Ship Engine Research Articles

Anomalistic Symptom Judgment Algorithm for Predictive Maintenance of Ship Propulsion Engine Using Machine Learning

Ships serve as crucial transporters of cargo and passengers in substantial volumes and operate for a long time; therefore, an efficient maintenance system is essential for economical and stable vessel operation. In this study, a machine learning based approach was developed that considers the rapidly changing load fluctuations on ships and large variability in normal operation data to apply predictive maintenance to the propulsion engines of ships. After acquiring propulsion engine data from the alarm monitoring system of a ship, data and maintenance items were analyzed to select the data that could determine the anomalistic symptoms of the propulsion engine. Further, the main engine condition criterion value was defined as the factor for anomalistic symptom prediction. An engine anomalistic symptom judgment algorithm that can be practically used for ship maintenance prediction was developed and verified using machine learning.

A Numerical Study on the Smoke Dispersion and Temperature Distribution of a Ship Engine Room Fire Based on OpenFOAM

To further study the smoke dispersion and the temperature distribution in ship engine room fires, the fire dynamics solver buoyantReactingFOAM in the software OpenFOAM-10 is used to conduct a numerical simulation study on a pool fire caused by fuel oil leakage in a ship engine room. The applicability of this solver in simulating ship-engine-room-scale fires is validated by comparing it with experimental data. The impact of the mechanical ventilation, fire area, and fire position on the smoke dispersion and the temperature distribution in the ship engine room during the fire are considered in the simulation study, with a focus on the control room and the escape exit. The simulation results of buoyantReactingFOAM agree well with the experimental data. The simulated results of the case study show that for both in the control room and near the escape exit, among the factors of fire position, fire area, and the ventilation situation, the fire position affects the temperature distribution and the smoke dispersion most heavily, followed by the fire area and then the ventilation situation, which has the least influence on them. But, compared to the control room, the influence degree of the ventilation air velocity in the escape exit is larger than that in the control room. With an increase in the fire area, the spread rate of high temperature and high smoke concentration increases. With an increase in the ventilation air velocity, the aggregation degree of smoke and temperature decreases, but its decreasing range is very small when the ventilation air velocity is larger than 2 m/s.

Simulation Experiment and Teaching Research of a Land-Based Ship Engine Room

In order to make up for the shortage of scientific research experiments and teaching in land-based engine room laboratory, a simulation system is designed and developed using B/S mode to simulate scientific research experiments, teaching and operation processes, and designed algorithms to simulate the propulsion characteristics of the main propulsion diesel engine. A large number of experiments were carried out, and the relationship curve between output power and fuel consumption rate of the main engine was obtained in the laboratory. Apache JMeter was used to test the pressure of the simulation system deployed in Dalian Maritime University Cloud. It is found that under the test conditions, the average response time of sample request is 330 ms, which is far superior the design standard of 2 s. There is no abnormal response to all requests, and all indicators fully meet the requirements of the project team. The simulation system fills the gap in the application of panoramic interactive technology in Marine engineering education, and provides a reference for the exploration of "intelligent +" experiment and teaching mode in maritime university laboratories.

Climate change and maritime law: A review of IMO governance mechanism

<p><strong><em> </em></strong>International maritime trade has long played a pivotal role in human development; however, its environmental impact cannot be disregarded. Air pollution (that includes Carbon and Sulphur emissions—all together Greenhouse Gases) emanating from ships has emerged as a significant contributor to climate change, prompting growing concern among the international community. The combustion of fossil fuels in ship engines releases pollutants such as sulfur dioxide, nitrogen oxides, and particulate matter into the atmosphere, adversely affecting both human health and the climate. In recognition of the need to tackle this issue, international laws have been established to regulate ship emissions. This research paper analysed the IMO’s regulations under international law for mitigating climate change, with a particular focus on various global initiatives controlling sulphur, carbon and GHG emissions. It is suggested that cooperation between public and private interests as well as at regional levels will play a crucial role in combating climate change and promoting global shipping sustainability.</p>

The Effect of a Web-Based Occupational Noise-Induced Hearing Loss Prevention Program on Hearing Protection Device Behavior Among Thai Navy Officers: A Quasi-Experimental Study

Navy officers working on the coastal guard vessels risk hearing loss due to repeated exposure to high noise levels from ship engines. Therefore, proper use of hearing protection devices is important. In this study, a web-based hearing loss prevention program was developed to promote the behavior of the use of hearing protection devices among Thai navy officers working on coastal guard vessels. In total, 152 navy personnel were recruited based on selection criteria and randomly assigned to the experimental (n = 76) and control groups (n = 76). The participants in the experimental group received the hearing loss prevention program via a website over four weeks. After completing the program, hearing protection device behavior was evaluated by a self-report questionnaire immediately after and at eight weeks follow-up. The results showed significantly increasing scores of the use of hearing protection devices behavior within the experimental group, both immediately and eight weeks after the program completion. However, there were no significant differences in the scores when comparing between groups, even though the scores of the experimental group were better than those in the control group. The restrictions could be explained by some emerging events during the implementation period, including the COVID-19 pandemic followed by a massive oil spill incident at sea. These put an extra workload on the study participants. Most importantly, there was a problem with the network connection that might have affected the continuation of participant attention to the program. Although this study found no effective results of the developed program due to some limitations, nurses can adopt this protective intervention to reduce the risk of occupational noise-induced hearing loss among Navy officers. Therefore, a recommendation for further study is to develop an intervention program that considers both the working context of the coastal vessels and appropriate participation methods that require more challenging efforts.

A Case Study on the Variable Frequency Drive for Ship Engine Room Ventilation

Increasing ship energy efficiency is essential to reducing fuel consumption and ship-based harmful emissions. In a ship’s engine room, there are a lot of electric motors, and their energy consumption is remarkable. The effective operation of these electric motors becomes significant when taking into account ship energy efficiency with regard to the effects on the environment and climate change. The electrical, mechanical, and operational efficiencies of electric motors can be improved with a variable frequency drive. In order to improve the ship’s overall energy efficiency, the electric motors used for engine room ventilation are examined in this paper using variable frequency drives for two different ambient temperatures. Energy consumption of the engine room ventilation fans is calculated and the change in the efficiency depending on the air temperature is analyzed. By using data from actual crude oil tanker ships, the outcomes are compared with those of the traditional system. The results indicate an energy consumption reduction of more than 80% is achievable by using VFD electric motors for engine room fans. The result corresponds to 153.279 kWh of energy instead of 613.116 kWh annually.

Development of the computer program for analysis structural integrity of marine engine elements

Timely implementation of maintenance processes provides confidence in maintaining performance and integrity throughout the life cycle of the system. Various developments in monitoring and analysis methods are aimed at maintaining the operability of systems by minimizing the failure rate. The developed computer program, presented in the paper, is used as one of the tools for assessing the technical condition of a ship power plant, allowing the use of an integrated approach to predicting and managing the quality of maintenance, including an assessment of the costs and timing of the implementation of repair work. When describing the creation of a computer program for assessing the structural integrity of ship engine elements, special attention is paid to the libraries used and the methods necessary for a comprehensive consideration of the “oil-engine” system. The Makava program, based on laboratory analyzes, allows you to determine the residual life of engine oil according to the actual state, by determining the parameters that mainly affect its aging, wherein setting threshold values for these parameters, forms the degree of deviation of actual values from the boundary values, predicting further wear of certain elements of the system. The program contains a database of typical changes in oil indicators regarding the occurrence of possible structural defects in the elements of the system, helps to expand the information resource by collecting, processing, accumulating and storing information on the degradation of the components of the propulsion complex of various engine models for subsequent planning of measures for the quality of maintenance and repair of shipboard power installations.

A calculation algorithm for ship pollutant gas emissions and diffusions based on real-time meteorological conditions and its application

Most literature focusing on the issue of ship pollutant emission and diffusion is based on static meteorological conditions. The relevant literature seldom analyzes the emission and diffusion of ship pollutant gas according to real-time meteorological data when wind direction, wind speed and other meteorological conditions have changed. This paper presents a fast translational diffusion algorithm, and empirically demonstrates it through ship and meteorological data from the Huangpu River field in Shanghai. First, CO2 emissions were estimated using the actual speed of the ship engine changed under the influence of variable wind, and simulation analysis was performed to the scenario of hourly diffusions. The research findings are as follows: In comparison with the traditional algorithms, the fast algorithm can significantly improve calculation efficiency, save calculation time and achieve the long-distance and long-time parallel calculation of multiple ships. As proven by the empirical research using the ships on Huangpu River in Shanghai, the maximum difference of CO2 emissions is 34.5%, 36.85% and 19.97% respectively after upwind, downwind and real-time meteorological conditions are taken into account. The research finding indicates that wind direction changes have a greater impact on the carbon emission of ships.

A Machine-Learning Approach Based on Attention Mechanism for Significant Wave Height Forecasting

Significant wave height (SWH) is a key parameter for monitoring the state of waves. Accurate and long-term SWH forecasting is significant to maritime shipping and coastal engineering. This study proposes a transformer model based on an attention mechanism to achieve the forecasting of SWHs. The transformer model can capture the contextual information and dependencies between sequences and achieves continuous time series forecasting. Wave scale classification is carried out according to the forecasting results, and the results are compared with gated recurrent unit (GRU) and long short-term memory (LSTM) machine-learning models and the key laboratory of MArine Science and NUmerical Modeling (MASNUM) numerical wave model. The results show that the machine-learning models outperform the MASNUM within 72 h, with the transformer being the best model. For continuous 12 h, 24 h, 36 h, 48 h, 72 h, and 96 h forecasting, the average mean absolute errors (MAEs) of the test sets were, respectively, 0.139 m, 0.186 m, 0.223 m, 0.254 m, 0.302 m, and 0.329 m, and the wave scale classification accuracies were, respectively, 91.1%, 99.4%, 86%, 83.3%, 78.9%, and 77.5%. The experimental results validate that the transformer model can achieve continuous and accurate SWH forecasting, as well as accurate wave scale classification and early warning of waves, providing technical support for wave monitoring.

Humic-like Substances (HULIS) in Ship Engine Emissions: Molecular Composition Effected by Fuel Type, Engine Mode, and Wet Scrubber Usage.

Humic-like substances (HULIS), known for their substantial impact on the atmosphere, are identified in marine diesel engine emissions obtained from five different fuels at two engine loads simulating real world scenarios as well as the application of wet sulfur scrubbers. The HULIS chemical composition is characterized by electrospray ionization (ESI) ultrahigh resolution mass spectrometry and shown to contain partially oxidized alkylated polycyclic aromatic compounds as well as partially oxidized aliphatic compounds, both including abundant nitrogen- and sulfur-containing species, and clearly different to HULIS emitted from biomass burning. Fuel properties such as sulfur content and aromaticity as well as the fuel combustion efficiency and engine mode are reflected in the observed HULIS composition. When the marine diesel engine is operated below the optimum engine settings, e.g., during maneuvering in harbors, HULIS-C emission factors are increased (262-893 mg kg-1), and a higher number of HULIS with a shift toward lower degree of oxidation and higher aromaticity is detected. Additionally, more aromatic and aliphatic CHOS compounds in HULIS were detected, especially for high-sulfur fuel combustion. The application of wet sulfur scrubbers decreased the HULIS-C emission factors by 4-49% but also led to the formation of new HULIS compounds. Overall, our results suggest the consideration of marine diesel engines as a relevant regional source of HULIS emissions.

On-board measurements of OC/EC ratio, mixing state, and light absorption of ship-emitted particles

Carbonaceous aerosols play important roles in environmental impacts and climate effects. The characteristics of ship-emitted carbonaceous aerosols keep unclear under the latest global low sulfur fuel oil policy. This study selected four ocean-going vessels burning low sulfur fuel oils for on-board exhaust testing. The emission factors of ship carbonaceous aerosols were obtained under different engine types (main and auxiliary engines), fuel types, and engine loads. Our results showed that fuel and engine types were both important factors affecting carbonaceous aerosol emissions for ship engines. The emission factors of OC and EC from main engines were 1.18 ± 0.62 and 0.06 ± 0.04 g/kg burning heavy fuel oil (HFO), while 0.52 ± 0.35 and 0.04 ± 0.03 g/kg burning marine gas oil (MGO), respectively. The OC/EC ratios of ship-emitted particles were within a large range of 2 to 23. The OC/EC ratios from the main engines were significantly higher than those from the auxiliary engines by a factor of 6.3. The result of chemical mixing states of ship-emitted particles observed by a single particle mass spectrometer (SPAMS) showed that OC and EC were internally mixed and existed as the ECOC-bonded forms in single particles. The measured light absorption of ship-emitted particles with higher OC/EC ratios showed an evident short-wave absorption enhancement based on the aethalometer AE-33. Our results implied that ship-emitted carbonaceous aerosols (especially with high OC/EC ratios) could not be uniformly treated regarding the optical properties to more precisely estimate their potential environmental impacts and climate effects in model systems in the future.

Heat Exchanger Simulation for Ballast Water Management Based on Ship Size and Engine Capacity

Heat Exchanger Simulation for Ballast Water Management Based on Ship Size and Engine Capacity

The future of ship engines: Renewable fuels and enabling technologies for decarbonization

Shipping is one of the most efficient transportation modes for moving freight globally. International regulations concerning decarbonization and emission reduction goals drive rapid innovations to meet the 2030 and 2050 greenhouse gas reduction targets. The internal combustion engines used for marine vessels are among the most efficient energy conversion systems. Internal combustion engines dominate the propulsion system architectures for marine shipping, and current marine engines will continue to serve for several decades. However, to meet the aggressive goals of low-carbon-intensity shipping, there is an impetus for further efficiency improvement and achieving net zero greenhouse gas emissions. These factors drive the advancements in engine technologies, low-carbon fuels and fueling infrastructure, and emissions control systems. This editorial presents a perspective on the future of ship engines and the role of low-life cycle-carbon-fuels in decarbonizing the marine shipping sector. A selection of zero-carbon, net-zero carbon, and low-lifecycle-carbon-fuels are reviewed. This work focuses on the opportunities and challenges of displacing distillate fossil fuels for decarbonizing marine shipping. Enabling technologies such as next-generation air handling, fuel injection systems, and advanced combustion modes are discussed in the context of their role in the future of low-CO2 intensity shipping.

Optimal Selection of Multi-Fuel Engines for Ships Considering Fuel Price Uncertainty

Maritime transport serves as the backbone of international trade, accounting for more than 90% of global trade. Although maritime transport is cheaper and safer than other modes of transport, it often means long sailing distances, which often results in substantial fuel consumption and emissions. Liner shipping, a vital component of maritime transport, plays an important role in achieving sustainable maritime operations, necessitating the implementation of green liner shipping practices. Therefore, this study formulates a nonlinear integer programming model for a multi-fuel engine selection optimization problem to optimally determine ship order choice in terms of the fuel engine type, fleet deployment, fuel selection, and speed optimization, with the aim of minimizing the total weekly cost containing the weekly investment cost for ship orders and the weekly fuel cost. Given the complexity of solving nonlinear models, several linearization techniques are applied to transform the nonlinear model into a linear model that can be directly solved by Gurobi. To evaluate the performance of the linear model, 20 sets of numerical instances with, at most, seven routes are conducted. The results show that among 20 numerical instances, 16 sets of numerical instances are solved to optimality within two hours. The average gap value of the remaining four sets of numerical instances that cannot be solved to optimality within two hours is 0.51%. Additionally, sensitivity analyses are performed to examine crucial parameters, such as the weekly investment cost for ordering ships, the ship ordering budget, and the potential application of new fuel engine types, thereby exploring managerial insights. In conclusion, our findings indicate that equipping ships with low-sulfur fuel oil engines proves to be the most economical advantageous option in the selected scenarios. Furthermore, ordering ships with low-sulfur fuel, oil + methanol + liquefied natural gas engines, is beneficial when the weekly investment cost for such engines does not exceed $13,000, under the current parameter value setting.

Effect of Performance by Excessive Advanced Fuel Injection Timing on Marine Diesel Engine

The injection timing of fuel in a diesel engine affects the combustion condition. Advanced fuel injection prolongs the ignition delay, positively impacting the increase in maximum combustion pressure and improving output. However, excessively advanced fuel injection can cause knocking. Moreover, premature ignition results in increased compression work when the maximum combustion pressure occurs before top dead center (TDC). This study aimed to diagnose and rectify starting failures, noise, and vibrations in a commercially operated ship engine by measuring the combustion pressure during low load operation. The target engine was a 4-stroke diesel, and the fuel injection system was mechanically controlled by a camshaft. The measured engine exhibited a 4.5 °CA error between the TDC, determined by the flywheel mark and the actual TDC. This discrepancy was influenced by excessively advanced fuel injection timing. It was confirmed that fuel injection and ignition were excessively advanced in all cylinders. After readjusting the engine by delaying the fuel injection timing by approximately 10 °CA, the combustion pressure was remeasured. The ignition was delayed by approximately 6.5 °CA at the same load, and the ignition intervals were uniformly adjusted. As the ignition timing was retarded, the compression work decreased and the expansion work increased in each cylinder, resulting in improved output across all cylinders. The amplitude of crankshaft angular velocity variation significantly decreased, improving uneven rotational force.

Emission characteristics of naphthalene from ship exhausts under global sulfur cap

The global sulfur limit regulation mandates the use of 0.5 % low sulfur fuel oil (LSFO) to reduce emissions of sulfur oxides (SOx), nitrogen oxides (NOx), and particulate matter (PM). However, the addition of naphthalene (Nap) to LSFO to stabilize its quality has led to an increase in polycyclic aromatic hydrocarbons (PAHs), with Nap being the main pollutant. This study investigates the effects of Nap in ship exhaust by analyzing the emission concentrations of volatile organic compounds (VOCs) and Nap in the exhaust of 16 ships, including 2 container ships, 6 bulk carriers, 1 tanker, 2 ferries, 3 fishing vessels, and 2 harbor crafts, based on USEPA method TO-15A. The results show that the percentage of Nap emissions in the exhaust gases of the 16 ship engines ranged from 77 % to 97 % of the total volatile organic compound (TVOC). The Nap concentration in the exhaust of fishing vessels, tanker, and harbor craft exceeded the occupational exposure limit of 50,000 μg/m3, with fishing vessels having the highest TVOC and Nap concentrations. The enhanced Nap emission in the air degrades air quality in port cities and poses an obvious potential public health risk. While the benefits of the global sulfur cap are being secured, additional efforts should be made to reduce the undetected side effects. Alternative stabilizers of LSFO should be considered, or Nap emission control should be boosted to mitigate the potential negative impact on harbor air quality.

Design of flipped classroom lesson in educational electronic environment of maritime higher education institutions

Online classes (due to COVID, and then because of the war in Ukraine) require the teacher to make constant changes and to use new forms and methods of learning so that students feel free and more independent. Such a learning model as the flipped class is a type of mixed learning, the peculiarity of which is that students work on new educational material at home and consolidate what they have learned in class by performing practical tasks on the topic. The research aims to describe the process of creation and implementation of flipped classroom lessons for ship engineering cadets of a modern maritime higher education institution. The following methods were used in the research: observation, study of practical experience, verification of creative works and application of tests. The example of a flipped classroom lesson on the Learning Management System platform MOODLE is presented in the article. The priority of such lessons is to redesign the learning model so that the cadets are familiar with new material before class. The set of examples of activities that motivate cadets to get ready before class are given. Fourth-year cadets of the ship engineering department of Kherson State Maritime Academy, Ukraine are the main participants of the experiment. The formation of competence regarding Maritime English using a flipped classroom was analysed. The article presents and substantiates the results of the experiment, confirming the positive influence of flipped classrooms on the communicative competence of future ship engineers. It is shown that, using the flipped classroom the teacher gets the opportunity to work with each student individually and immediately focus on the performance of practical tasks; each student can independently, at the necessary pace, review the material, which is available at any time (for those who attended the class, and for those who were absent for some reason). The practical significance of the article is that it demonstrates how the new pedagogical model allows for increased active learning opportunities for cadets of the ship engineering department.

Aligning the Ship Engine Cadets’ Skills to the 21st Century

The Philippines is one of the single largest nationality groups in the maritime and shipping sectors; as a result, the nation's efforts to modernize the skills of the engine cadets are significant. This study aimed to assess the engine cadets' skill level in relation to the requisite 21st-century skills while they were receiving shipboard training at TORM Shipping Philippines Inc. It used a sequential explanatory mixed-methods design. The paper used mean, standard deviation, and Mann-Whitney for comparing differences between two independent groups for the statistical treatment analyses of the quantitative data. Thematic analysis of the descriptive data provided by the interviewees involved coding and identifying common themes, patterns, and responses. The findings revealed that the engine cadets were competent in three (3) areas but needed to be more competent in the remaining area (inventive thinking). This signified that the engine cadets need supplemental training in the areas where they are less apt to improve their skills in all variables, especially 21st-century skills. The management of maritime schools and policymakers must address the common factors that prevent engine cadets from acquiring 21st-century skills, according to the study.

Data-driven condition monitoring of two-stroke marine diesel engine piston rings with machine learning

ABSTRACT Maintaining the condition of a vessel and its equipment guarantees the scheduled completion of voyages and the safety of the crew. This paper presents condition monitoring techniques for early detection of faults related to piston rings in remote cylinders of two-stroke marine diesel engines. Operational sensor data from the main engine of a container ship are provided by a shipping company. A graphical approach complimented by correlation heatmaps and feature importance from gradient boosting trees are used for feature selection. Support Vector Machine, Random Forest and Extreme Gradient Boosting Trees are tested for residual generation from the nominal behavior. The residual time series gives a good indication of the degradation of the system and can be used for alarm raising under strict rules. It is proven that the proposed method could alert the engine crew of a change in the condition of the piston rings much earlier than existing methods.

Fire Detection in Ship Engine Rooms Based on Deep Learning.

Ship fires are one of the main factors that endanger the safety of ships; because the ship is far away from land, the fire can be difficult to extinguish and could often cause huge losses. The engine room has many pieces of equipment and is the principal place of fire; however, due to its complex internal environment, it can bring many difficulties to the task of fire detection. The traditional detection methods have their own limitations, but fire detection using deep learning technology has the characteristics of high detection speed and accuracy. In this paper, we improve the YOLOv7-tiny model to enhance its detection performance. Firstly, partial convolution (PConv) and coordinate attention (CA) mechanisms are introduced into the model to improve its detection speed and feature extraction ability. Then, SIoU is used as a loss function to accelerate the model's convergence and improve accuracy. Finally, the experimental results on the dataset of the ship engine room fire made by us shows that the mAP@0.5 of the improved model is increased by 2.6%, and the speed is increased by 10 fps, which can meet the needs of engine room fire detection.