Marine Accident Analysis Research Articles

A marine accident analysis based on data-driven Bayesian network considering weather conditions and its application to Taiwanese waters

Few marine accident studies contemplate the weather effects on the places where and dates when shipping casualties occur. This study conducts a marine accident analysis based on Bayesian Network (BN) considering the weather characteristics of the accident spots and occurrence dates. The weather element is adopted as a node in the BN that comprises a group of five clusters illustrating the states of current speed, wave height and wind speed. A total of 431 accidents occurring in the western coast of Taiwan during the period from 2014 to 2022 are analyzed. Wave with height greater than slight sea has a certain effect on the accident frequency and severity. Mishaps are likely to suffer severe consequences if encountering the weather conditions featured by strong current, moderate/fresh breeze and slight/moderate sea. In addition, Accident Type is the most influential node of Accident Severity among the parameters, followed by Ship Type, Gross Tonnage (GT), Weather Cluster, Location and Ship Age. Finally, the three most crucial parameters leading to Very Serious Marine Casualty are Accident Type, Ship Type and GT.

A machine learning-based data-driven method for risk analysis of marine accidents

In view of the frequent occurrence of marine accidents and the complex interaction of various risk-influencing factors (RIFs), a data-driven method to risk analysis that combines association rule mining (ARM) and complex network (CN) analysis is proposed in this study. The efficient FP-Growth algorithm is applied to facilitate ARM to examine risk patterns that frequently occur in marine accidents. Subsequently, CN theory is employed to scrutinise the multifaceted role of various RIFs and their interactions in the complex marine accident system, which involves the basic characteristics of the network, the identification of key RIFs through the application of the weighted LeaderRank (WLR) algorithm, and a robustness analysis. The results of the study indicate that compared with random networks, marine accident networks exhibit a higher level of complexity, which brings challenges to safety prevention and control. Inadequate regulation, violations, and deficiencies in safety management systems are identified as key RIFs, stressing the urgency of improving supervision, strengthening law enforcement and strengthening the safety management system. This study may facilitate maritime safety management of maritime traffic and the development of risk analysis methods.

Data-driven Bayesian analysis of marine accidents in the English Channel

The English Channel, renowned for its heavy traffic and challenging conditions, frequently witnesses marine accidents. To understand the causal mechanisms and identify risk factors, this study analyzed 833 accidents from 2017 to 2022, employing a Bayesian network predictive model. Validation using log loss, quadratic loss, and spherical gain metrics confirmed the model’s accuracy. The research elucidates the primary influences on accident occurrence: ship type, tonnage, accident location, and flag state. Ship-related factors surpass environmental ones in significance. Older ships face heightened risks of mechanical failures and collisions, especially in adverse weather with limited visibility. Yachts and fishing vessels are particularly susceptible to fire, explosion, collision, and grounding incidents. The study offers theoretical guidance for management departments to devise prevention strategies and enhance navigation safety in the English Channel.

A Study on the Influence of Animated AcciMap: A System Analysis of Marine Accidents

A Study on the Influence of Animated AcciMap: A System Analysis of Marine Accidents

Comparative Analysis of Marine Accidents in Fishing Activity Protection Zones and Port and Navigation Zones to Improve Fishing Vessel Security

Comparative Analysis of Marine Accidents in Fishing Activity Protection Zones and Port and Navigation Zones to Improve Fishing Vessel Security

Possibility analysis of complex marine accidents caused by large marine plastic litter in the Republic of Korea

An average of 286 marine accidents related to wrapped floating material occur annually, most caused by large marine plastic litter (LMPL). Although statistically, little damage occurs, accidents by entanglement can lead to additional incidents due to ship, facility, weather, and submarine conditions; crew decisions; rescue capabilities; and water depth. To determine the types of complex marine accidents caused by LMPL, this study analyzed 172 written accounts of the cause, development, and outcome of marine accidents due to propeller entanglement in LMPL such as fishing nets and ropes between 1970 and 2020 using temporal association rules. Type 4 complex marine accidents and maritime hazards involve major events such as drift, grounding, collision, capsizing, sinking, and spilling, which can all potentially cause casualties and economic and environmental damage. Considering existing studies on marine accidents caused by LMPL as post responses focusing on the frequency of incidents and prevention technologies, this study could be regarded as innovative in that it seeks preliminary countermeasures through causal analysis. Carefully planned safety measures are likely to minimize the risk that indifference may increase. Thus, it is necessary to review and revise or newly prepare policies for inspection, law, and crew education regarding LMPL.

A content-aware corpus-based model for analysis of marine accidents

In the past decades, marine accidents brought the serious loss of life and property and environmental contamination. With the accumulation of marine accident data, especially accident investigation reports, compared with subjective reasoning based on expert experience, data-driven methods for analysis and accident prevention are more comprehensive and objective. This paper aims to develop a content-aware corpus-based model for the analysis of marine accidents to mine the accident semantic features. The general research framework is established to combine accident data, expert prior knowledge, and semi-automated natural language processing (NLP) technology. The NLP models are optimized, fused, and applied to the case study of ship collision accidents. The results show that the proposed model can accurately and quickly extract hazards, accident causes, and scenarios from the accident reports, and perform semantic analysis for the latent relationships between them to extend the accident causation theory. This study can provide a powerful and innovative analysis tool for marine accidents for maritime traffic safety management departments and relevant research institutions.

Applicability of Current Statutory Rules for Stability Requirements of Bangladesh Inland Passenger Vessels

_ Applicability of current Bangladesh inland vessels stability rule has been investigated for the local passenger vessels. Bangladesh inland vessel’s stability rule is exactly the same as international stability code (2008), despite of the different environmental load in navigational routes. The restricted waterways limit the dimension of the vessels. It has been found that domestic passenger vessels have changed their dimensions considerably from the year 1974 to 2009. But analysis shows, still most of the domestic passenger vessels exceed the dimensional ratio range that is specified in both the righting lever-based criteria and weather criterion of international code. The part of the weather criterion, specifically estimation method for the angle of roll due to wind and wave action has been studied in details. Different nationals have adopted values of governing parameters for extended range of vessel dimensions, which can also successfully cover all the Bangladesh domestic passenger vessels. As per the code 2008, for ships with values outside of the addressed range, the angle of roll may be determined with model experiments of a subject ship as alternative weather criterion. Bangladesh is still lacking both in facility and infrastructure for carrying model tests. This study shows that computer simulation can be used in exchange of experimental setup where the simulation result can be validated by Parameter Identification Technique, which is described as an alternative approach in the interim guideline of International Maritime Organization (IMO). Introduction Passenger vessel accident is a persistent phenomenon in Bangladesh inland waterways. Thousands of people have passed away due to these catastrophic incidents. The major two modes of failure that are responsible for accidents in waterways are identified as structural failure and stability failure (Islam et al. 2015a). Structural failure like collision also leads to stability failure (Damage Stability). Iqbal et al. (2008a, 2008b) analyzed the Bangladesh inland passenger vessels accident data of 25 years and found that in 49% cases, the failure was due to lose of intact stability. Raiyan et al. (2017) have done event tree analysis of marine accidents in Bangladesh taking initial condition as overloading. Literature study (Awal 2006; Awal et al. 2007; Awal et al. 2014; Islam et al. 2015b; Rahman 2017) shows that researchers have proposed many general recommendations from different point of view to prevent the passenger vessel accidents. But still now, no attempt has been made to analyze the currently applicable statutory rules for ensuring the safety in inland waterways, which is mainly Bangladesh Inland Vessels Stability Rule including Weather Criterion (Zulfikar 2005). Stability rules of inland vessels are to be governed by standard localized condition of the subjected parameters. The socioeconomic condition, local environment, as well as infrastructural development like availability of model test facilities need to be considered for smooth and proper application of stability rules which then can only ensure the safety of local vessels. This implies that the individual efforts of concern country in research and analysis are of great importance for the development of practicable stability rules of inland vessels.

A hybrid model for marine accident analysis based on Bayesian Network (BN) and Association Rule Mining (ARM)

In order to ensure sustainable maritime safety, studies based on unreported maritime accidents in maritime transport are necessary. Such studies allow the causes of accidents that have not come to light, to be identified and addressed. In this study, the data of unreported occupational accidents on Turkish fishing vessels with a full length of 12 m and above was analysed using both Bayesian network (BN) and Association Rule Mining (ARM) methods. A network structure that summarizes the occurrence of occupational accidents on fishing vessels with the BN method was put forward. The network structure makes it possible to analyse the latent factors, active failures and operational conditions that cause the accident qualitatively and quantitatively. The Predictive Apriori algorithm was used to establish rules for the occurrence of occupational accidents on fishing vessels, taking variables such as day condition, length, sea condition, and ship type into account. These rules provide an understanding of how occupational accidents occur on fishing vessels. In other words, these rules define the minimum requirements for the occurrence of accidents on fishing boats. The developed hybrid model can be used for analysing unreported occupational accidents on fishing vessels.

大型クルーズ船における海難の解析 ～コスタ・コンコルディア海難事例～

大型クルーズ船における海難の解析 ～コスタ・コンコルディア海難事例～

Application of the HFACS-PV approach for identification of human and organizational factors (HOFs) influencing marine accidents

Shipping is one of the leading modes of transport that has dominated the world economy from past to present. The effectiveness and efficiency of maritime trade is closely related to maritime safety. Providing quality maritime safety is a fundamental requirement for environmentally friendly, sustainable, safe and efficient global trade. Therefore, maritime safety and human factors are frequently studied topics in literature. However, the fact that the human element has a complex socio-technical structure makes it difficult to fully analyse human factors in accidents. That is one of the biggest challenges in preventing and mitigating accidents. This research aims to demonstrate the feasibility of the modified Human Factor Analysis and Classification System for Passenger Vessel collisions (HFACS-PV) for other types of accidents. 51 grounding accidents that occurred in passenger vessels between 1991 and 2017 were analysed by using the HFACS-PV structure. The results show that the HFACS-PV structure created for passenger vessel accidents is compatible with contact, grounding and sinking accidents as well as collisions. Thus, the HFACS-PV structure allows for coherent analysis of marine accidents. Owing to the flexibility of HFACS, it is also possible to combine it with other analytical methods to conduct both qualitative and quantitative analysis.

Vessel Trajectory Analysis in Designated Harbor Route Considering the Influence of External Forces

A vessel must navigate along designated routes within a harbor area to ensure navigation safety. The impact of strong currents is one of the most dangerous factors in coastal navigation. However, it is challenging to determine the deviation of a ship in advance from the ship’s position data in the case of a marine accident. In this study, to support the decision-making of ship navigators and vessel traffic service (VTS) operators in track monitoring tasks, tracks were classified according to the tidal stream, and the track distribution was analyzed according to the tidal current situations. Marine accident analysis was performed to investigate the tidal influence on ship tracks. Track data were collected for 12 months from a VTS center in Korea, and tidal information was collected through a meteorological observation buoy. Representative tracks were extracted from the track data using the support vector regression (SVR) seaway model. K-fold cross-validation and a grid search were performed to determine the optimal parameters. The ship tracks appeared in specific patterns according to the forces and directions of tidal currents, and specific deviation patterns were observed. This study is expected to contribute to the reduction of marine accidents by predicting ship trajectories according to the tidal situations in advance.

АНАЛИЗ ТЕХНИЧЕСКИХ ОТКАЗОВ НА ПРОМЫСЛОВЫХ СУДАХ В ДАЛЬНЕВОСТОЧНОМ РЕГИОНЕ

The article focuses on the main factors influencing the safety of navigation, such as natural factors, man-made impact, depreciation aspect, operational impact and human factor. The analysis of marine accidents in the far East region determined the value of its technical component. The statistics of the machinery failures on fishing vessels is given. One out of ten accidents has been stated to occur as a result of force majeure events, three quarters of the accidents are related to the human factor in the form of personnel erroneous actions, the rest happen due to technical imperfection of the ships. The chart shows the distribution of accidents by years due to failures and breakdowns of ship technical equipment given in percentage figures. Breakdowns of the main engines, auxiliary mechanisms and their elements, including their systems, annually make up 33.9 - 40.7% of the total number of accidents. Characteristic failures of ship technical equipment are: breakdowns of the main engines, auxiliary diesel generators, auxiliary mechanisms, electrical equipment, screw-steering complex with the shaft line, automation systems. Statistics of the causes of breakdowns of propulsion plant, auxiliaries, main systems and their elements is proportional to the data of similar studies. An attempt has been made to evaluate the importance of the operator-machine link at all levels of responsibility for coastal personnel and ship crews. The impact on the man-machine link in the whole chain of operation of the vessel is important; thus, there was set a task to carry out a quantitative investigation of the reliability of this link. In terms of the ergotechnical component of the fishing fleet operation there has been substantiated the necessity of developing measures (technical, economic, informational, legal) to improve the quality of the vessel activity.

Human Error Assessment and Reduction Technique for Marine Accident Analysis: The Case of Ship Grounding

Human Error Assessment and Reduction Technique for Marine Accident Analysis: The Case of Ship Grounding

Factors Analysis of Marine Accidents and its Preventive Measures Based on TEM Model

Factors Analysis of Marine Accidents and its Preventive Measures Based on TEM Model

Analysis of Ship Accidents in the Istanbul Strait Using Neuro-Fuzzy and Genetically Optimised Fuzzy Classifiers

Marine accident analysis is important for ships passing through narrow, shallow and busy waterways. This study analyses the accidents which have occurred in the Istanbul Strait and proposes both quantitative and qualitative assessments of marine accidents. Marine accidents occurring in the Istanbul Strait are analysed by using a method based on neuro-fuzzy and genetically optimised fuzzy classifiers. It can be concluded that accident severity increases when poor weather conditions prevail in the Strait regardless of ship size. Therefore, solutions to reduce unwanted events should be prioritised by accounting for weather conditions and the capacity of the vessels. This analysis indicates that the safety level would be significantly improved if all the vessels follow the passage guidelines.

Analysis of Vessel-Based Marine Accidents and the Economic Risks to Nigeria

The aim of the study is to evaluate the economic loss of vessel-based marine accidents to Nigeria and the impact on marine transport sub-sector output and/or performance. Time series data of 30 years were gathered from the Central Bank of Nigeria (CBN) statistical bulletin, the Nigeria insurance digest, the Organization of Petroleum Exporting Countries (OPEC) annual statistical report. The contribution of marine transport to the Gross Domestic Product (Y), shipping accident economic loss (X₁), economic losses of offshore oil and gas (O&G) drilling accidents (X₂), and marine oil spill accidents economic losses (X₃) were obtained and used as the explanatory (independent) variables. The data was analyzed using multiple regression method with Y as the dependent variable. The hypotheses were tested using t-test. The findings of the study indicates that shipping accidents economic losses and economic losses of offshore oil and gas drilling accidents shows significant impact on the output of the marine transport sub-sector over the period covered by the study. The model expressing the quantitative relationship between GDP_{marine transport} (Y), shipping accidents economic loss (X₁), economic loss of offshore oil and gas drilling accidents (X₂) and marine oil spill accidents loss (X₃) is: Y = 332156363.1 + 0.167X₁ + 0.837X₂ + 0.203X₃ + e. it was recommended that investment in safety policies and standards be improved with greater focus in reducing accidents induced economic losses in shipping and offshore O&G drilling maritime operations.

Event Tree Analysis of Marine Accidents in Bangladesh

The frequency of marine accidents in Bangladesh is observed to be one of the highest in the world. Maritime disasters in the country took more than 10,000 lives in past three decades. Each time an accident occurs with terrible loss of lives, the issue goes viral through newspapers and social media for several days, and then it is simply consigned to oblivion. Most of the records kept of marine accidents are limited to unsubstantiated news reports with a few exceptions marked in a handful of accidents that were subjected to detailed reporting conducted by maritime authorities. Several research works have been carried out to point out the core reasons behind accidents. But there was a demand of time to find out and represent the sequence of events leading to an accident with the help of a tool more effective than those used in earlier papers. The tool used in this paper is event tree, showing how a single factor, when coupled with other factors or not, is likely to lead to an accident. Despite being a widely-used tool for accident analysis, event tree has been applied for the first time with quantitative study in analyzing maritime accidents in Bangladesh. The research work didn’t end up using event tree as a tool only, but it also conducted a probabilistic analysis. In this research work, the factors, most likely to lead to a disaster, has been identified and then assessed with the data of previous accidents. The probabilistic analysis yielded to the finding that the number of accidents can be reduced considerably if the problem of poor visibility, when the vessel is overloaded, can be solved. The event tree showing the sequence of events will help future researchers and system designers to find out and eliminate the factors contributing to marine accidents and eventually curb the very high frequency of disasters.

Prevention and health promotion as a management task Implementation of Marine accident analysis using PRA concepts

Prevention and health promotion as a management task Implementation of Marine accident analysis using PRA concepts

A Study on the Development of an Early Detection System for Altering Course of a Target Ship

This paper contributes to the development of an early detection system to detect the alteration of a target ship during early stages using the steering wheel signal via AIS communication. The feasibility of this system is also verified with a real ship trial. It was confirmed that the rudder angle on ECDIS was ordinarily marked green or red by the used rudder angle after the steering wheel operation. We were able to detect intentions for a change in course by a target ship quickly and efficiently avoid collisions. This system will contribute to more active VTS services and the analysis of marine accidents using the General Information Center On Maritime Safety & Security (GICOMS).