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The mechanics-based analysis framework predicts top-down fatigue cracking initiation time in asphalt concrete pavements by utilizing fracture mechanics and mixture morphology-based property. To reduce the level of complexity involved, traffic data was characterized and incorporated into the framework using the equivalent single axle load (ESAL) approach. There is a concern that this kind of simplistic traffic characterization might result in erroneous performance predictions and pavement structural designs. This paper integrates axle load spectra and other traffic characterization parameters into the mechanics-based analysis framework and studies the impact these traffic characterization parameters have on predicted fatigue cracking performance. The traffic characterization inputs studied are traffic growth rate, axle load spectra, lateral wheel wander and volume adjustment factors. For this purpose, a traffic integration approach which incorporates Monte Carlo simulation and representative traffic characterization inputs was developed. The significance of these traffic characterization parameters was established by evaluating a number of field pavement sections. It is evident from the results that all the traffic characterization parameters except truck wheel wander have been observed to have significant influence on predicted top-down fatigue cracking performance.

The need to account for design inputs variabilities effect on predicted performance has led many design procedures to address the issue of reliability for pavement applications. The Florida cracking model utilizes an empirically derived reliability for fatigue cracking design of asphalt pavements. A reliability approach, which is based on probabilistic uncertainty quantification, is necessary in order to account properly and effectively for the contribution of the variability in each parameter to the overall variance. This paper presents a load and resistance factor design (LRFD) procedure for the Florida cracking model. By delivering designs of uniform reliability, LRFD provides the basis for developing quality control and quality assurance standards. A first order reliability method (FORM) which incorporates central composite design (CCD) based surrogate model is employed to compute the reliability and formulate the partial safety factors. The reliability calibration was achieved based on field pavement sections that have a wide range in design inputs and target reliability. Illustrative designs based on the developed LRFD procedure has shown the effectiveness of the partial safety factors, and thus giving further confirmation to the credibility of the employed reliability analysis methodology. INTRODUCTIONLoad induced top-down fatigue cracking (i.e., cracking that initiates at the surface of asphalt concrete (AC) layer and propagates downward) has been observed in many parts of the world (e.g., 1-4). It is widely accepted that top-down cracking results from a critical combination of load, thermal and aging effects. A multi-year research at the University of Florida has led to the development of a new hot mix asphalt fracture mechanics (HMA-FM) framework. HMA-FM is based on visco-elastic principle and predicts the initiation and propagation of top-down cracking (e.g., 5, 6). Based on the performance evaluation of field pavement sections, a parameter termed energy ratio (ER) which relates well with the observed performance in the field was identified and introduced into HMA-FM (7). Utilizing ER as a design criterion, a mechanistic empirical (M-E) pavement design model for top-down fatigue cracking was developed. The model was calibrated and validated on a number of field pavement sections from the State of Florida and has been found to be successful in distinguishing pavement sections which exhibited cracking from those that did not. The energy ratio method has recognized the importance of accounting for the effects of uncertainty in design inputs on predicted performance, and has therefore incorporated an empirically derived reliability concept. These reliability factors were developed by fitting computed ER values of a single section with respective target reliabilities without accounting directly for the effects of design inputs variabilities on performance (8). A reliability which is not based on probabilistic method of uncertainty propagation might not give designs of uniform target reliability th...

Reliability has been incorporated in many pavement design procedures to account for the effects of inputs variabilities and uncertainties on predicted performance. The American Association of State Highway and Transportation Officials (AASHTO) mechanistic empirical pavement design guide (MEPDG) computes the reliability of pavement sections with the assumption that the variability of predicted distresses follows normal distribution. This approach does not account for the systematic contribution of each design input variability on the overall output variance. This paper evaluates a two-component reliability analysis methodology for pavement application. The two-component reliability analysis methodology uses a response surface method (RSM) for a surrogate model generation and the first order reliability method (FORM) for reliability computation. Three different response surface methods (central composite, Box–Behnken and Doehlert designs) were implemented and statistically verified for their suitability for surrogate model generation. The two-component reliability analysis methodology was further utilized for the generation of partial safety factors for the development of a load and resistance factor design (LRFD) procedure for pavement applications. Field pavement sections with a wide range in design inputs and target reliabilities were used to evaluate the proposed reliability analysis methodology. The results have shown that the three RSM can be used effectively for pavement reliability problems.