and bollard pull values, employing Bayesian network and non-linear regression methods. We utilized a dataset comprising 476 samples from 68 distinct diesel-powered Z-Drive harbor tugboat series to construct this model. The case study results demonstrate that the established model accurately predicts the main parameters of a tugboat with the obtained average of mean absolute percentage error values; 6.574% for the Bayesian network and 5.795%, 9.955% for non-linear regression methods. This model, therefore, proves to be a practical and valuable tool for ship designers in determining the main particulars of ships during the concept design stage by reducing revision return possibilities in further stages of ship design. Full article

Turning ships in port turning basins is an important and responsible operation, mainly involving the ship itself and the port tugboats. Such operations involve many maneuvers that consume a lot of energy (fuel) and emit a lot of emissions. Turning basins in harbors and quay approaches are, in most cases, relatively shallow. This paper examines the turning of ships in port turning basins using harbor tugboats, the effect of shallow depth on ship turning, energy (fuel) consumption and the generation of emissions during such maneuvers of harbor tugboats. This paper presents the developed theoretical models, and the experimental results on theoretical models that were verified on real ships and using calibrated simulators. Discussions and conclusions were prepared on the basis of the research results. The use of the developed methodology makes it possible to increase shipping safety, optimize maneuvers and reduce energy (fuel) consumption when turning ships in the port and, at the same time, reduce the amount of fuel consumed by port tugboats and reduce the number of emissions of tugboats during such operations. Full article