Assessment of a cantilever bridge deck slab using multi-level assessment strategy and decision support frameworkShow others and affiliations
2019 (English)In: Engineering structures, ISSN 0141-0296, E-ISSN 1873-7323, Vol. 200, article id 109666Article in journal (Refereed) Published
Abstract [en]
A Multi-Level Assessment Strategy has previously been proposed and proved feasible for structural analysis of existing RC slabs. In this paper, the Multi-Level Assessment Strategy, which focuses on sophisticated structural analysis, was used to investigate the load-carrying capacity and structural behaviour of a composite bridge with an RC bridge deck slab subjected to a concentrated load. In addition to more sophisticated structural analysis, improved knowledge content about the structure and more advanced models for uncertainty consideration were also incorporated in a systematic way for higher levels of assessment. Furthermore, a decision support system was adopted, in which the cost for different alternatives regarding if and how the assessment should be enhanced with respect to model sophistication, knowledge content and modelling uncertainty were compared in a systematic way. The results show not only that the load-carrying capacity and the structural behaviour can be assessed with different level of detailing, but also that the cost for each level of assessment can be evaluated with a decision support system, facilitating more sustainable management of infrastructure.
Place, publisher, year, edition, pages
Elsevier Ltd , 2019. Vol. 200, article id 109666
Keywords [en]
Cantilever bridge deck slab, Decision support framework, Multi-level assessment, Shear and punching, Artificial intelligence, Bridge decks, Cantilever bridges, Load limits, Loads (forces), Nanocantilevers, Structural analysis, Uncertainty analysis, Concentrated load, Knowledge content, RC bridges, RC slab, Structural behaviour, Sustainable management, Decision support systems
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-39973DOI: 10.1016/j.engstruct.2019.109666Scopus ID: 2-s2.0-85072515519OAI: oai:DiVA.org:ri-39973DiVA, id: diva2:1359583
Note
Funding details: Energimyndigheten; Funding details: Trafikverket; Funding details: Vetenskapsrådet, VR; Funding text 1: The authors acknowledge the financial support provided by the Swedish Transport Administration (Trafikverket) and the strategic innovation programme InfraSweden2030, a joint effort of Sweden's Innovation Agency (Vinnova), the Swedish Research Council (Formas) and the Swedish Energy Agency (Energimyndigheten). Contribution from adjunct professor Morgan Johansson from Chalmers University of Technology is appreciated for the inspiring discussion.
2019-10-092019-10-092020-02-03Bibliographically approved