Decision theoretic approach for identification of optimal proof load with sparse resistance information

Medha Kapoor, J. D. Sørensen , S. Ghosh, S. Thöns

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Proof load testing may be performed to confirm the reliability of the bridge for an existing classification or to prove the reliability for a higher classification. In this paper, a probabilistic decision analysis approach is applied to the scenario for the evaluation of target proof load in the situation where information on the bridge resistance model is lacking. In this case, the resistance model is established by proof loading and taking very basic prior knowledge into account. The decision scenario is modelled in the context of the proof load test planner who shall choose the required load level for assessment of a bridge. The choice of the load level depends on the risks due to the testing and the expected benefit gain from the test. Information acquired about the loading response from monitoring during the proof load testing is modelled by taking basis in the model uncertainty formulation. The optimal proof load level for classification of a single lane, simply supported bridge of 8m span subjected to live load from very heavy (gross weight > 80 tons) transport vehicles was calculated. The optimal proof load level was identified as leading to a positive expected benefit gain to the decision maker while also satisfying target reliability criteria for remaining service life. The analysis was performed for the evaluation of bridge performance with respect to five classifications of very heavy transport vehicles with different vehicle weights and configurations.
Original languageEnglish
Title of host publicationBridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations : Proceedings of the Tenth International Conference on Bridge Maintenance, Safety and Management
Number of pages8
PublisherCRC Press
Publication date2021
ISBN (Electronic)9780429279119
DOIs
Publication statusPublished - 2021

Fingerprint

Dive into the research topics of 'Decision theoretic approach for identification of optimal proof load with sparse resistance information'. Together they form a unique fingerprint.

Cite this