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Data Fusion Approach for the Effective Inspection of Prestressed Concrete

Award Information
Agency: Department of Transportation
Branch: N/A
Contract: DTRT57-14-C-10033
Agency Tracking Number: DTRT57-14-C-10033
Amount: $149,400.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 14.1-FH1
Solicitation Number: DTRT5714RSBIR1
Timeline
Solicitation Year: 2014
Award Year: 2014
Award Start Date (Proposal Award Date): 2014-08-26
Award End Date (Contract End Date): 2015-02-22
Small Business Information
6521 Meridien Drive
Raleigh, NC 27616-3209
United States
DUNS: 125145974
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Robert Lindyberg
 Vice President
 (919) 755-1012
 rlindyberg@fdh-inc.com
Business Contact
 Tena Crook
Title: Vice President
Phone: (919) 755-1012
Email: tcrook@fdh-inc.com
Research Institution
N/A
Abstract

While many inspection technologies are available to find corrosion in steel tendons of prestressed concrete, no single technology has shown consistent results over the wide range of prestressed structures and inspection settings that are required from the bridge infrastructure market. However, a new NDE method – Nonlinear Impact Resonance Spectroscopy (NIRS) – shows promise in identifying corrosion of embedded steel by identifying changes in the interfacial bond, interfacial stresses, as well as micro-cracking at the interfacial regions and within the concrete, all of which can be a byproduct of the corrosion of prestressing steel.
The research team proposes combining the NIRS method – by which the nonlinearity of the dynamic response of the concrete is monitored and correlated to the condition of the prestressing strands – with the results from the best proven techniques using a data fusion approach, to obtain more consistent and useful results than any of the individual tests for inspecting and evaluating prestressed concrete. In addition to NIRS, the techniques proposed include traditional electrochemical inspections and ground penetrating radar, as well as several emerging ultrasonic technologies. The resulting corrosion predictions will be used to create risk-based criteria for specifying inspection intervals

* Information listed above is at the time of submission. *

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