Ship Operation Research Articles

Alignment Prediction of Air Spring Vibration Isolation System for Marine Shafting Based on Genetic Algorithm-Back Propagation Neural Network.

Shafting alignment plays an important role in the marine propulsion system, which affects the safety and stability of ship operation. Air spring vibration isolation systems (ASVISs) for marine shafting can not only reduce mechanical noise but also help control alignment state by actively adjusting air spring pressures. Alignment prediction is the first and a key step in the alignment control of ASVISs. However, in large-scale ASVISs, due to factors such as strong interference and raft deformation, alignment prediction faces problems such as alignment measurement sensors failure and difficulty in establishing a mathematical model. To address this problem, a data model for predicting alignment state is developed based on a back propagation (BP) neural network, fully taking advantage of its self-learning and self-adaption abilities. The proposed model exploits the collected data in the ASVIS instead of the alignment measurement data to calculate the alignment state, providing another alignment prediction approach. Then, in order to solve the local optimum issue of BP neural network, we introduce the genetic algorithm (GA) to optimize the weights and thresholds of the BP neural network, and an improved GA-BP model is designed. The GA-BP model can leverage the advantages of the global search capability of GA as well as the BP neural network's fast convergence in local search. Finally, we conduct experiments on a real ASVIS and evaluate the prediction models using different criteria. The experimental results show that the proposed prediction model with the GA-BP neural network can accurately predict the alignment state, with a mean-square error (MSE) of 0.0114. And compared to the BP neural network, the GA-BP neural network reduces the MSE by approximately 74%.

Features of planning and evaluation of the work of small shipping vessels enterprises at the present stage

The article considers one of the possible approaches to planning and evaluating the fleet operation of small shipping enterprises at the present stage. The existing algorithms for mathematical modeling of fleet operations are universal and can be used for enterprises with a small number of vessels, but at the same time they are complex, costly and therefore inefficient, and therefore unclaimed. In this regard, the article state the problem of developing a system for operational planning and evaluation of the fleet of small shipping enterprises in the context of modern economics and trends in the use of information technology, defines the objectives of the development and implementation of the system, its configuration; reveals the purpose and methods of implementing the components of the system. The methods necessary for the development of the system and also to be developed are called. The importance of substantiating the effectiveness of informatization is emphasized.

Markov Chain Analysis of Ship Energy Efficiency

A formulation is presented for the assessment of the CO2 generated by ships in operation and their evolution with time, conditional on the current legislation using Markov chains. Any potential deep repair or retrofitting of the ship propulsion system or enhancement of route operational characteristics during the service life are not accounted for. The Markov transition matrix is defined based on the ship operations and CO2 history of A, B, C, D, and E carbon intensity indicator (CII) rates. The transition between different CII rate states in the survey data is used to estimate the probability of transition of the analysed ships between different CII grates. Distinct transition matrices employing the progressively tightened legislation of CII are employed and analysed. In addition, the transition matrices can be fed into risk-based models that take the CII rates as input for defining the most appropriate ship energy efficiency management plan.

A framework of a data-driven model for ship performance

An accurate assessment of a ship's required power is increasingly relevant for ship operations. We used a simplified framework of a data-driven model to predict ship's fuel consumption. Our approach was based on the learning capabilities of a generalized AutoML (Automated Machine Learning) process, trained with a variety of databases obtained from Computational-Fluid-Dynamics (CFD) simulations or from simplified numerical methods. These CFD simulations were conducted by solving the Reynolds Averaged Navier-Stokes (RANS) equations, using the STARCCM + commercial CFD software to calculate the ship resistance at speed under different operating conditions. Initially, we conducted a statistical analysis to select the independent variables before fitting the regression models and identifying potentially wrong assumptions. The AutoML process allowed optimizing the model's hyperparameters and designing the topology of the neural networks. For a set of unknown scenarios, comparative predictions obtained from the data-driven model and from numerical simulations showed that the data-driven model, trained with results obtained from CFD simulations, accurately and efficiently predicted ship operational parameters under realistic operating conditions, thereby dispensing with the need to perform elaborate CFD computations. Specifically, this low-cost and efficient operational data-driven technique forecasted the ship's operational fuel consumption although only a limited amount of recorded operational data was available.

A Multi-Attribute Decision-Making Approach for International Shipping Operator Selection Based on Single-Valued Neutrosophic Power Hamy Mean Operators

A Multi-Attribute Decision-Making Approach for International Shipping Operator Selection Based on Single-Valued Neutrosophic Power Hamy Mean Operators

Implementasi Pendidikan Karakter dalam Pembentukan Taruna Pelayaran

Character education has its own uniqueness when applied in the context of shipping cadet education. Sailing cadets are those who are undergoing education to become reliable sailors or sailors. In this profession, it requires not only technical expertise in navigation and ship operations, but also a strong character to face challenges in an often harsh and dangerous maritime environment. Qualitative method with case study is a suitable research approach to investigate the implementation of character education in the formation of shipping cadets. Through this method, research will be conducted in depth to understand how character education is integrated in curriculum and daily practice in specific shipping schools. In this context, research shows that there is a need to strengthen the integration of character education in the cruise education curriculum to ensure that character values and principles are not only taught separately, but also integrated in every aspect of cadet learning and experience. This can be done through the development of more holistic and well-rounded programs, as well as through training for cruise school faculty and staff to understand how to best integrate character education into their teaching. Studies show that cadets consider strong character important in the maritime profession. However, there are variations in their views on the effectiveness of character education in cruise schools. There needs to be stronger integration between character education and technical curriculum, as well as training for shipping school teachers and staff. The findings of this study provide the basis for the development of more effective strategies in improving the integration of character education in cruise schools.

ЕКОЛОГІЧНА КОМПЕТЕНТНІСТЬ СУДНОВОДІЇВ В УМОВАХ СТАЛОГО РОЗВИТКУ

Relevance: Under current conditions, the problem of ship navigation gains particular relevance – the formation of ecological competence of ship operators in the context of sustainable development, the study of important aspects of the interaction of vessels and the surrounding environment, particularly their impact on water resources, water pollution, emissions of harmful substances, and other ecological aspects. Objective: To determine the role of ecological competence of ship operators in the context of sustainable development. Methods: Theoretical methods: analysis, synthesis, generalization of scientific works on the issue of ecological competence of future professionals in the field of ship navigation and official documents – to define the theoretical and methodological bases of the phenomenon; study and generalization of the existing problem status with the aim of choosing pedagogical tools – for the development of ecological competence of ship operators; comparison – to identify various approaches to solving the researched problem; modeling – to justify the structural elements of the model for the development of ecological competence of ship operators. Results: Key characteristics of ecological competence and its components have been identified; ecological competence of ship operators is considered as a complex integrative characteristic of the personality, reflecting motives of ecological activity, possession of ecological knowledge and natural science bases, practical skills and abilities regarding environmental protection; the necessity of forming ecological competence in ship operators during their professional training has been substantiated, as it directly affects the conservation of the marine water state, protecting them from pollution. It is noted that under current conditions, when sustainable development has become one of the priority directions of global policy, the ecological competence of ship operators is a key factor in ensuring safe navigation, and ecological education in the maritime sector is an important tool for forming this competence in ship operators. Conclusions: Education acts as a catalyst for the development of sustainable thinking and practices in the maritime sector, promoting ecological safety and sustainable development in this strategically important industry; as the maritime sector continues to develop, the results of the conducted research emphasize the important role of education in preparing future ship operators to navigate the ecological complexities of the global maritime industry and to contribute to sustainable development and effective communication.

Метод определения эффективности вариантов организации перевозок барже-буксирными составами

A study has been conducted on the method of evaluating options for organizing cargo transportation by barge-tow trains based on determining their effectiveness. Using the methods of the classical theory of transport processes, this problem has no quantitative solution, since it is not possible to take into account the regrouping of the composition during the passage of the route. To overcome this problem, additional mathematical tools have been developed for constructing integral time and velocity matrices, an objective function and graphs of the ratios of the total volume of transported cargo to the time it was en route. The consistent implementation of the proposed tools ensures the coherence of the calculation methods for determining the effectiveness of a flight with and without regrouping on the route, and also makes it possible to select the most appropriate option for organizing transportation. The cumulative result allows us to reflect the method of evaluation, comparison and selection of the most effective option for organizing a flight / group of flights, taking into account the ability to set individual parameters for the movement of the train and cargo. An example of approximation of the coordinate points of the route from the Nizhne-Svirsky shipping lock to Lake Ladoga is illustrated, as well as an example of discretization of an inland waterway section according to a three-level model. The parameters of equalization of the objective function of determining the efficiency of cargo transportation are considered. It is concluded that the optimal transportation option can be carried out on the basis of a combined approach, when several parameters are taken into account or sequentially set in the process of modeling the operation of ships. Graphs have been built that demonstrate the differences between the ways of organizing flights.

Evaluation of constraints for investment in NOx emission technologies: case study on Greek bulk carrier owners

PurposeThe maritime industry is the transport mode that contributes most to air pollution. The International Maritime Organization (IMO) identified the reduction of air pollution by ships as a crucial issue. Since 1 January 2020, ships have had to adopt strategies and new technologies to eliminate air pollution. However, ship compliance with nitrate oxide (NOx) emission restrictions is more challenging. This paper aims to identify shipowners' challenges in investing in new technologies.Design/methodology/approachThis paper applied a hybrid methodology combining a survey, a balanced scorecard and fuzzy analytic hierarchy process (F-AHP) to identify and evaluate constraints and weights in investment decision-making for NOx technologies. A survey was carried out to validate constraints.FindingsA survey was carried out, representing 5.1% of Greek-owned ships by deadweight capacity. The findings provide a weighted list of seven crucial technical and economic constraints faced by ship operators. The constraints vary from ship retrofit expenditure to crew training and waste management. Additionally, NOx emission technologies were compared. It was found that liquefied natural gas is the preferred investment option for the survey participants compared with selective catalytic reduction, exhaust gas recirculation and batteries.Originality/valueSeveral studies have dealt with the individual technical feasibility of NOx reduction technologies. However, apart from technical feasibility for a shipowner, the selection of a NOx technology has several managerial and safety risks. Therefore, the originality of this paper is to reveal those constraints that have a higher weight on shipowners. With this cost-benefit approach, investment challenges for ship operators are revealed. Policymakers can benefit from the results of the employed methodology.

Developed Status and Forecast of Intelligent Ship Application

The concept of smart ships is not limited to ship autonomous driving, it covers a broader scope, including the full life cycle of ship design, construction, operation and maintenance. By integrating advanced sensors, navigation systems and data analysis platforms, smart ships are able to monitor ship status and the Marine environment in real time, optimize route planning and improve fuel efficiency, thereby reducing energy consumption and greenhouse gas emissions. In addition, smart ships can revolutionize the shipping industry by improving maritime safety and reducing human error through remote control and autonomous decision-making. In recent years, smart ship technology has gradually moved from the theoretical research stage to practical application, and has attracted wide attention from the global shipping industry. A number of international cooperation and research projects have been launched to explore the practical application potential and promotion paths of smart ships. However, the development of smart ships also faces many challenges, including technical difficulties, legal and regulatory restrictions, and public acceptance issues. This paper will deeply discuss the current development status of smart ships, analyze the main challenges it faces, and forecast the future development trend, in order to provide reference and inspiration for the innovative development of the shipping industry.

Complex network-based risk analysis for maritime heavy casualties in China during 2012–2021

A collection of accident investigation reports for the 21 maritime heavy casualties that occurred in China during 2012–2021 is studied statistically and analytically in the present study. The basic accident factors are first extracted from these investigation reports to present the distribution features of these heavy casualties. Then, the accident factors in terms of crew, environment, ship equipment and management in each individual investigation report are logically linked to develop a causative chain. As a result, 21 chains developed from the 21 accident investigation reports are interweaved into a complex network by sharing the same factors. The accident factors involved in the complex network are quantitatively assessed in terms of activeness, connection strength and criticality based on the network topology parameters and the improved K-shell decomposition algorithm. The topology of the developed complex network implies that the occurrence of maritime heavy casualties is under control, and the results show that the seaworthiness of crew, ship equipment and cargo is critical to maintain safe operation on board; meanwhile, supervising ship operators and managers to ensure that they fulfil their responsibility is an effective way to maintain the maritime safety level.

Proposal of a New Control System Making Use of AI Tools to Predict a Ship’s Behaviour When Approaching the Synchronism Phenomenon

In spite of the IMO’s efforts to improve the safety of intact stability on ships, synchronous rolling still causes large rolling angles, resulting in a very dangerous situation on board. The implementation of automatic tools to predict this undesirable situation has not been widely implemented. Furthermore, the safety of ship stability is not the only responsibility of people involved in the design process, so ship operators must have enough knowledge to predict and avoid these dangerous situations well in advance. Therefore, from a theoretical point of view, in the first part, this paper aims to present a valuable guiding tool for ship operators in order to predict synchronous rolling and avoid undesirable situations on board by making use of only empirical observations of the wave profile and moments. With this purpose, mathematical models are first proposed, with the ship sailing in the worst condition, i.e., with and without considering the damping factor, at zero speed and considering the influence of any pure beam and trochoidal waves. Relevant results shown provide the exact time and wave profile at which the maximum rolling angles are reached. In the second part of the paper, a new control system making use of AI tools is proposed in order to be used by ship operators on board, avoiding dangerous situations. Finally, the results are validated using a set of ship rolling simulations for the most common and representative ship loading conditions and wave periods.

Satisfaction of passengers - process comparison between three different cruise ship classes

In cruise ship design, a ship designer often focuses on the ship’s function, while a cruise operator’s focus is on the creation of a comfortable and enjoyable cruise experience for passengers. Today, these two viewpoints are strongly connected, and thus, the way the inside of a ship is designed can impact how satisfied passengers are on their cruise journey. Thus, we need to figure out the best way to design a passenger ship from the perspective of the passengers themselves. In this paper, we analyse the differences in the combination passenger ship environmental elements and overall consumer satisfaction in two different cruise ship classes from the same ship operator, but from different eras. First, we present a theoretical framework and model for the cruise ship environment that consist of ambient, layout/design, social, product/service and onboard enjoyment factors. Then, by using data collected from the public domain, we compare two types of cruise ships using open-source data (N=755). This allows us to identify the factors contributing to the discrepancy in expectations across cruise guests. Based on this limited data, we create several linear regression models which indicates a favourable and statistically significant link between environmental elements and passengers' conduct while on board. Information processed this manner can be utilised to make informed decisions on cruise ship layout and amenities. In addition, the developed innovative KPI proved instrumental in influencing decision-making processes related to cruise ship designs and operations. Therefore, the findings from our research show a positive link between the onboard environment and the overall happiness of passengers.

Modernisation of Domestic Ro-Ro Passenger Ships Operating in the Philippines

This paper forms part of a wider study in the form of a Formal Safety Assessment of the domestic passenger ships operating in the Philippines, undertaken on behalf of the Philippines Government, and financed by the World Bank and the International Maritime Organisation. The paper focuses on design deficiencies of the domestic RoPax ships, primarily in damage stability. The process of ship selection for representation of the wider fleet risk assessment is explained, leading to one medium RoPax and one large RoPax, typical of some 500 of these ships, serving the open sea domestic trade in the Philippines. To this end, the selected designs have been subjected to a systematic process of damage stability and flooding risk analysis in order to identify design vulnerabilities, leading to risk estimation in the form of Potential Loss of Life. A number of risk control options have then been identified, enabling a thorough risk assessment and identification of cost effective RCOs, as well as impact assessment, using IMO risk acceptance criteria as basis. Despite the poor state of the domestic Ro-Ro passenger vessels operating in the Philippines, many of these aged, badly retrofitted, poorly maintained, and operated, it has been possible to identify cost-effective design solutions to raise the damage stability (and safety) standard of these ships to international standards of newly designed ships; it seems an unprecedented achievement, but evidently true. This presents the Philippine Government and the owners of these vessels with a unique opportunity to upgrade their domestic fleet of RoPax vessels and showcase these against the best in the world. Because of the similarity in the approach, the selection of risk control options and the overall analysis adopted, only one of the typical RoPax vessels selected is presented in this paper.

MariData – Digital Twin for Optimal Vessel Operations Impacting Ship Design

Energy efficiency is a key element for reduced shipping emission to meet future environmental regulations. Both design and operation play an important role to meet this goal and the perfection of the interplay between these aspects promises quick improvements to meet the requirements of short term emission standards. The MariData project [https://maridata.org] developed a forward-looking energy management and decision support system (DSS) for ship operation based on rational methods and data created during ship design and sets out to bridge the gap between design and optimized operation. The “digital performance twin” of a vessel, which is based on design data, is enhanced with lifecycle data covering the entire operational envelope and provides valuable feedback into design processes.

Rancang Bangun Sistem Monitoring Kinerja Fresh Water Generator Menggunakan Arduino Mega 2560

Fresh water is a basic need of the ship's crew in supporting the creation of smooth ship operating activities, therefore it is also necessary to have an auxiliary aircraft that can produce its own fresh water on board to reduce ship operating costs, which is called the Fresh Water Generator (FWG). FWG is an auxiliary aircraft that can convert seawater into fresh water by evaporation and condensation processes. Therefore, it is necessary to have a tool to monitor the performance of the fresh water generator. The purpose of this research is none other than to monitor temperature conditions, water TDS, and conditions on the input and output streams of the fresh water generator evaporator filter to be more optimal and efficient and to determine the reliability of the fresh water generator performance equipment system using a long distance in order to create better and higher quality fresh water production on board. This research uses a prototyping method system. After designing and testing the tool monitoring system for the performance of fresh water generators using Arduino mega 2560 based on LoRa Ra-02, this system is one of the new technologies that can monitor the performance of fresh water generators to be more efficient and reliable. Then the readings of all sensors can work properly with an average percentage error on the Max 6675 temperature sensor of 0.58%, pressure transmiter sensor 1 of 2.04%, pressure transmiter sensor 2 of 2.04%, and TDS sensor of 1,70% and the distance to communication between the receiver and transceiver reaches a range of 200 meters without obstacles and 97 meters through obstacles around.

Improved tide level prediction model combined GA-BP neural networks and GNSS SNR data

High-precision tidal forecasting plays a crucial role in providing reliable tidal information to coastal communities, ship operators, fishermen, and government agencies. Existing tidal prediction models, such as backpropagation neural networks (BPNN) and genetic algorithm-optimized BPNN (GA-BPNN), frequently difficulty in in achieving high precision because they rely solely on past tidal variations for real-time predictions. Signal-to-Noise Ratio (SNR) data have emerged as a valuable indicator closely related to real-time sea level changes due to the widespread adoption of Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technology. In this paper, we propose a nowcasting tide level prediction method by adding SNR data to BPNN, i.e., Improved BPNN and Improved GA-BPNN, which predicts the next momentary tide level value by using the previous 15 tidal values and real-time SNR as input factors to BPNN. The results of 100-day, 200-day and 1-year tide prediction based on Astoria and Friday Harbor tide gauge stations show that the improved model prediction accuracies are better than the traditional model. Meanwhile, among the two improved models, Improved GA-BPNN has the higher prediction accuracy and can adapt to different time lengths of tide level prediction.

Study on the Operation Safety of Sea Sightseeing Tourist Ships in the Waters of Kowloon Bay, Weihai

With the rapid development of social economy, tourism as a tertiary industry has developed rapidly, and sea sightseeing has become a popular project in coastal areas. These areas not only meet the requirements of tourists, but also promote the rapid development of the regional economy and make a great contribution to the development of local tourism. Tourist ship operation is one of the important ways for people to enjoy the scenery of the sea and experience boat travel, but also faces many problems such as navigation safety. In recent years, tourism and aviation safety incidents at home and abroad have frequently attracted social attention, and strengthening tourism navigation safety supervision has become a top priority. This paper selects the operation safety of maritime sightseeing and tourist vessels in the waters of Weihai Jiulong Bay as the research object, starts from the analysis of the factors affecting the operation safety of sightseeing and tourism vessels in Kowloon Bay, and establishes a hierarchical model of the operational safety factors of tourist vessels in Weihai Jiulong Bay from the perspective of the "man-ship-environment-management" system. The grey correlation analysis method is used to study the risk factors affecting the operation safety of tourist ships, and corresponding improvement measures are proposed to improve the safety of maritime sightseeing tourism and the safety of tourists.

A machine learning approach towards reviewing the role of ‘Internet of Things’ in the shipping industry

The technology of the Internet of Things (IoT) represents a cornerstone of the fourth industrial revolution. We adopt a machine learning approach to examine the effect of IoT technology on shipping business operations. Text mining and the probabilistic latent Dirichlet allocation are applied for an unsupervised topic modelling analysis of two hundred and twenty-eight academic papers. Our findings reveal the potential of IoT to provide more efficient approaches to business operations and improve the quality of services, highlighting the value of instant and secure information flow among all parties involved. Problematic areas of the new technology are also identified, in reference to issues of standardization and interoperability. Relatively few studies have used machine learning techniques to elicit insights into the holistic effect of emerging IoT technology in the shipping industry. The research findings highlight the potential of IoT technology to transform shipping operations, offering useful and practical implications to academics and professionals.

Comparison and Evaluation of Learning Capabilities of Deep Learning Methods for Predicting Ship Motions

The development of intelligent ship control systems in real-world conditions relies heavily on the accurate identification and prediction of ship seakeeping and maneuvering trajectories. In this study, we comprehensively evaluate a selection of deep learning methods to assess their learning capabilities in terms of idealizing ship motion behavior in realistic operational environments. To recover real conditions, we utilize historical Automatic Identification System (AIS) data and a time domain 6 Degree of Freedom (6- DoF) grounding dynamics model to generate ship motion sequences for a Ro-Ro passenger ship operating in the Gulf of Finland. Via a rigorous evaluation process, we validate the performance of these methods using extensive data streams. The analysis includes the identification and estimation of uncertainties between two ports. The paper demonstrates the proficiency of the selected deep learning methods in capturing ship maneuvering features, their potential use in the design of ship control and intelligent decision support systems.