Recently the construction project is becoming large-sized, complicated, and modernize. This has increased the uncertainty of construction risk. Therefore, studies should be followed regarding scientifically identifying the risk factors, quantifying the frequency and severity of risk factors in order to develop a model that can quantitatively evaluate and manage the risk for response the increased risk in construction. To address the problem, this study analyze the probability distribution of risk causes, the probability of occurrence and frequency of the specific risk level through Monte Carlo simulation method based on the accident data caused at construction sites. In the end, this study derives quantitative analysis by analyzing the amount of risk and probability distributions of accident causes. The results of this study will be a basis for future quantitative risk management models and risk management research.

Recently, the quantity of risk in construction project has been inflated due to the fact that current construction projects have been large and complicated. Therefore, a study on the risk management methods is necessary that can predict and respond to the need in complicated modern construction projects. In this study, the objective is to analyze the cause of accident in actual construction sites and develop a risk assessment model based on insurance claims records. To reach the goal of this study, first, the frequency and severity of accidents are analyzed the causes of accidents based on the classification; progress rate, season, and total construction costs. Second, a risk assessment model is developed by utilizing a multiple regression analysis. The dependent variable is loss ratio of material damage and three categories; natural hazards, geographic information, and construction method & ability, are used as the independent variables. The model's adjusted R-square is 0.455. The contributions of this study will be used as a material for a quantitative risk analysis model development and review of the construction risk factors for future study.

This study provides the numerical model to assess retrofit and strengthen levels in the dispersal and combat facilities. First of all, it is verified that direct-hitting projectiles are more destructive to the structures rather than close-falling bombs with explosion tests. The protective capacity of dispersal and combat facilities, which are modeled with soil uncertainty and structural field data, is analyzed through finite element method. With structural survivability and facility data, the logistic regression model is drawn. This model could be used to determine the level of the retrofit and strengthen in the dispersal and combat facilities of contact areas. For more reliable model, it could be better to identify more significant factors and adapt non-linear model. In addition, for adapting this model on the spot, appropriate strengthen levels should be determined by hands on staffs associated with military facilities.

The losses of accidents in the construction industry was significantly increased during the past decades. Therefore, the study of risk management measures in the domestic construction has become very important, and the inherent risk factors need to derive and analyze them based on the quantified method. However, most studies on the construction risk are conducted finding on the qualitative way. This study analysis the accident records from actual construction sites as a quantities study. A correlation analysis and regression analysis are adopted to identify the risk factors and develop a model. The results of this study are expected to be evolve through the accumulated effect and verification of data in the future through continuous feedback.