• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.6
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• pp.129-139
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• 2008

Due to uncertainty of numerous variables in durability model, a probalistic approach is increasing. Monte Carlo simulation (Level III method) is an easily accessible method, but requires a lot of repeated operations. This paper evaluated the effectiveness of First Order Second Moment method (Level II method), which is more convenient and time saving method than MCS, to predict the corrosion initiation in harbor concrete structure. Mean Value First Order Second Moment method (MV FOSM) and Advanced First Order Second Moment method (AFOSM) are applied to the error function solution of Fick's second law modeling chloride diffusion. Reliability index and failure probability based on MV FOSM and AFOSM are compared with the results by MCS. The comparison showed that AFOSM and MCS predict the similar reliability index and MV FOSM underestimates the probability of corrosion initiation by chloride attack. Also, the sensitivity of variables in durability model to corrosion initiation probability was evaluated on the basis of AFOSM. The results showed that AFOSM is a simple and efficient method to estimate the probability of corrosion initiation in harbor structures.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.139-147
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• 2021

In this study, we proposed the possibility of reliability analysis of risk index by using Monte Carlo simulation as basic data of safety accident occurrence data and expert opinion by construction industry type. Through this, it is expected that risk index for safety accidents according to detailed types of works will be presented stochastically and it will be possible to predict the risk factors and the expected range of damage based on the reliability analysis in the construction safety management plan. It will also reduce many of the planning risks that are common to decision makers in the field of construction management. In identifying risks, road bridge construction was classified into earthworks, drainage works, and bridge construction, and possible safety accidents were classified based on expert data. The risk index was calculated for each detailed construction of road and bridge construction, drainage construction, and bridge construction.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.45-67
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• 2014

National Innovative Capability (NIC) is an important decisive factor where economic growth is concerned. As such, it is very important to measure and manage NIC. The composite index approach is one of the widely used approaches to measuring NIC, but there have been insufficient reviews of its feasibility and reliability. This paper conducted an analysis of the feasibility and reliability of the report on the last three years (i.e. 2011 through 2013) of the Innovation Union Scoreboard (IUS) of the EU, which is the most representative means of measuring NIC. It turned out that its reliability meets the recommended criteria as a result of Chronbach's alpha-based test of the models of IUS-related composite index. However, neither the absolute fit index nor the incremental fit index was found to meet the recommended criteria in a construct validity analysis. It also turned out that predictive validity is very low as a result of panel linear regression analysis of sectors and items of IUS-related composite index. This paper presents a number of considerations to be made when measuring national innovative capability using the composite index approach, as well as major policy suggestions based on the results of the analysis.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.2
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• pp.115-122
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• 2016

The classical statistical approach using test data samples to estimate true value of Random Variables by calculating mean and variation (standard deviation or coefficient of variation) of samples is very useful to understand the existing condition of the structure. But with this classical approach, our prior knowledge through educational background and professional experience cannot provide any benefit to make decisions by the structural engineers. This paper shows the role of Bayesian methodology by providing chance of using valuable prior knowledge to come up with more accurate estimation of structural condition. This paper also shows how important it is to have a proper prior estimate of Random Variables and corresponding confidence level through gathering and studying more relevant information.