Modeling factors influencing culvert load ratings: A parametric analysis

Timothy A. Wood, James G. Surles, S. Mehdi Mousavi, Priyantha W. Jayawickrama, Amir Hossein Javid, Hoyoung Seo, William D. Lawson

Research output: Contribution to journalConference article

Abstract

This parametric analysis illustrates the relative influence of six parameters on reinforced concrete box culvert (RCBC) load rating using a production-simplified soil-structure interaction demand model. Frequently, field inspections show in-service RCBCs to perform adequately, but load rating per AASHTO guidance requires load posting. Parameters such as (1) the culvert design, (2) cover soil depth, and (3) soil stiffness are driven by the in-service culvert condition. The test matrix consists of three RCBC designs evaluated under three cover soil depths embedded in three soil stiffnesses. Load raters may implement less conservative, more accurate assumptions for (4) pavement stiffness, (5) effective moment of inertia, and (6) the top interior wall fixity, as appropriate. Cover soil depth and design showed significant impact on the culvert load rating, but are defined by the culvert condition. Less conservative assumptions for the effective moment of inertia had the greatest impact on the load rating, followed by the inclusion of pavement stiffness.

Original languageEnglish
Pages (from-to)243-252
Number of pages10
JournalGeotechnical Special Publication
Issue numberGSP 277
DOIs
StatePublished - 2017
EventGeotechnical Frontiers 2017 - Orlando, United States
Duration: Mar 12 2017Mar 15 2017

Fingerprint Dive into the research topics of 'Modeling factors influencing culvert load ratings: A parametric analysis'. Together they form a unique fingerprint.

Cite this