0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessMost of masonry arch bridges dates from ancient times, having an important historical value to society, thus requiring appropriate conservation approaches. Regarding masonry arch bridge’s structural condition, considering its age, and consequently deterioration, and the fact that they are submitted to loads much higher than those existing at their construction period, it is imperative to evaluate the structural performance of these structures. This paper will expose a methodology for safety assessment of masonry arch bridges, namely in terms of ultimate load- carrying capacity, determined by limit analysis. Monitoring and material characterization are standard procedures in safety assessment and, will be shown that Bayesian techniques are a useful tool to incorporate new gathered information in structural analysis model. Safety assessment procedures described in the article will be applied to a Portuguese stone masonry arch bridge from the 19th century.
Vicente N. Moreira, José C. Matos, Daniel V. Oliveira (2015). Probabilistic structural assessment of railway masonry arch bridges. Report, DOI: 10.2749/222137815818358033.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2015
Authors
3
Datasets
0
Total Files
0
Language
English
Journal
Report
DOI
10.2749/222137815818358033
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access