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The Mechanistic Empirical Pavement Design Guide (MEPDG) developed by the National Cooperative Highway Research Program (NCHRP) project 1-37A, is a very powerful tool for the design and analysis of pavements. The designer utilizes an iterative process to select design parameters and predict performance, if the performance is not acceptable they must change design parameters until an acceptable design is achieved. The design process has more than 100 input parameters across many areas, including, climatic conditions, material properties for each layer of the pavement, and information about the truck traffic anticipated. Many of these parameters are known to have insignificant influence on the predicted performance During the development of this procedure, input parameter sensitivity analysis varied a single input parameter while holding other parameters constant, which does not allow for the interaction between specific variables across the entire parameter space. A portion of this research identified a methodology of global sensitivity analysis of the procedure using random sampling techniques across the entire input parameter space. This analysis was used to select the most influential input parameters which could be used in a streamlined design process. This streamlined method has been developed using Multiple Adaptive Regression Splines (MARS) to develop predictive models derived from a series of actual pavement design solutions from the design software provided by NCHRP. Two different model structures have been developed, one being a series of models which predict pavement distress (rutting, fatigue cracking, faulting and IRI), the second being a forward solution to predict a pavement thickness given a desired level of distress. These thickness prediction models could be developed for any subset of MEPDG solutions desired, such as typical designs within a given state or climatic zone. These solutions could then be modeled with the MARS process to produce am “Efficient Design Solution” of pavement thickness and performance predictions. The procedure developed has the potential to significantly improve the efficiency of pavement designers by allowing them to look at many different design scenarios prior to selecting a design for final analysis.

Pavement damage due to heavy loads on thaw weakened flexible pavements is a major concern for road agencies in Western Canada. To protect weaker, low volume roads, agencies impose spring weight restrictions (SWR) during the spring thaw to reduce pavement damage. While SWR may be cost effective for highway agencies, reducing the spring weight allowances can have a major impact on truck productivity and shipping costs. Therefore an improved process that links SWR loads to pavement damage, and based on limiting failure strain, is required. This thesis developed Local mechanistic-empirical damage models to predict fatigue and rutting failure on two spring weight restricted (SWR) flexible pavements in Manitoba. The Local damage models were used to assess the SWR loads that regulate commercial vehicle weights in Manitoba based on a limiting strain relationship between truck loads and damage. The Local damage models and a calibrated Finite Element Model (FEM) were used to predict the equivalent single axle load (ESAL) repetitions to fatigue and rutting failure at varying B-Train axle loads at the Manitoba sites. The Local model predictions were compared to predictions from the Asphalt Institute (AI) and Mechanistic Empirical Design Guide (MEPDG) damage models. The results of the analysis showed that for each 1% increase in load, there was a corresponding 1% increase in strain, and up to 3% decrease in ESAL repetitions to failure, depending on the Local, AI, or MEPDG damage models. The limiting failure strains, computed from the Local model for design ESALs of 100,000, were 483μm/m and 1,008μm/m for fatigue and rutting failure, respectively. For the Manitoba sites, the predicted FEM strains at B-Train normal and SWR loads were higher than the Local model limiting strains. Therefore the Manitoba ii SWR loads regulating B-Train operations on the two pavements during the spring period appeared to be reasonable. It is recommended that the research findings be verified with further calibration and validation of the Local damage model using a larger data set of low volume flexible pavements. A strain-based concept on how to manage the SWR regime in Manitoba based on the limiting strains was developed and presented.

Pavement damage due to heavy loads on thaw weakened flexible pavements is a major concern for road agencies in Western Canada. To protect weaker, low volume roads, agencies impose spring weight restrictions (SWR) during the spring thaw to reduce pavement damage. While SWR may be cost effective for highway agencies, reducing the spring weight allowances can have a major impact on truck productivity and shipping costs. Therefore an improved process that links SWR loads to pavement damage, and based on limiting failure strain, is required. This thesis developed Local mechanistic-empirical damage models to predict fatigue and rutting failure on two spring weight restricted (SWR) flexible pavements in Manitoba. The Local damage models were used to assess the SWR loads that regulate commercial vehicle weights in Manitoba based on a limiting strain relationship between truck loads and damage. The Local damage models and a calibrated Finite Element Model (FEM) were used to predict the equivalent single axle load (ESAL) repetitions to fatigue and rutting failure at varying B-Train axle loads at the Manitoba sites. The Local model predictions were compared to predictions from the Asphalt Institute (AI) and Mechanistic Empirical Design Guide (MEPDG) damage models. The results of the analysis showed that for each 1% increase in load, there was a corresponding 1% increase in strain, and up to 3% decrease in ESAL repetitions to failure, depending on the Local, AI, or MEPDG damage models. The limiting failure strains, computed from the Local model for design ESALs of 100,000, were 483μm/m and 1,008μm/m for fatigue and rutting failure, respectively. For the Manitoba sites, the predicted FEM strains at B-Train normal and SWR loads were higher than the Local model limiting strains. Therefore the Manitoba ii SWR loads regulating B-Train operations on the two pavements during the spring period appeared to be reasonable. It is recommended that the research findings be verified with further calibration and validation of the Local damage model using a larger data set of low volume flexible pavements. A strain-based concept on how to manage the SWR regime in Manitoba based on the limiting strains was developed and presented.

The Utah Department of Transportation (UDOT) has fully implemented the Mechanistic-Empirical Pavement Design Guide for pavement design but has been using primarily level-three design inputs obtained from correlations to aggregate base materials developed at the national level. UDOT was interested in investigating correlations between laboratory measurements of resilient modulus, California bearing ratio (CBR), and other material properties specific to base materials commonly used in Utah; therefore, a statewide testing program was needed. The objectives of this research were to 1) determine the resilient modulus of several representative aggregate base materials in Utah and 2) investigate correlations between laboratory measurements of resilient modulus, CBR, and other properties of the tested materials. Two aggregate base materials were obtained from each of the four UDOT regions. Important material properties, including particle-size distribution, soil classification, and the moisture-density relationship, were investigated for each of the sampled aggregate base materials. The CBR and resilient modulus of each aggregate base material were determined in general accordance with American Society for Testing and Materials D1883 and American Association of State Highway and Transportation Officials T 307, respectively. After all of the data were collected, several existing models were evaluated to determine if one or more of them could be used to predict the resilient modulus values measured in this research. Statistical analyses were also performed to investigate correlations between measurements of resilient modulus, CBR, and other properties of the tested aggregate base materials, mainly including aspects of the particle-size distributions and moisture-density relationships. A set of independent predictor variables was analyzed using both stepwise regression and best subset analysis to develop a model for predicting resilient modulus. After a suitable model was developed, it was analyzed to determine the sensitivity of the model coefficients to the individual data points. For the aggregate base materials tested in this research, the average resilient modulus varied from 16.0 to 25.6 ksi. Regarding the correlation between resilient modulus and CBR, the test results show that resilient modulus and CBR are not correlated for the materials tested in this research. Therefore, a new model was developed to predict the resilient modulus based on the percent passing the No. 200 sieve, particle diameter corresponding to 30 percent finer, optimum moisture content, maximum dry density (MDD), and ratio of dry density to MDD. Although the equation may not be applicable for values outside the ranges of the predictor variables used to develop it, it is expected to provide UDOT with reasonable estimates of resilient modulus values for aggregate base materials similar to those tested in this research.

The purpose of this research was to compare the rutting, cracking, and development of roughness of two asphalt overlay types commonly used in northern Utah and to evaluate how well the Mechanistic-Empirical Pavement Design Guide (MEPDG) can predict the observed results. AC-10 and PG 64-34 asphalt overlay materials were paved in a checkerboard pattern at a test site on State Route 30 near Logan, Utah, and observed for 3 years at 6-month intervals. Primary data included rutting, cracking, and roughness. At the conclusion of the 3-year evaluation period, rut depths were 0.08 in. deeper, on average, in the AC-10 overlay compared to the PG 64-34 overlay. Fatigue cracking in the PG 64-34 overlay exceeded that in the AC-10 overlay by 0.11 percent, on average. The measured roughness of the PG 64-34 overlay was greater by 24 in./mile, on average, than the AC-10 overlay. In summary, although the AC-10 product exhibited more rutting than the PG 64-34 product, the latter exhibited more fatigue cracking and greater roughness than the former. Although the MEPDG predictions for rutting are within the range of observed rut depths, the MEPDG overestimated the AC-10 rut depth while underestimating the PG 64-34 rut depth. Furthermore, the apparent inability of the MEPDG to predict amounts of longitudinal, fatigue, and transverse cracking comparable to measured values is concerning; the MEPDG predicted negligible cracking for both overlay types for the duration of the 3-year analysis period. While the MEPDG cracking models appear to be unsuitable for predicting cracking at this site, the MEPDG predictions for roughness are shown to be within the range of observed values. Given the findings of this study, the researchers recommend that Utah Department of Transportation (UDOT) engineers consider specifying the AC-10 asphalt overlay product for pavement treatments in conditions similar to those evaluated in this investigation. Even though the MEPDG predictions of rutting and roughness were generally correct, the researchers recommend that such predicted values be used as general predictions only. Further evaluation of these models, as well as the MEPDG models for longitudinal, fatigue, and transverse cracking, should be completed before the MEPDG is fully adopted by UDOT.

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