DISTRESS PREDICTION MODELS FOR CRCP

The major purpose of this study was to develop regression models for the prediction of distress in CRCP in Texas for use by the SDHPT in making decisions concerning the allocation of funds for rehabilitation of these pavements. Use of these models in the manner recommended in this report will facilitate making the choice among rehabilitation alternatives and give greatly improved efficiency with regard to utilization of these funds. First, condition survey data from two separate surveys (four years apart) were analyzed to establish repeatability, variability over time and the effect of directionalized traffic. Next, analysis of variance was performed to determine the relative contributions to distress in the pavements of a series of different factors. Multiple regression techniques were then utilized to obtain distress prediction models in terms of these factors. Finally, guidelines for a procedure for utilization of these models in decision making among rehabilitation alternatives as part of a rigid pavement evaluation system (RPES) were outlined. It is anticipated that the models and procedures developed here will be implemented by the Texas SDHPT in the near future. (FHWA)