Analysis of occupational accidents encountered by deck cadets in maritime transportation

The 2010 Manila amendments to the Standards of Training, Certification and Watchkeeping Code (STCW) was adopted by the idea to render the profession more attractive to the seafarers, particularly to cadets. It is possible to ensure greater attraction only by providing suitable and safe working conditions on board to cadets. This study analyses occupational accidents and near misses encountered by ocean going deck cadets, who received A-II/I training, during their sea training. The aim of this study was to determine causal factors influencing work accidents and to propose several recommendations for the safety of deck cadets. A total of 857 officer candidates, who received maritime education at university level in Turkey, were interviewed. The Analytic Hierarchy Process (AHP) method was used in the study to analyse the occupational accidents. As a result of this study on deck cadets, the most risky areas for work accidents were found to be the deck (39.9%), cargo areas (35.7%), areas used for manoeuvring operations (including winch areas and areas in which berthing, unberthing, and anchoring operations take place) (16.1%), and accommodation areas (8.3%). The most important root causes for occupational accidents were identified as not using personal protective equipment (24.2%), haste (22.6%), and presence in inappropriate places (13.6%). This study offers some important insight into the prevention of occupational accidents, and includes suggestions and advisory opinions of sector representatives. As a result of this study, several recommendations for the prevention of accidents are proposed.     

A decomposition method for surrogate models of large scale structures

Analysis is computationally the most expensive part of optimization. Surrogate models, which are approximate but faster statistical models, can be used in place of more precise but more computer-intensive methods like finite element method to improve efficiency. Unfortunately, the surrogate models are limited by the number of model parameters. So large-scale problems cannot be fully defined by a single surrogate model. Furthermore, current domain decomposition methods cannot be used with black-box models. This study presents a novel approach to design thin-walled structures using surrogate models that overcome the curse of dimensionality by a special decomposition method. A parametric panel structure is defined as a building block. An interface is developed to maintain compatibility across the blocks. Finally, an iterative algorithm finds the displaced state using only local information. Three test structures are used to show the convergence of the algorithm for static analysis. In these sample cases, number of steps required for convergence of the error did not change with the number of panels. This approach offers many benefits including automatic design creation and optimization, effective usage of stream processors and model reuse.     

Blast Pressure Measurements of an Underwater Detonation in the Sea

Blast pressure measurements of a controlled underwater explosion in the sea were carried out. An explosive of 25-kg trinitro-toluene (TNT) equivalent was detona...