In the domain of Marine Education and Training (MET), simulators have been utilized for the purpose of training seafarers in the norms for avoiding collisions or for developing the skill of ship manoeuvrability, and even the operation of machinery in the engine room, as well as for conducting research on the subject matter of ship structure, specialized vessel operation, working principle of equipment, and shipboard safety training. These tools are even more important when facing disruptive events such as the COVID-19 pandemic. In MET institutions, full-mission bridge and engine room simulators have been utilized for teaching seafarers for more than a decade. A Systematic Literature Review (SLR) was conducted to identify immersive and non-immersive simulator applications produced over the previous ten years to improve seafarers’ experiential teaching and learning, in the maritime domain. We retrieved 27 articles using the four stages of PRISMA paradigm: Identification, Screening, Eligibility, and Inclusion. The selected papers were read and analyzed according to the training type, the area of training, and the technologies used. The utilization of immersive and non-immersive simulators in the context of the MET domain has been identified and mapped. A few research studies (9 out of 27) compared immersive and non-immersive simulator-based training with conventional training. The quality and efficacy of immersive and non-immersive simulator training at MET institutions have been studied. A model from the learner’s perspective is essential and recommended for future research to assess efficiency and efficacy.

This study deals with an artificial neural network (ANN) modelling of a marine diesel engine to predict the brake power, output torque, brake specific fuel consumption, brake thermal efficiency and volumetric efficiency. The input data for network training was gathered from engine laboratory testing running at various engine speed. The prediction model was developed based on standard back-propagation Levenberg-Marquardt training algorithm. The performance of the model was validated by comparing the prediction data sets with the measured experiment data. Results showed that the ANN model provided good agreement with the experimental data with high accuracy.

Demand for low carbon emissions in the shipping sector has prompted alternative energy sources to reduce dependence on diesel petroleum for day-to-day operations. Biodiesel fuel has been identified as one of the alternative energy sources that can be used in marine engines. Biodiesel is a plant-based fuel, environmentally friendly, renewable, non-toxic and oxygenated. Despite having many advantages, it nevertheless contributes to a slight reduction in engine power due to its low energy content compared to diesel fuel. Therefore, this study aims to evaluate the effect of using different types of nanoparticle additives with different concentrations on the properties of biodiesel fuel. Nine test samples were prepared by blending B20 palm methyl ester biodiesel fuel with aluminium oxide (Al2O3), silicon dioxide (SiO2) and titanium dioxide (TiO2) nanoparticle by different concentrations of 50 ppm, 100 ppm and 150 ppm. Several series of fuel property tests were performed on the samples including density, viscosity, calorific value, scanning electron microscope (SEM) and X-ray diffraction (XRD). The test results showed that, the caloric value of B20 biodiesel fuel was increased from 44747 J/g to 45122 J/g, 45090 J/g and 45110 J/g with the addition of Al2O3, SiO2 and TiO2 nanoparticle, respectively. The viscosity and density properties have also improved with the highest values found on the SiO2 blend of 3.7792 mm2/s and 820.36 kg/m3. The morphology study revealed that the structure of nanoparticles is in an amorphous state which is expected to contribute a large contact area, good stability and catalytic with a high combustion rate of blend fuel. All of these advantages are expected to contribute as a good catalyst to biodiesel fuel in order to produce optimal combustion of marine diesel engines and further reduce harmful gas emissions

Navigational safety necessitates careful route monitoring, which includes staying on the planned course. For a ship to achieve effective route monitoring while changing course, a wheel over point (WOP) must be precisely calculated and marked on a charted course. The reason is to warn the watchkeeping officer that the ship must make a course alteration to prevent overshooting the intended route. One of the techniques for appraising the WOP is the advance transfer technique (ATT). During a practical review by means of an electronic and paper chart work exercise of the ATT, this study discovered two research gaps related to the technique. Following that, this study created an improved advance transfer mathematical model (ATMM) by restructuring the use of the ship’s turning circle to overcome the limitations discovered. To validate the improvement of the ATMM over the ATT, data were collected by evaluating both methods using a ship simulator and performing a manoeuvring analysis. The data, specifically the reduction in the cross-track distance (XTD), was validated in three verification stages: compliance with XTL, percentage change, and Mann‒Whitney U test using IBM SPSS. In comparison to the ATT, the ATMM produces better results in terms of the course-keeping capability and it can be implemented as an algorithm in an integrated bridge navigation system for autonomous ship navigation safety.

Shipping activities are major contributors to air pollution at sea which mostly occur as a result of ships exhaust emissions. Stringent emission limits imposed by the International Maritime Organization (IMO) and concerns about the depletion of fossil fuel reserves have hastened the need to find new alternative fuels for marine engines. This study investigates the effects of a low proportion of palm fatty acid methyl ester (PFAME) biodiesel which is renewable and environmentally friendly fuel on marine diesel engines performance and combustion characteristics. The results revealed the use of PFAME biodiesel blends reduces the harmful gases emission CO2 and NOx emission up to 9.1% and 7.8%, respectively. Oxygen elements in biodiesel has contributed to increase peak in-cylinder pressure and heat release rate up to 2.7% and 4.5% respectively, thereby promoting complete combustion. Besides that, the brake specific fuel consumption raised by 18.8% at higher engine speeds. This finding suggests that a low concentration of PFAME biodiesel is suitable for use in marine diesel engines without engine modification, thereby providing a positive benefit to the environment in terms of lower emission of toxic gases.

Software applications to solve engineering problems and performance issues of marine diesel engines are becoming easier in current trends due to the rapid development of technology and computer science. However, the cost of software kits for users is very high and burdensome, especially for researchers in developing countries. Alternatively, Diesel-RK software is an open-source program created to help researchers in modelling and making predictions on the performance and exhaust emissions of a diesel engine. Therefore, this work presents the results of the Diesel-RK application for simulating performance, emissions, and the capability of use of another type of diesel by marine diesel engines of 4-cycle-inlined 6-cylinder, and suggests the best type of diesel fuel for testing on an actual marine engine. Different types of diesel fuel, such as Light Fuel Oil 1 (LFO-1), Diesel No. 2, EN590, and Heavy Fuel Oil, were tested in this simulation. The engine performance and emission parameters, such as brake power, torque, specific fuel consumption, thermal efficiency, Nitrogen Oxide (NOx) emissions, and Carbon Dioxide (CO2) emissions, were analysed. The research indicated that utilising EN590 fuel resulted in enhanced marine diesel engine performance, including improved brake power, torque, thermal efficiency, and fuel consumption. Moreover, EN590 fuel exhibited significantly reduced NOx and CO2 emissions compared to Diesel No.2, LFO-1, and Heavy Fuel, offering valuable guidance for both simulation and practical engine studies.