Development of structural condition thresholds for TSD measurements
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This thesis presents (a) results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The results showed consistent error standard deviation in the TSD measurements and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT’s Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher.
In order to develop deflection thresholds, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation.