1Director, Arctic Sea Route Policy Division, Ministry of Oceans and Fisheries 2Associate Professor, Department of Civil & Environmental Engineering, Seoul National University
Corresponding author:
Yong-Sung Park ,Tel: +82-2-880-8387, Email: dryspark@snu.ac.kr
Received: June 22, 2026; Revised: July 24, 2026. Accepted: July 28, 2026.
Share :
ABSTRACT
This study aims to develop a probabilistic deterioration model to predict the performance degradation of port civil infrastructure. Infrastructure systems deteriorate over time, and deterioration models that quantitatively predict this decline serve as essential tools for maintenance decision-making. However, research on deterioration modeling for port infrastructure—particularly quay structures—remains highly limited both globally and in South Korea. To address this gap, this study develops a deterioration model to predict changes in the safety grades of port facilities by applying the MCMI (Markov Chain Monte Carlo with Multiple Imputation) approach, which integrates Bayesian MCMC with Multiple Imputation. After preprocessing precision safety inspection data from the Ministry of Oceans and Fisheries (MOF, 2012), a total of 103 data records were utilized for analysis. The predictive performance of four calibration methods—Optimization, OWBB, MCMC, and MCMI—was compared. Evaluation using Root Mean Square Error (RMSE) and Index of Agreement (IA) demonstrated that while the MCMI method showed a predictive accuracy equivalent to Optimization and OWBB based on representative values (IA = 0.722, RMSE = 0.447), it provided the most favorable upper and lower bounds for the 95% confidence interval, indicating that MCMI offers more comprehensive uncertainty quantification among the methods. According to the analysis, under a scenario with no maintenance intervention, domestic port facilities reach Grade B in 2 years on average, Grade C in 19 years (95% confidence interval [CI]: 13~30 years), Grade D in 56 years (95% CI: 36~131 years), and Grade E in 124 years (95% CI: 75~300 years). This study provides a reference standard as a preliminary scenario analysis technique for establishing port maintenance budgets and determining the timing for preventive conservation. Furthermore, the proposed methodology can be extended and applied to ports in other countries where performance indicators are available.
PDF Links
Full text via DOI
Download Citation 
