Abstract
Bridge A7957 is the first Missouri Department of Transportation (MoDOT) large-scale project using self-consolidating concrete (SCC) and high-strength self-consolidating concrete (HS-SCC). The objective of this research was to monitor the initial in-service behavior of the precast-prestressed concrete primary elements of Bridge A7957 and to obtain the load distribution of the bridge using field and finite element models (FEM) data. An initial series of diagnostic load tests was conducted on the bridge superstructure. Embedded sensors recorded strain variations at different section of the instrumented girders for different load configurations. An automated total station (ATS) collected the vertical deflection of the girders at several locations during the application of different test loads. The load distribution for moment was obtained experimentally (using deflection and strain data), FEMs, and using the AASHTO LRFD Bridge Design Specifications. The distribution factors for moment estimated with the AASHTO LRFD equations resulted in larger values compared to field test and FEM results. No difference was observed between the response of the SCC and conventional concrete members during the first series of field load tests.
Recommended Citation
E. S. Hernandez and J. J. Myers, "Load Distribution of a Prestressed Self-Consolidating Concrete Bridge," Frontiers in Built Environment, vol. 5, Frontiers Media S.A., Jul 2019.
The definitive version is available at https://doi.org/10.3389/fbuil.2019.00096
Department(s)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
diagnostic load test; girder distribution factors; lateral load distribution; load distribution factors; SCC prestressed concrete girders
International Standard Serial Number (ISSN)
2297-3362
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2019 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
01 Jul 2019
Comments
This work was funded by the Missouri Department of Transportation (MoDOT) under the project TRyy1236, the National University Transportation Center (NUTC) at the Missouri University of Science and Technology under the project 00040350, and the US Department of Transportation under contract DTRT06-G-0014.