Journal article
Nonlinear Behavior of Heavy Class Steel Truss Bridges
Journal of structural engineering (New York, N.Y.), v 129(8), pp 1113-1121
Aug 2003
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper presents nonlinear modeling and analysis of a decommissioned steel truss bridge (STB) in Franklin County, Ohio that was tested to failure in 1992 and demolished in 1993. When the existing heavy class STB constructed with built-up sections and rigid joints are idealized in the analysis as simple nonredundant trusses, the load rating of the trusses may indicate posting or replacement. The inherent capabilities and the redundancy of heavy class trusses may be studied by nonlinear analysis. In this paper, nonlinear models of the subject bridge are evaluated by sensitivity analysis, the most viable representation of the bridge is selected, and the simulated behavior is correlated with those measured during the destructive testing of the bridge. Analyses suggested that trusses of this bridge possess significant rotational energy that must be dissipated by plastic deformations within the truss joints before the rigid frame-like truss is transformed into a determinate system. Analysis and tests indicated that heavy-class STBs remain redundant and maintain their load capacity even after initiation of material yielding in several members of the main trusses. The paper also discusses the minimum requirements of nonlinear finite element analysis for the strength and failure mode evaluation of existing steel bridges.
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Details
- Title
- Nonlinear Behavior of Heavy Class Steel Truss Bridges
- Creators
- Razi S Nagavi - Senior Structural Engineer, SES and PEDCo Engineers, Cincinnati, OH 45231.A. Emin Aktan - Drexel University
- Publication Details
- Journal of structural engineering (New York, N.Y.), v 129(8), pp 1113-1121
- Publisher
- American Society of Civil Engineers
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- [Retired Faculty]
- Web of Science ID
- WOS:000184243800012
- Scopus ID
- 2-s2.0-5544231094
- Other Identifier
- 991019168838004721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Construction & Building Technology
- Engineering, Civil