Marine accident analysis for collision and grounding in oil tanker using FTA method

In this study, collision and grounding data registered in GISIS (Global Integrated Shipping Information System) were investigated for oil tankers. The database includes the information of the collision and grounding accidents during the period between 1998 and 2010 in oil tankers. The risk assessments were carried out using fault tree analysis (FTA) programme for the incidents as collision and grounding occurred in oil tankers. In this study, we were able to investigate first the potential problems which cause the collision and grounding accidents have been determined, second, the occurrence of accidents has been shown with causal factors by the FTA method, and, finally, the significance degree of the initial events causing occurrence of accidents have been put forth. Collision in oil tanker resulted in economical loss (81%), pollution (6%) and death or injury (13%). Grounding in oil tanker resulted in economical loss (91%) and pollution (9%). According to the FTA results, the main reason for the accidents originating from human error is as follows: for collision accidents, Convention on the International Regulations for Preventing Collisions at Sea (COLREG) violation and the lack of communication between vessels; and for grounding accidents, the interpretation failure of the officer on watch and lack of communication in the bridge resource management.     

Prediction of wave parameters by using fuzzy inference system and the parametric models along the south coasts of the Black Sea

Forecasting of sea-state characteristics has a great importance in coastal and ocean engineering studies. Therefore, the purpose of this study was to investigate performances of Adaptive-Network-Based Fuzzy Inference System (ANFIS) and several parametric methods in the Black Sea. For this purpose, different fuzzy models with different input combinations were developed for two different wind data sources (TSMS and ECMWF) at two offshore buoy stations. It also aimed to apply several approaches to event-based data sets for wave predictions. Generally, in literature the tendency is to use time series data for wave predictions. In this kind of prediction approach, lagged time series data are taken as inputs and current or future variables are taken as output. In this study, event-based data for each independent storm were extracted from time series data. Simultaneous or concurrent data of wind speed, blowing duration, fetch length and wave characteristics were detected for each single storm. These event data were then used to set up models. The hindcast results were validated with significant wave height and mean wave period data recorded in Hopa and Sinop buoy stations. The performance of developed fuzzy models were also compared with that of four different parametric methods (Wilson, SPM, Jonswap, and CEM methods) applied for two wind data sources at both buoy stations. Finally, it was determined that in the prediction of both wave parameters (H _s and T _z) the ANFIS models (R = 0.66, squared correlation coefficient, and MAE = 0.37 m, mean absolute error, for the best model in prediction of H _s) were more accurate than the parametric methods (R = 0.63 and MAE = 0.75 m for the best model in prediction of H _s).     

Simulation optimization of the berth allocation in a container terminal with flexible vessel priority management

ABSTRACT

Solving the berth allocation problem (BAP) in ports is not trivial where the berth resources are limited and various sizes of vessels arrive with dramatically dissimilar loads. Especially in real scenarios, arriving vessels are accepted for a berth with the first come first served (FCFS) priority rule. This study proposes a decision support system coupled with a simulation optimization module based on the swarm-based Artificial Bee Colony optimization algorithm for solving the BAP. The proposed methodology was implemented for the Izmir port in Turkey. To investigate the influences of the vessel priorities on the BAP, four different experimental scenarios based on the single (SQM) and multiple queue models (MQM) were coupled with FCFS and proposed hybrid queue priority (HQP) rule. The results indicated that SQM scenarios were superior to MQM scenarios in a manner of minimizing the average vessel waiting times and the implementation of a dynamic berth allocation strategy for the MQM significantly decreases the vessel waiting times. Results of the SQM also imply that utilization of the HQP approach further minimizes the average vessel waiting times and increases the berth utilization and port throughput without yielding excessive waiting times for the larger vessels compared with the FCFS priority rule.     

Analytic hierarchy process application in selecting the mode of transport for a logistics company

As a multi‐criteria decision‐making (MCDM) method, the analytic hierarchy process (AHP) has been used considerably to solve hierarchical or network‐based decision problems in socio‐economic fields. Following an in‐depth explanation of the transport function in logistics and an overview of the MCDM methods, the AHP model is employed in the paper for a logistics company in selecting the most suitable way of transportation between two given locations in Turkey. The criteria used in the selection of transportation modes are identified as the cost, speed, safety, accessibility, reliability, environmental friendliness, and flexibility. Several cost parameters (transportation, storage, handling, bosphorus crossover) are incorporated into the decision‐making process. The application is carried out in instructional character. The results of the study indicate that the railway transportation, which is not widely used in Turkey, is also an alternative and suitable means of transportation. Copyright © 2013 John Wiley & Sons, Ltd.     

PM10 concentrations and the size distribution of Cu and Fe-containing particles in Istanbul’s subway system

In this study, PM₁₀ concentrations, as well as the size distributions of Fe-containing and Cu-containing particles are measured in six subway stations in Istanbul. The average daily PM₁₀ concentrations are found to vary considerably. They were also found to be significantly higher than the levels found at urban air quality stations. Further, the relative abundance of Fe-containing particles among the particles of size >2.1 μm collected in the metro stations is 3.5-8 times higher than in the in the Istanbul atmosphere.     

The subjective measurement of seafarers’ fatigue levels and mental symptoms

Human error is the most important factor causing many ship accidents in maritime industry despite advanced technology and international regulations. Fatigue in seafarers is a well-known problem and a serious cause of ship accidents. There are many factors unique to the marine environment raising the potential for fatigue at sea. Due to the difficulties in measuring human fatigue and also in suggesting fatigue to be a root cause of accident, it is important to devise methods to detect and quantify the fatigue and mental symptoms. In this study, ‘Piper Fatigue Scale’ (PFS) has been used for measuring fatigue level and ‘Symptom Checklist 90- Revised’ (SCL-90-R) for detecting the severity of mental symptoms. Data analyses were performed using the SPSS (Statistical Package for the Social Sciences) software. According to the results of PFS analysis, a slight degree of fatigue is detected in all sub-dimensions of the scale. According to the results of SCL-90-R analysis, the distress of mental symptoms perceived by seafarers is not generally highly detected. In conclusion, the purpose of this study is to determine, by using subjective measurements, the fatigue level and mental symptoms among seafarers caused by working conditions on-board.     

Numerical modeling of exhaust smoke dispersion for a generic frigate and comparisons with experiments

The exhaust smoke dispersion for a generic frigate is investigated numerically through the numerical solution of the governing fluid flow, energy, species and turbulence equations. The main objective of this work is to obtain the effects of the yaw angle velocity ratio and buoyancy on the dispersion of the exhaust smoke The numerical method is based on the fully conserved control-volume representation of the fully elliptic Navier-Stokes equations. Turbulence is modeled using a two-equation （k-ε） model The flow visualization tests using a 1/100 scale model of the frigate in the wind tunnel were also carried out to determine the exhaust plume path and to validatc the computational results. The results show that down wash phenomena occurs for the yaw angles between ψ=10° and 20°. The results with different exhaust gas temperatures show that the buoyancy effect increases with the increasing of the exhaust gas temperature. However, its effect on the plume rise is less significant in comparison with its momentum. A good agreement between the predictions and experiment results is obtained.     

Simulation-based assessment methodology to improve ground service operations at a hub airport

ABSTRACT

Airport terminals are dynamic environments and security/passport services generally constitute costly bottlenecks in terminals. Increases in the number of airline passengers compels airport terminals to provide more efficient services to its customers under space and resource limitations. This study examines the level of service of passenger processes at Istanbul Atatürk Airport by constructing a comprehensive simulation model. It focuses mainly on passport control services and passenger transfer security services because of the airport's hub status and the strategy of Turkish Airlines. The increasing number of transfer passengers may cause disruptions in departure flight schedules due to slow passenger processes. After validating the model, we investigate the consequences of three main alternative solutions, including 17 sub-scenarios, to capture target quality levels. Finally, we provide the results for each scenario to investigate the optimum allocation of resources to terminal operations.     

A multiple criteria approach for the evaluation of the rail transit networks in Istanbul

The deficiencies in the Istanbul transportation system have led the local authorities to plan several alternative transportation projects. In this paper three alternative rail transit network proposals are evaluated by using Analytic Hierarchy Process (AHP), a multiple criteria decision support system. The AHP facilitates decision-making by organizing perceptions, experiences, knowledge and judgments, the forces that influence the decision, into a hierarchical framework with a goal, scenarios, criteria and alternatives of choice. Based on this analysis, the decision makers have developed a new alternative as a combination of the most closely competing two alternative rail transit networks. This combination rail transit network is currently under construction.     

Numerical experiments on the prediction of sea surface temperature anomalies in the Gulf of Mexico

The conservation of thermal energy equation applied to the mixed layer of the ocean, has been used to predict the sea surface temperature anomalies (SSTA) and the month-to-month changes in the Gulf of Mexico. The model includes the horizontal transport of heat by mean ocean currents and by turbulent eddies, as well as the heating by short and long wave radiation, evaporation and sensible heat given off to the atmosphere. A comparative study is carried out on the relative importance of the heating and transport terms. An objective verification of the skill of the predictions is presented for each season and for the whole period from March 1986 to February 1987. The predictions using only the heating terms have some skill over the control predictions (persistence and return to normal). The skill is substantially increased when the horizontal transport of heat by turbulent mixing is included in the model. The incorporation in the model of the Ekman wind drift current anomalies computed from the anomalous surface geostrophic wind improves appreciably the skill of the predictions in winter and fall.The mixed layer depth computed using the Kraus and Turner theory with dissipation, shows that the depths in summer and fall are shallower than in spring and winter. The effect of the shallow mixed layer depth in the model becomes apparent in summer and fall, improving the skill of the predictions in these seasons, with respect to the skill obtained using a constant mixed layer depth of 60 m.The incorporation in the model of the cooling in the mixed layer by turbulent entrainment of colder water from the thermocline, does not improve in an appreciable way the average skill of the predictions.