Semi-probabilistic assessment of existing bridge using simplified methods for estimation of variance
dc.contributor.author | Novák, Lukáš | |
dc.contributor.author | Novák, Drahomír | |
dc.date.accessioned | 2023-01-18T15:56:51Z | |
dc.date.available | 2023-01-18T15:56:51Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Acta Polytechnica. 2022, vol. 36, no. , p. 142-148. | |
dc.identifier.issn | 1210-2709 (print) | |
dc.identifier.issn | 1805-2363 (online) | |
dc.identifier.uri | http://hdl.handle.net/10467/106395 | |
dc.description.abstract | The paper is focused on assessment of existing prestressed concrete bridge by simplified methods for estimation of coefficient of variation. The bridge was selected in the framework of the European Project INTERREG AUSTRIA-CZECH REPUBLIC "ATCZ190 SAFEBRIDGE" focused on advanced numerical analysis of existing bridges represented by non-linear finite element model. The key ingredient in semi-probabilistic design and assessment of structures is an estimation of coefficient of variation (ECoV). Recently, correlation interval approach together with novel Eigen ECoV were proposed by authors of this paper and theoretically proved to be an efficient and accurate alternative to existing methods. This contribution is focused on practical application of Eigen ECoV on real example solved by NLFEM and its comparison with other existing simplified methods. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | České vysoké učení technické v Praze | cs |
dc.publisher | Czech Technical University in Prague | en |
dc.relation.ispartofseries | Acta Polytechnica | |
dc.relation.uri | https://ojs.cvut.cz/ojs/index.php/APP/article/view/8396 | |
dc.rights | Creative Commons Attribution 4.0 International License | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.title | Semi-probabilistic assessment of existing bridge using simplified methods for estimation of variance | |
dc.type | article | en |
dc.date.updated | 2023-01-18T15:56:51Z | |
dc.identifier.doi | 10.14311/APP.2022.36.0142 | |
dc.rights.access | openAccess | |
dc.type.status | Peer-reviewed | |
dc.type.version | publishedVersion |
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