In this study, the maneuvering forces and moments of the DARPA Suboff submarine model were determined under static drift condition using computational fluid dynamics (CFD) methods. Two different configurations of the submarine model namely; the AFF-3 configuration, which consists of bare hull and four stern rudders, and the fully appended configuration AFF-8, which is formed from bare hull, sail, and four stern rudders, have been used. Initially, for the AFF-3 configuration, a mesh independence study has been conducted. Three different cases; coarse, medium and fine meshes are investigated at small angles (0-2-4-6 degrees). After that the results have been verified, the medium mesh structure has been selected and the analyzes have been continued for larger angles (from 00 to 180 degrees). The accuracy of the obtained results was assessed by comparing them with non-dimensional experimental results. The comparison between the CFD results and the experimental results demonstrated a high level of agreement, indicating the effectiveness and accuracy of the CFD methods used in this study. After the validation studies, the maneuvering forces and moments of the AFF-8 fully appended configuration were calculated for which no prior experimental data existed in the literature. To achieve this, steady-state CFD simulations were performed using the commercial software ANSYS Fluent, and the results were presented for the same flow angles.

Since its inception, the coronavirus pandemic has caused serious social, economic, and health problems around the world. Seafarers have been identified as key workers in mitigating the negative impact of the coronavirus on global trade and ensuring the delivery of medical and hygiene supplies to regions in need. However, the complete closure policies implemented by certain countries have led to prolonged periods on board for seafarers with expired contracts and economic hardship for those unable to join new assignments. Seafarers who spend long periods on board a ship must deal with issues that may affect their psychological state. Therefore, it is important to identify the factors that cause seafarers to experience psychological distress and to develop relevant strategies to address them. The aim of this study was to determine the association between seafarers’ fear of coronavirus disease-2019 (COVID-19) and psychological distress including symptoms of anxiety, depression, and stress. The questionnaire used the fear of COVID-19 Scale and the expression, Anxiety and Stress Scale), which have strong psychometric properties. Data were collected from 425 qualified seafarers working on international merchant ships and analyzed by structural equation modeling using AMOS-24. The results indicate that seafarers’ fear of COVID-19 is positively associated with symptoms of anxiety and stress but not with depression. Maritime companies, sectoral organizations, and policymakers should collaborate to reduce these associations among seafarers. A unified management approach improved access to health services, and regular mental health assessments can be effective solutions.

Carrier selection is a complicated problem as it includes many quantitative and qualitative criteria. Due to the complexity of this issue, many criteria that influence decision making interact with each other, making it necessary to consider these interactions in order to make the best decision. The analytical network process (ANP) method enables us to solve the carrier selection problem of decision making more effectively and realistically. This study, which aims to contribute to the research field, employs the previously unused ANP method, which permits criteria interaction, and investigates the carrier selection problem in order to determine the similarities and differences between different industries’ expectations of ocean container carriers. In this context, this study has been applied in three different industries: textiles, white goods, and chemicals. In this way, the study contributes to the literature on ocean container carriers. From the results, the most important criterion for the three shipper groups was found to be reliability. However, there were significant differences in the ranking of other criteria.

In engineering problems, the concepts of design and optimization are two basic topics that are related to each other. The problem owner should prioritize the design or optimization on each other. In this regard, two different ways can be followed in engineering problems: firstly designing and then optimizing or using optimized parameters in the design process. In this study, the basic design parameters of a capesize bulk carrier for a specific purpose were created and exemplified on a model. The prototype development problem is handled as a multi-criteria optimization problem by creating appropriate and pareto optimal solutions. Parameter Space Investigation method was used to solve this optimization problem, and this method was applied in a program called Multi-criteria Optimization Vector Identification. As a result of the study, the design parameters of the capesize bulk carrier sample were created and the objective function criteria were obtained better than the prototype and the value in the literature.

This study investigates the cognitive levels of tugboat captains, key players during port manoeuvres, which are a crucial part of sea navigation. The objective is to reveal the main neurophysiological findings related to the measurements of the tugboat captains’ brain activity during both rest and actual manoeuvring performance and to investigate the relationship between this brain activity and situational awareness. The study employed an experimental research method. Brain waves of the tugboat captains were recorded using the Emotiv X EEG device and the Emotiv Pro v2.0 program during real port manoeuvres which is a part of the sea navigation. Situational awareness levels were tried to be determined by analysing the obtained values in the Brain Products Vision Analyzer 2.1 software. The study examined the cognitive states of four tugboat captains during 16 manoeuvres and resting, focusing on the Fast Fourier Transform (FFT)/Band power graph values. Within the scope of the research non-parametric Friedman Test with five variables [Resting State (RS), 1st Manoeuvre Group, 2nd Manoeuvre Group, 3rd Manoeuvre Group, and 4th Manoeuvre Group] to analyse the FFT values of the participants. Post-hoc comparisons were calculated using Bonferroni correction. The results showed no difference in alpha wave power, while delta, theta, beta, and gamma power decreased. The primary outcome of the research indicates that professional tugboat captains, who were the participants of the study, exhibited consistent situational awareness levels both during manoeuvring and resting moments.

Cargo unloading operations on bulk carriers are critical shipboard operations. Many tasks are expected to fulfill by the ship’s personnel to safely complete this type of operation. However, many human errors may occur during this process, and this situation threatens the safety of life and property. In this respect, this study predicts potential human errors and probabilities that may occur during cargo unloading operations on bulk carrier ships. In this study, an integrated human error prediction approach is proposed using interval type 2 fuzzy sets and the success likelihood index method. Thus, within the scope of this study, a model was obtained that allows human errors to be evaluated both qualitatively and quantitatively. Because of the analyzes made, it has been found that the most common human errors that occur while unloading cargo operations on bulk carriers occur in the processes of following the ballast operation and performing the tasks to prevent excessive trim/list formation on board ship, respectively. In addition, it was concluded that the factors that most shape the performance of the ship’s personnel are education, communication, and experience.

This work is a preliminary dielectric relaxation time distribution analysis of several fresh and used marine engine oils that have not previously been examined for degradation with relaxation time distribution. The correlation of the distribution of relaxation times with other characteristics of oils, particularly the content of additives and wear products, was analyzed. The obtained results can be useful in the development of instrumentation for express diagnostics of the engine. The proposed mechanism for describing the dielectric spectrum using the relaxation time distribution can provide a meaningful interpretation of the processes at the molecular level. Information about the frequency measurements of permittivity can be used in various applied research.

This project aims to provide a novel and compact pollution detection, monitoring, and analysis system architecture to monitor marine fields and detect different types of marine pollution that includes hardware and software components. The system will mainly consist of a Shore Control Centre (SCC) and unmanned surface vessels, both equipped with multi-sensor technology and artificial intelligence-based solutions. The SCC will play a key role as a central network hub of the system.