# Development of Fire Consequence Prediction Model
## 1 Introduction  
### Background  
Rapid external support cannot be deployed in marine accidents, unlike land accidents. Thus, it is crucial to identify the risk of accidents to minimize or prevent damage. If risk prevention or accident identification fails in the early stage, it leads to second and third damage states. Moreover, if the decision making for an effective and urgent response to an accident cannot be supported or delayed owing to the failure of a quick report on the situation, it can lead to huge casualties and property loss. Safety management and accident prevention techniques are important during the handling of LNG considering the risks of a massive explosion and damage in the event of fire accidents. As the LNG facilities age, the likelihood of accidents may increase, and severe accidental fires and explosions can cause fatal damage not only to industrial workers but also to external civilians. Quantitative risk analysis is required to investigate the impact of LNG fire accidents on the human body or building by analyzing the frequency of accidents and accident consequences based on preset scenarios by identifying the potential risks during the LNG bunkering process and refueling process in LNG ships. Quantitative risk-analysis methods consist of three main steps for interpreting the risk of accidents: risk identification, risk estimation, and risk assessment. Through the estimated risk, safety measures can be formulated, and the risks are lowered to an acceptable level, which is applied in the design stage. It is widely used in the process industry to identify the risks of expected accident scenarios, such as in quantitative risk assessment (QRA),probabilistic safety analysis (PSA), and maximum reliable accident analysis [1]. Existing risk assessment methods play an important role in identifying and maintaining the major risks of process facilities; however, they have the disadvantage of using static and general failure data [2; 3]. The static nature of the aforementioned method hardly reflects the changes that almost always occur during the process. In addition, the use of general data prevents case-by-case analysis and introduces uncertainty in the results. Meanwhile, a dynamic risk assessment method considers new information and adjusts to the dominant dynamic environment for processing system risk and safety analysis. Risk assessment methods can be considered over the lifetime of the system, as well as for decision-making support, risk-management tools, and the design stage of the process system [4]. The continuous improvement and updating of the risk management process are required through rapid accident detection, accident damage prediction according to the situation, and safety systems [5]. The quantitative risk analysis method, which is applied in the design stage, serves to suggest safety measures and lower the risk to an acceptable level through the estimated risk. This approach utilizes a computer simulation database constructed based on thousands of predefined accident scenarios. The conventional accident response system enables a response to rapidly evolving accident situations by supporting decision-making and organizing the operating system required to respond to accidents. This can support decision making inside a ship by searching the scenario of a similar situation in the event of an accident; however, it is difficult to consider realistic conditions to respond to accidents based on the current process conditions. Therefore, a real-time response method that considers real-time conditions is required [6]. Understanding the accident consequence as a priority is helpful in making decisions because accidents on ships are highly likely to be an urgent situation. For instance, if a 1 mm leak occurs in the piping in a situation where a process work is in progress, it can be effectively responded to because a 1 mm leak is not a considerably dangerous situation.