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Novel Application of the Falling Weight Deflectometer Test: Detection of Surface and Subsurface Distresses

  • Anirban ChatterjeeEmail author
  • Yichang(James) Tsai
Conference paper
Part of the RILEM Bookseries book series (RILEM, volume 20)

Abstract

Falling Weight Deflectometers (FWD) and Traffic Speed Deflectometers (TSD) have become increasingly popular for monitoring the structural performance of roadway pavements. However, many transportation agencies measure the functional performance of the pavement (given by surface distresses such as cracking, rutting and raveling) for maintenance purposes. This study explored the feasibility of estimating surface and subsurface distresses using FWD tests. It was found that the presence of pavement cracking can be detected through FWD tests but not pavement rutting. A random forest classifier was used to predict the presence of cracking between layer interfaces below the pavement surface. The classifier achieved an accuracy of 92.3%. With the methodology presented in this paper, FWD tests can be used to measure the structural as well as functional performance of pavements. The methodology also serves as a proof-of-concept for using TSDs to measure the functional performance of pavements at high speeds. This provides an alternative to unsafe and laborious on-foot survey practices.

Notes

Acknowledgements

The authors would like to thank the research project sponsored by the Georgia Department and Transportation, “RESEARCH PROJECT 14-05: Study of Georgia’s Pavement Deterioration/Life and Potential Risks of Delayed Pavement Resurfacing and Rehabilitation”, especially Jewell Stone and Neoma Cole from GDOT for their Falling Weight Deflectometer Tests on SR 26/US 80 near Savannah, GA, and the support provided by Ernay Robison, Eugene and Binh Bui from GDOT. We would like to thank the research team, Yiching Wu, Dr. Ross Wang, Dr. Zhaohua Wang, Geoffrey Price, Georgene Geary, Vincent Cartillier and April Gadsby from Georgia Tech for collecting 3D data on SR 26/US 80.

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Copyright information

© RILEM 2019

Authors and Affiliations

  1. 1.Georgia Institute of TechnologyAtlantaUSA

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