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 ARLINGTON, MASS. — Infrasense Inc. recently developed and is currently providing automated processing software to integrate Ground Penetrating Radar (GPR) pavement thickness data with Falling-Weight Deflectometer (FWD) testing. Infrasense’s GPR Automated Processing (GPRAP) software streamlines the FWD testing process by quickly and accurately providing layer thicknesses without the need for data processing experience or coring. GPRAP is currently being incorporated by JILS, of El Segundo, Calif., to create a fully integrated GPR-FWD system using the automated processing software.

Pavement strength evaluations are an important aspect of planning and designing pavement rehabilitation and reconstruction, and FWD is a useful tool in performing these evaluations. However, in order to determine the pavement moduli, the layer thickness must be included in the calculation. Although GPR has seen a number of applications in highway engineering, one of the most common applications is the determination of pavement layer thickness. A recent survey found that at least 28 state highway agencies utilize GPR, either for individual projects or in network-level pavement management. GPR can provide quick, accurate pavement thickness results; and by integrating GPR data with FWD testing, pavement structural properties may be determined more efficiently.

Earlier this year, Infrasense completed a study in conjunction with the Montana Department of Transportation to evaluate the thickness of 26 pavement test sections located throughout the state using GPR. GPR and FWD data was collected at five test locations per site, and coring and augering were performed to obtain ground truth data. This data was used to determine the effectiveness of the GPRAP software in providing accurate pavement thicknesses for FWD analysis.

The GPR data collected was analyzed to determine asphalt thickness using both a traditional processing method with a trained interpreter, and by the GPRAP automated processing software. Based on data from 130 cores, the average deviation between GPR data and core data was found to be 6.2 percent for the traditional manual method versus 7.6 percent for the automated method. Thus, GPRAP provides an effective and timely method for combining GPR and FWD data to obtain pavement thickness and moduli quickly and accurately.