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ÖgeA quantitative approach on human factor analysis in maritime operations(Lisansüstü Eğitim Enstitüsü, 2021)The maritime authorities and international organizations have taken the issue of the pivotal role of the human element and its contribution to the safety of ship operations very seriously due to the growing global concern over maritime disasters. At this point, that at least 80 per cent of shipping casualties are related to the human element is underpinned by the conducted studies and investigation reports published by organizations such as IMO (International Maritime Organization), ILO (International Labour Organization) and experts in the field. Despite the economic and technological improvements, since tragic events had caused the worst environmental disasters in recent years, never has the human element been so crucial in the safe operation of ships. However, although the issue of human contribution to unsafe shipboard operations needs to be the focal point of the researches, there has not been a qualified novel study that can meet the gap of the maritime transportation industry. The purpose of this thesis is to develop a uniquely quantitative approach to evaluate the human error probabilities (HEPs) and to analyse the increasing operational risks due to human errors. In this context, a hybrid approach incorporating Fault Tree Analysis (FTA) and Interval type-2 fuzzy-based Success Likelihood Index Method (SLIM) is developed. The approach, additionally contributing to current human error probability assessment methods in academic literature, is applicable to all shipboard operations regardless of vessel type. With the study under this thesis, it is predicted to provide supportive guidance that enables shipping companies to undertake the early detection of unsafe cargo operations before they get out of control. With the risk assessment concentrated on the concept of the human-related operational failure by implementing the hybrid approach, system vulnerabilities that could result in an undesired event are considerably detected and the awareness in shipping safety management is increased. It is also predicted to reach solid targets by providing both qualitative and quantitative data to maritime container transportation safety as well as an insight into what measures may be necessary to reduce future losses. A hybrid approach that differs from a traditional HEP assessment, suitable customization to containership platform, a methodology that involves key risk and performance shaping factors (PSFs) based on the literature, industry standards, technical knowledge of marine experts and analysis of marine accident investigation reports, increased consistency in expert judgements, and analysis of the root causes of major risks to operational safety can be mentioned as original aspects of the thesis. Implementation of management of human error probability analysis integrating with risk analysis will provide a consistent tool for the maritime industry. As a result, the study offering proactive solutions to related issue of unsafe shipboard operations that closely related to both economic and environmental aspects of the maritime transportation industry will provide tangible contributions for enhancing safety.
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ÖgeA quantitative approach on human factor analysis in maritime operations(Lisansüstü Eğitim Enstitüsü, 2021)The maritime authorities and international organizations have taken the issue of the pivotal role of the human element and its contribution to the safety of ship operations very seriously due to the growing global concern over maritime disasters. At this point, that at least 80 per cent of shipping casualties are related to the human element is underpinned by the conducted studies and investigation reports published by organizations such as IMO (International Maritime Organization), ILO (International Labour Organization) and experts in the field. Despite the economic and technological improvements, since tragic events had caused the worst environmental disasters in recent years, never has the human element been so crucial in the safe operation of ships. However, although the issue of human contribution to unsafe shipboard operations needs to be the focal point of the researches, there has not been a qualified novel study that can meet the gap of the maritime transportation industry. The purpose of this thesis is to develop a uniquely quantitative approach to evaluate the human error probabilities (HEPs) and to analyse the increasing operational risks due to human errors. In this context, a hybrid approach incorporating Fault Tree Analysis (FTA) and Interval type-2 fuzzy-based Success Likelihood Index Method (SLIM) is developed. The approach, additionally contributing to current human error probability assessment methods in academic literature, is applicable to all shipboard operations regardless of vessel type. With the study under this thesis, it is predicted to provide supportive guidance that enables shipping companies to undertake the early detection of unsafe cargo operations before they get out of control. With the risk assessment concentrated on the concept of the human-related operational failure by implementing the hybrid approach, system vulnerabilities that could result in an undesired event are considerably detected and the awareness in shipping safety management is increased. It is also predicted to reach solid targets by providing both qualitative and quantitative data to maritime container transportation safety as well as an insight into what measures may be necessary to reduce future losses. A hybrid approach that differs from a traditional HEP assessment, suitable customization to containership platform, a methodology that involves key risk and performance shaping factors (PSFs) based on the literature, industry standards, technical knowledge of marine experts and analysis of marine accident investigation reports, increased consistency in expert judgements, and analysis of the root causes of major risks to operational safety can be mentioned as original aspects of the thesis. Implementation of management of human error probability analysis integrating with risk analysis will provide a consistent tool for the maritime industry. As a result, the study offering proactive solutions to related issue of unsafe shipboard operations that closely related to both economic and environmental aspects of the maritime transportation industry will provide tangible contributions for enhancing safety.
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ÖgeModelling departure time, destination and travel mode choices by using the generalized nested logit model: an example for discretionary trips( 2020)Nowadays, understanding the influences of different temporal and spatial factors on individuals' travel choices becomes essential especially after the pandemic of COVID-19 that invaded the world in 2020. Such an outbreak had its own influences on the future transportation planning studies. By words, policy makers have directed their interests toward newly emergency transportation policies that aim to distribute travels over wider time and space spans in accordance with precautionary and preventive measures to counteract Corona virus or any other similar future virus attacks. However, transportation planning studies still rely on traditional demand modelling approaches such as the four-step model. The four-step model is still exposed to considerable criticism for its shortages in representing the potential correlations between temporal, spatial factors and different travel dimensions which leads to inaccurate representations of individuals' actual travel behaviour. In order to overcome that, some researches have directed their interests toward using choice modelling approach as an alternative to some stages in four-step model. Even though these approaches show better performance in terms of goodness of fit and predictability power, most of them have represented travel dimensions individually rather than jointly. As there is a gap in literature about representing a unified choice model that connect different travel demand dimensions and consider various potential inter-correlation among them, this dissertation contributes filling this gap through introducing three research papers that employ various types of discrete choice models for jointly representing three major travel dimensions; destination, departure time and travel mode. Such models contribute more to mathematical modelling literature of transportation demand models that provide more detailed and specific micro-policy analyses where traditional four-step model cannot. The presented papers introduce three discrete choice models that differ in the level of accounting for correlation of error terms within elementary alternatives and therefore differ in cross-elasticity pattern while offering computational simplicity. In the first paper, limited number of correlation patterns is introduced by adopting the three-level Nested Logit (NL) models. In the second paper, opposite to traditional NL models that was introduced in previous paper, this paper assesses the effect of considering spatial correlation of adjacent discretionary destinations on the choice of the two other travel dimensions by using the Ordered Generalized Extreme Value (OGEV) approach. The third paper, introduces a novel modelling methodology for using the Generalized Nested Logit (GNL) model to represent multi-dimensional potential correlations; between different travel dimensions (inter-correlation), inside the same travel dimension (inner-correlation) and correlation due to ordered nature travel dimensions (e.g. spatial correlation among destinations and temporal correlation between departure times). Overall, in the published papers, different levels of correlation between departure time, destination and travel mode choices and within each travel dimension are represented through different assumed correlation structures according to the nesting structure limitations provided by each model. Moreover, the associated formulas for each proposed model that reflect different patterns of correlation (cross-elasticity) are explicitly introduced. From a policy implications standpoint, a calibrated version of departure time, destination and travel mode model will provide policy makers very detailed analyses about the inter-relationships associated with the three travel dimensions (while traditional four-step model cannot provide at micro-level). That leads to more certain, specific, efficient and precise policy decisions. Thus, developing these models can be considered as a significant milestone toward obtaining a consistent, efficient and integrated full-scale model that can lie in all travel demand dimensions (e.g. number and duration of activities for activity and tour-based models). The developed models have been estimated and calibrated by using shopping and entertainment trips data of Eskisehir city, Turkey. The data have been collected through a household survey that was conducted in 2015 in the context of Eskisehir strategic master plan project which was operated by Eskisehir Metropolitan Municipality. Eskisehir is a city in north-western Turkey. It is considered as a medium sized city with a population of 799724 (2013 census) distributed over about 2678 km2 area. The collected data include variables that represent attributes of alternatives and individuals' characteristics to be used in models' utility functions. The first group of alternatives' attributes is travel time related attributes where, in vehicle time and out of vehicle time (egress time, at stop waiting time and access time) for each individual trip have been obtained. Moreover, related to travel cost, the fare of public transportation modes (for public transportation users), trip cost for private cars as well as parking fees (for private car users) have been observed for each individual trip. Within the collected revealed data, a good portion of socio-economic individual characteristics related observations are presented. These data include car ownership, individual's age, monthly income and student status (if respondent is a student or not). The total number of observations related to the determined alternatives has been found to be 529. The estimation results of each model have been explicitly interpreted in each paper and logical as well as statistical comparisons between pairs of models have been conducted in order to ensure the superiority of more advanced approaches (OGEV and GNL) over the lesser ones (NL). In the light of the estimation results, generally, individuals have been found to jointly decide on "at which departure time", "to which destination" and "by which mode" rather than doing this separately as assumed by traditional four-step model. Neglecting the potential correlation among alternatives of the three travel dimensions has led to inaccurate estimates of measurements' indicators such as Value of Time (VOT) which results finally in incorrect and improper policy decisions. From another hand gradual improvements in predictability have been observed as the level of the represented correlation increases. That is, three-level NL model was found to offer improvements over Multinomial Logit (MNL) model, OGEV model is prominent over NL model and GNL is superior over all models. It is possible to argue that the proposed GNL approach has distinct improvements over all other proposed approaches. Its simplicity along with the incomparable flexibility in representing a lot of correlation patterns within and among three vital travel dimensions all of that under a unified modest model qualify it to be prominent. The proposed GNL model has provided very detailed analyses about the inter-dependencies associated with various departure times, travel modes and discretionary destinations where other models cannot. The estimation results have expressed the powerful analytical ability of the proposed GNL approach where it has the power of capturing unusual correlation patterns. These patterns are thoroughly specific, unexpected, and very difficult to be observed in the market. By words, the dissertation argues that there is no other approach as simple as the proposed GNL and leads to such temporal and spatial specific analyses. The advantages associated with the proposed GNL approach qualify it to be a strong peer to the traditional four-step model in micro-disaggregate modelling scopes if applied for medium and small-scale planning studies that involve limited number of alternatives in each travel dimension. It may be used with a large number of alternatives in each travel dimensions as well, however, through stratifying the whole population to small segments based on one or more travel dimensions to produce small segments suitable for readily estimation process. Finally, the proposed GNL methodology represents a time of day-based trip-end distribution model that can reproduce a considerably more accurate transportation mode based origin-destination matrix dependent on time of day. Moreover, unlike traditional four-step models, parameter estimates produced from the GNL model can provide significant indications which precisely reflect the individuals' actual behaviour. Obviously, that can enormously help policy makers to reach a solid perception about the effects of applying various strategies to manage demands through different times of day and towards different destinations.
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ÖgeFuzzy logic system applied to the optimization of BWMS with emphasis on stakeholders' management( 2020)The International Convention for the Control and Management of Ships' Ballast Water and Sediments (IMO, 2018 Edition) was adopted in 2004 and came into force on 8 September 2017, aiming to produce global regulations to monitor and control the transfer of potentially invasive species. Large efforts have been made by the maritime industry in creating reliable strategies for the installation of systems on board (Register, 2014). Environmental considerations (INTERTANKO, 2018) and optimization of the management systems (IMO, 2017 Report) are the main factors considered to tackle this matter. These factors are translated into a wide range of solutions for retrofitting and new building services, which is evidenced through the substantial amount of data disclosed and analyzed by different parties showing that optimization processes will have an important role for management systems. The analysis of a BWMS project in terms of implementation involves a series of requests in both the initial and concept phases, which are operationally and technically based. The project feasibility, as the market becomes more competitive, is a major aspect to managing projects of this order with the highest levels of monitoring and process control. At a time when engineering processes are reliant on large sources of data, and multienvironmental constraints cannot be neglected, consistent analysis must be studied and applied in the maritime industry. The project management, on the sub field of stakeholders' management, (Bourne, 2016) brings a myriad of shipping agents connected to ballast water management matters with different levels of knowledge, experience and commitment - according to the engineering perspective. From an engineering perspective, categorizing the agents involved and assessing the outcomes are important matters. The stakeholders' expertise is considered at the BWM Convention and its amendments set an important call, in terms of deliverables, to the industry. Avoiding any delay in operation is not the only answer to this call; setting up an optimized and sustainable operation after the installation project for a BWMS is also important. A consistent implementation strategy must be stated before the BWM system installation project starts – the management of stakeholders' is an important aspect of this process. This relies on their expertise, which in turn results in a high level of engagement and supports the implementation plan into the organizations. Another aspect to be taken into account for this analysis is the oil tankers' unique characteristics of purpose and operation, which can be amplified by their hazardous atmosphere. This brings the application of specific classification areas and explosion proof to the system to be installed on board. In this thesis, this type of vessel isxxii highlighted, due to its high levels of regulation, compared to other segments, for example, bulk carriers. In the introduction, the establishment of a framework of management systems to be optimized, with the location of the main constraints, is addressed. Frameworking the process doesn't mean restricting the process, as the research is a dynamic entity, subject to revisions as the investigation advances. The framework provides an understanding of the research and the overall picture as to what it includes and where it starts and finishes. The study of the technical solutions for the management systems available is the first objective of the data analysis in this thesis. Understanding how the makers are presenting solutions according to the BWM Convention is important, because most of the consultants in the market are presenting their analysis for installation based on rankings offered by the same range of data (IMO provides a list of final approved makers). As the research progressed, the stakeholders' management analysis became the main point, where the expertise of the key stakeholders about the BWM Convention is measured, analyzed and translated into a group of coefficients, which are central to the optimization process. The data analyzed was obtained from a series of interviews made from January/2019 to August/2019. Then, the use of Fuzzy Logic principles (Mamdani) – as an instrument of evaluation from the rankings obtained by multi-criteria analysis (from the database of makers) accomplishes the main objective of this thesis, where the peculiarities about oil tankers' modelling are demonstrated through the analysis of 2 optimization case studies (Suezmax and Aframax)
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ÖgeDevelopment of a dynamic navigational risk assessment model( 2020)Marine traffic, which has an increasing importance in terms of global freight and passenger transportation, has increased significantly in recent years and has brought some navigational safety problems. An increase was observed especially in collision and grounding accidents in especially dense waterways. In order to find solutions to this problem, many academic studies have been carried out that offer different sights and analysis methods. In the literature review stage made within the scope of the thesis, the studies on the subject were examined in detail, the factors included to calculations, the methods utilised and their applicability to the solution of the problem were evaluated. Although the studies in the literature constitute an academic value in terms of their proposed methods and approaches, it has been evaluated that many of them are insufficient in terms of applicability, namely the solution of the problem faced by the industry. As a matter of fact, there is no real-time dynamic risk analysis algorithm that can work onboard ship which is capable of corresponding the needs of the industry. In addition, many studies in the literature do not seem to address both the risks of collision and grounding at the same time. Studies in which only collision or grounding risk analysis was presented could not fully meet the expectations of the maritime sector. For this reason, it is aimed to develop a real-time dynamic risk analysis algorithm with some novel and strong aspects which can provide decision support to the officer on watch, can work integrated with real navigational equipment. The proposed algorithm consists of 4 main stages as Automatic Identification System (AIS) Module where AIS data are decode and parsed, Electronic Navigational Chart (ENC) Module that allows reading ENCs, Calculation Module where all risks and other required calculations are performed, and Visualisation Module where risk indicators are projected with AIS targets over the visualized ENCs. The National Marine Electronics Association (NMEA) 0183 infrastructure, which is the standard data exchange protocol of ship navigation equipment, has been added to the algorithm so that it can be integrated to navigation equipment for real-time calculations. All of the factors obtained from integrated navigation equipment used as data source and which may affect the risk of collision and grounding were included directly or indirectly as inputs. Information of Closest Point of Approach (CPA), Time to Closest Point of Approach (TCPA), relative bearing, relative speed, ship's length and ship's type are determined as the system inputs of the algorithm. Own ship and target ships perceived with AIS data are not considered as a single point as in the classical approaches in the literature. Instead, the actual dimensions of the ships are calculated by considering the position information of the Global Positioning System (GPS) receiver sent by OTS on the ship. Ship forms created in real dimensions are perceived as a set of multi-points consisting of points in which a distance of less than 10 meters between each one, and risk calculations of collision is carried out in real time by including all of these points in consideration. Similarly, shallow contour information obtained using ENC, which is dangerous in terms of vessel draft value, is perceived as a set of multi-points with a distance of less than 10 meters between them. Risk calculations have been conducted with the Fuzzy Inference System (FIS) method, which is widely used as one of artificial intelligence methods, from medicine to many branches of engineering. A case study was carried out by applying the AIS data of a ship navigating in the Istanbul Strait to the model. In this study, it is aimed to develop a model to reduce the risks of collision and grounding by increasing situational awareness and thus providing a decision support.