A numerical risk analysis approach on salvage operation of grounded vessels

Abstract

Maritime is one of the most influential actors of world trade, whose importance is increasing day by day. In addition to this great importance, maritime is full of risks with a wide variety of serious consequences. For this reason, safety is at the center of the maritime industry and risk analysis has an important place in academic studies on the maritime industry. One of the most dangerous operations in maritime is salvage. Salvage has several sub- sections, such as salvaging a wrecked ship, removing sunken ships or valuable materials, and harbor cleaning. Salvage operations are operations involving heavy loads for long periods and high-risk activities. Considering that each accident has different variables, there is no single truth in salvage. For example, the ship may have run aground in a sandy area or a rocky area, or may have been involved in a collision and therefore severely damaged or sunk. Risk situations will vary according to the situation and planning to be made according to the variable situation of the accident and the operation to be performed. When considered from this point of view, risk analysis is of great importance in the field of salvage. In the light of this information, it is aimed to make a general risk analysis in the salvage operation of the stranded ship in this thesis. Although salvage operations differ in themselves, the main realities of salvage and the risks determined in the light of lived experiences are focused on. In this context, HAZOP and LOPA methods will be combined in risk analysis assessment and the order of magnitude approach will be used for quantification. First of all, the initial events, the undesired consequences of deviations, and the safety measures that can be taken will be determined by the HAZOP method. Then, with the LOPA method, the frequency of initial events, the severity of undesirable consequences, and the risk reduction values of safety measures will be determined by the order of magnitude approach.