Improved infrastructure assessment through the integration of nondestructive evaluation and structural health monitoring paradigms.

Format:

Book

Government document

Author/Creator:

Moon, Franklin L., 1976- author.

Braley, John, author.

Gucunski, Nenad, author.

Contributor:

United States. Federal Highway Administration. Office of Infrastructure Research and Development, sponsoring body.

Engineering & Software Consultants, researcher.

Rutgers University, researcher.

Turner-Fairbank Highway Research Center, issuing body.

Language:

English

Subjects (All):

Structural health monitoring.

Nondestructive testing.

nondestructive testing.

Physical Description:

1 online resource (xi, 104 pages) : color illustrations

Place of Publication:

McLean, VA : United States Department of Transportation, Federal Highway Administration, Research, Development, and Technology, Turner-Fairbank Highway Research Center, January 2021.

Language Note:

English

Summary:

This report provides recommendations for integrating both nondestructive evaluation (NDE) data and field data from structural health monitoring (SHM) to obtain load ratings that reliably represent a bridge's load-carrying performance. Modern NDE techniques, which provide accurate location and characterization of deteriorations, enable more reliable estimates of capacity. The existing LRFD Bridge Design Specifications provide detailed equations for determining the capacity of a given bridge member (AASHTO 2017). The dimensions or material properties used in these equations should be revised based on NDE results. Several common deterioration types are shown through analytical studies to have minor effects on the capacity of composite girder sections. Demand estimates require structural analysis to translate globally applied loads to their corresponding member actions or force effects. The effects of local deterioration and defects on member demands were investigated through finite-element (FE) simulation and were shown to have negligible effect (<3 percent). However, an in situ structure may behave very differently than predicted by demand models. Field data from SHM may be leveraged to reduce the uncertainty associated with those demand models. The use of experimental distribution factors(introduced in this report) is shown to more reliably estimate demands compared to the methods provided by the Manual for Bridge Evaluation for incorporating results from diagnostic and proof-level load tests (AASHTO2018). However, it is recommended that refined analysis with FE models be used when practical, as this method permits explicit consideration of all influential mechanisms.

Notes:

"Authors: Franklin Moon, John Braley, and Nenad Gucunski"-- Technical Report Documentation Page.

"Publication FHWA-HRT-21-011."

"HRDI-20/01-21(WEB)"--Page 4 of cover.

"Performing Organization: Engineering & Software Consultants; Rutgers University"--Technical Report Documentation Page.

"January 2021."

Includes Bibliographic References (pages 103-104).

OCLC:

1252632527

Access Restriction:

Open access content Open access content