Maintenance Cost Estimation in PSCI Girder Bridges Using Updating Probabilistic Deterioration Model

Lee, Jin Hyuk; Choi, Yangrok; Ann, Hojune; Jin, Sung Yeol; Lee, Seung-Jung; Kong, Jung Sik

doi:10.3390/su11236593

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Maintenance Cost Estimation in PSCI Girder Bridges Using Updating Probabilistic Deterioration Model

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School of Civil, Environmental and Architectural Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea

Department of Civil, Construction and Environmental Engineering, NC State University, Raleigh, NC 27606, USA

Advanced Railroad Civil Engineering Division, Korea Railroad Research Institute, 176 Cheoldobangmulgwan-ro, Uiwang-si, Gyeonggi-do 16105, Korea

Author to whom correspondence should be addressed.

Sustainability 2019, 11(23), 6593; https://doi.org/10.3390/su11236593

Received: 23 October 2019 / Revised: 18 November 2019 / Accepted: 20 November 2019 / Published: 22 November 2019

(This article belongs to the Special Issue Sustainability in Civil Engineering: from Sustainable Materials to Sustainable Structures)

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Abstract

A deterioration model plays an important role to predict the valid total maintenance cost for sustainable maintenance of bridges. In the current state-of-the-art, the deterioration model has regression parameters as a probabilistic process by an initially determined mean and standard deviation, called an existing model. However, the existing model has difficulty to predict maintenance costs accurately, because it cannot reflect an information based on structural damage at an operational stage. In this research, updating the probabilistic deterioration model is presented for the prediction of pre-stressed concrete I-type (PSCI) girder bridges using a particle filtering technique which is an advanced Bayesian updating method based on big data analysis. The method enables predicting maintenance cost fitted in the current structural status, which includes the recent information by inspection with bridge-monitoring. The method is adapted in the Mokdo Bridge which is currently being used for evaluating the efficiency of maintenance cost by effects on updated probabilistic values with two different scenarios. As the result, it is shown that the proposed method is effective in predicting maintenance costs. View Full-Text

Keywords: deterioration model; maintenance cost; sustainable maintenance; particle filtering; bridge-monitoring

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MDPI and ACS Style

Lee, J.H.; Choi, Y.; Ann, H.; Jin, S.Y.; Lee, S.-J.; Kong, J.S. Maintenance Cost Estimation in PSCI Girder Bridges Using Updating Probabilistic Deterioration Model. Sustainability 2019, 11, 6593. https://doi.org/10.3390/su11236593

AMA Style

Lee JH, Choi Y, Ann H, Jin SY, Lee S-J, Kong JS. Maintenance Cost Estimation in PSCI Girder Bridges Using Updating Probabilistic Deterioration Model. Sustainability. 2019; 11(23):6593. https://doi.org/10.3390/su11236593

Chicago/Turabian Style

Lee, Jin H., Yangrok Choi, Hojune Ann, Sung Y. Jin, Seung-Jung Lee, and Jung S. Kong. 2019. "Maintenance Cost Estimation in PSCI Girder Bridges Using Updating Probabilistic Deterioration Model" Sustainability 11, no. 23: 6593. https://doi.org/10.3390/su11236593

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Maintenance Cost Estimation in PSCI Girder Bridges Using Updating Probabilistic Deterioration Model

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