Researchers Create TSD Conversion Application TSD deflections can now be converted into FWD deflections for backcalculation

Featured in Technology Today (Volume 34, Issue 2), a quarterly publication of the Louisiana Transportation Research Center.

In their project “A Mechanistic Approach to Utilize Traffic Speed Deflectometer (TSD) Measurements into Backcalculation Analysis,” researchers Mostafa Elseifi, Ph.D., P.E. (VA), Zia U.A. Zihan, and Patrick Icenogle created and sought to validate a theoretical model using 3D-Move software in order to utilize traffic speed deflectometer (TSD) measurements in backcalculation analysis.

Backcalculation takes a measured surface deflection (a real-life test) and attempts to match it (within some tolerable error) with a calculated surface deflection (the desired result) generated from an identical pavement structure. Usually, backcalculation analysis is used based on falling weight deflectometer (FWD) measurements, which need lane closure and traffic control to be accurate. However, in recent years a number of continuous deflection devices have been introduced, including the traffic speed deflectometer (TSD), which involves a special vehicle that actively scans the road while driving.

Traffic speed deflectometer
“Recent studies conducted in Louisiana and elsewhere suggest that the TSD is a promising device for pavement evaluation at the network level because it can measure deflection at traffic speeds, which enable large spatial coverage and can provide continuous deflection profile rather than measuring pavement deflection at discrete points, which is the case with FWD,” Dr. Elseifi explained. “However, in spite of the encouraging advantages of TSD, currently available tools to backcalculate layer moduli use FWD deflection measurements as the main input and cannot be directly used with TSD deflection measurements.”

As a result, researchers created an application to convert TSD deflections into FWD deflections. Dr. Elseifi and his team utilized 3D-Move software to calculate the theoretical deflection bowls corresponding to FWD and TSD loading configurations. Dr. Elseifi explained, “Since 3D-Move requires the definition of the constitutive behavior of the pavement layers, cores were extracted from 13 sections in Louisiana and were tested in the laboratory to estimate the dynamic complex modulus of asphalt concrete.”

Non-Uniform Tire Pressure Distribution in the 3D-Move Model

Researchers then generated deflection bowls in 3D-Move; these bowls proved to be acceptably accurate, so the researchers moved forward with their parametric study, wherein all model loading configurations created in 3D-Move were field-tested for validation.

“The results obtained from the parametric study were utilized to develop a Windows-based application, which uses artificial neural network as the regression algorithm to convert TSD deflections to the corresponding FWD deflections,” said Dr. Elseifi. “The converted deflections may then be used in regular backcalculation analysis software to backcalculate the pavement layer moduli.”

Windows application for converting TSD deflections to FWD deflections

According to researchers, this application can greatly reduce computational efforts in backcalculating from TSD measurements and is ready for implementation in TSD deflection research. In addition, the results of this research were successfully presented at the TRB annual meeting in 2021 with several agencies expressing interest in evaluating the developed Windows applications.

For more information

To learn more, please visit Final Report 612 or contact Dr. Mostafa Elseifi at elseifi@lsu.edu.