TY - GEN
T1 - Optimal bridge maintenance algorithms considering subordinate relation with bridge members
AU - Jin, Sungyeol
AU - Lee, Jin Hyuk
AU - Choi, Yangrok
AU - Lim, Jaehoon
AU - Kong, Jung Sik
N1 - Funding Information:
Acknowledgements This research was supported by a grant (17SCIP-B128492-01) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport of Korean Government.
Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2021.
PY - 2021
Y1 - 2021
N2 - Recently, social interest in the deteriorated bridges and infrastructure has been increasing. Also, studies on performance prediction and maintenance decision making of structures are underway. In this study, it was proposed an algorithm to create an optimal maintenance scenario that takes into consideration the relationship between the members of bridge that affect each other, rather than the conventional maintenance that is focused on single members of the bridge. Since maintenance scenario creation is discrete in terms of time and cost. So in this study, it is used a genetic algorithm. Each member of bridge has a subordinate relation that takes into account member damage transitions effect and the elimination of duplication maintenance cost, which was established through the Korean bridge maintenance manual and expert opinion. In order to predict the performance change of each member, the algorithm used the condition prediction model of each member of the bridge, which was created by multiple regression analysis based on the actual bridge case. Also, it used the maintenance cost model of members for cost estimation, it has created and applied it through actual maintenance case analysis. The constraint of the algorithm is set to the minimum maintenance level of the bridge by the bridge administrator. And, it was conducted the case study about real bridge model using the optimal maintenance model, analyzed the cost-effect and made maintenance scenario.
AB - Recently, social interest in the deteriorated bridges and infrastructure has been increasing. Also, studies on performance prediction and maintenance decision making of structures are underway. In this study, it was proposed an algorithm to create an optimal maintenance scenario that takes into consideration the relationship between the members of bridge that affect each other, rather than the conventional maintenance that is focused on single members of the bridge. Since maintenance scenario creation is discrete in terms of time and cost. So in this study, it is used a genetic algorithm. Each member of bridge has a subordinate relation that takes into account member damage transitions effect and the elimination of duplication maintenance cost, which was established through the Korean bridge maintenance manual and expert opinion. In order to predict the performance change of each member, the algorithm used the condition prediction model of each member of the bridge, which was created by multiple regression analysis based on the actual bridge case. Also, it used the maintenance cost model of members for cost estimation, it has created and applied it through actual maintenance case analysis. The constraint of the algorithm is set to the minimum maintenance level of the bridge by the bridge administrator. And, it was conducted the case study about real bridge model using the optimal maintenance model, analyzed the cost-effect and made maintenance scenario.
KW - Condition prediction model
KW - Genetic algorithm
KW - Optimal bridge maintenance
KW - Subordinate relation
UR - http://www.scopus.com/inward/record.url?scp=85104112564&partnerID=8YFLogxK
U2 - 10.1007/978-981-15-8079-6_116
DO - 10.1007/978-981-15-8079-6_116
M3 - Conference contribution
AN - SCOPUS:85104112564
SN - 9789811580789
T3 - Lecture Notes in Civil Engineering
SP - 1237
EP - 1242
BT - EASEC16 - Proceedings of the 16th East Asian-Pacific Conference on Structural Engineering and Construction, 2019
A2 - Wang, Chien Ming
A2 - Kitipornchai, Sritawat
A2 - Dao, Vinh
PB - Springer Science and Business Media Deutschland GmbH
T2 - 16th East Asian-Pacific Conference on Structural Engineering and Construction, 2019
Y2 - 3 December 2019 through 6 December 2019
ER -