Implementation of the AASHTO Mechanistic-Empirical Pavement Design Guide and Software (2014)

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42 Development of the AASHTO Mechanistic-Empirical Pave- ment Design Guide (MEPDG) (and accompanying software) has provided the pavement design community with a pavement design and analysis process based on mechanistic-empirical (ME) procedures. ME-based pavement design procedures allow a designer to analyze and evaluate features that directly impact pavement performance, such as traffic loadings, climatic impacts, materials properties, and existing soil conditions. As with any new process, implementation of an ME-based design procedure may require additional agency efforts related to obtaining data, conducting data collection or testing to quantify materials and traffic, staff training, and comparing the results of the new procedure to the existing procedure. The summary of agency MEPDG implementation efforts provided in this synthesis was obtained through a literature search, an agency web-based survey, and follow-up questions with agencies that indicated in the survey that the MEPDG had been implemented by their agency. The literature search was conducted on relevant documents related to agency MEPDG implementation efforts. Although there is extensive docu- mentation related to MEPDG performance prediction model- ing, materials and traffic characterization, and climate impacts, relatively few documents are readily available that summarize the agency MEPDG implementation efforts. The web-based survey was distributed to U.S., Puerto Rico, District of Colum- bia, and Canadian highway transportation agencies requesting information related to current pavement design practices, orga- nizational structure, MEPDG implementation efforts, lessons learned in the implementation process, and the development of products (e.g., training programs, user guides) that could aid the implementation effort. Finally, follow-up questions were asked to further clarify the implementation efforts of the Indiana, Missouri, and Oregon departments of transportation (DOTs). The implementation efforts of these three agencies were showcased as agency implementation case examples. OVERALL FINDINGS Implementation of the MEPDG is a major change in pave- ment design practices for most transportation agencies. In the agency survey, 48 agencies indicated that pavements were designed using empirical-based design procedures that, for the most part, have served the pavement design community reasonably well. Although the agencies have a comfort level with their existing pavement design procedures, many are moving toward implementation of the MEPDG, which is dem- onstrated by the MEPDG implementation by three respond- ing agencies, and 46 agencies that plan on implementing. The majority of responding highway agencies have or intend to implement the MEPDG in the design of asphalt pavements (45 agencies), new jointed plain concrete pave- ments (JPCP; 39 agencies), and new continuously reinforced concrete pavements (CRCP; 12 agencies). In addition, most agencies indicated that the MEPDG will be used for the design of asphalt overlays of existing asphalt pavements (38 agen- cies), asphalt overlays of existing JPCP (34 agencies), and asphalt overlays of fractured JPCP (27 agencies). For con- crete overlays, 22 agencies indicated that the MEPDG will be used to design unbonded JPCP overlays of existing JPCP, JPCP overlay of existing asphalt pavements (21 agencies), and bonded concrete overlays of existing JPCP (13 agencies). The MEPDG requires a larger number of data inputs as compared with previous empirical-based pavement design procedures. Thirty-two agencies indicated that pavement con- dition data are the most readily available, followed by exist- ing pavement structure data (31 agencies), and traffic data (28 agencies). By far the most difficult data for agencies to obtain is material characterization data, as only 17 agencies indicated that it is readily available. In relation to the input level, the survey asked agencies to specify the level of input (i.e., MEPDG default, agency regional or agency site-specific value) that was used for each of 49 input categories (e.g., traffic, asphalt, concrete, unbound materials). In general, the most common response indicated that either the MEPDG default values and/or agency-determined regional values were used. For traffic-specific inputs, vehicle class distribution is predominantly based on site-specific values, hourly and monthly adjustment factors are evenly split between default or regional input values, and truck-specific informa- tion (e.g., axles per truck, wheelbase) are predominantly based on MEPDG default values. For most of the asphalt, concrete, chemically stabilized, sandwiched granular, unbound base, and subgrade soil inputs values are based on agency-determined regional values. For bedrock layers, input values are generally based on MEPDG default values. As of May 2013, nine agencies indicated that some or all of the MEPDG performance prediction models had been calibrated to local conditions. Depending on the performance chapter six CONCLUSIONS

43 prediction model, reported calibration coefficients varied significantly. There are several organizational commonalities among the responding agencies, including an MEPDG champion and establishing an MEPDG oversight committee. Thirty-two agencies indicated that there was an MEPDG champion, and for the majority of agencies (29), this person was the pave- ment engineer or pavement design engineer (or similar posi- tion). The MEPDG oversight committee has been established by 25 agencies and committee members generally included the pavement engineer, materials engineer, pavement design engineer, district or region engineer, and the research engi- neer or director. Although it is difficult to determine a direct correlation between implementation status and organization structure, the majority of the agencies (31) have a central- ized organization structure, most have consistent commu- nication across agency functions (25 agencies), and those agencies that had an MEPDG champion and/or oversight committee appeared to be further along in the implemen- tation process (i.e., implementation was expected to occur within 2 years). Common Elements of Agency MEPDG Implementation Plans Based on the literature review of agency implementation plans, a number of common elements were identified. Deter- mining which elements to include is based on the approach that best meets the individual agency needs. The following lists the common elements of agency MEPDG implementa- tion plans: • Pavement types included in the implementation effort. • Data sources and necessary data collection or testing. • Data libraries for materials and traffic inputs. • Threshold and reliability levels for each performance prediction model. • MEPDG verification—Confirmation that predicted dis- tress meets measured distress. • Agency documentation of MEPDG-specific information. • Training of agency staff in the areas of ME principles, MEPDG procedures, and operation of AASHTOWare Pavement ME Design™. Case Examples Based on the agency survey, three agencies indicated that the MEPDG had been implemented: the Indiana, Missouri, and Oregon DOTs. Common organizational elements among these agencies include the open discussion and access to data and information across all agency divisions (all three agencies), the presence of an MEPDG champion (all three agencies), and the establishment of an oversight commit- tee (two of the three agencies). The following summarizes the implementation efforts for each agency included in the case examples. • Indiana DOT. Indiana DOT began evaluation of the MEPDG in 2002, with full implementation in 2009. In general, the Indiana DOT MEPDG implementation effort included: – Defining input parameters for each level of design accuracy. – Reviewing relevant data contained in the DOT and Long-Term Pavement Performance databases. – Evaluating and acquiring needed equipment and developing a testing program. – Conducting material and traffic characterization. – Locally calibrating the MEPDG performance predic- tion models. – Conducting concurrent designs to compare the results of the existing design procedure with the MEPDG. – Providing training in ME principles, MEPDG proce- dures, and software operation. – Revising the Indiana DOT Design Manual to incorpo- rate the use of the MEPDG for the design of pavement structures. • Missouri DOT. Missouri DOT initiated the MEPDG implementation process, with full implementation by 2009. The implementation effort for Missouri DOT included: – Comparing Missouri-specific traffic data with the MEPDG default values. – Conducting testing to quantify material properties (asphalt, concrete, dense-graded aggregate base, and subgrade materials). – Testing section evaluation (coring to quantify asphalt layer properties, concrete properties, falling weight deflectometer testing to quantify in situ layer stiffness, manual condition surveys, and analysis of historical International Roughness Index data). – Conducting local calibration. • Oregon DOT. Oregon DOT began evaluation of the MEPDG in 2006, and implemented the MEPDG for the design of new or reconstructed pavement on high- volume routes in 2009. The Oregon DOT MEPDG implementation process included: – Characterizing properties of typical asphalt mixtures. – Characterizing weigh-in-motion data from 22 loca- tions across the state. – Identifying existing conditions (pavement layer type and thickness, material properties, traffic, and distress condition data). – Conducting local calibration. LESSONS LEARNED The agency survey responses reported the following lessons learned during the implementation of the MEPDG: • Realistic timelines for the calibration and validation process. • Sufficient time for obtaining materials and traffic data.

44 • Readily available data related to the existing pavement layer, materials properties, and traffic. • A plan for collecting needed data; this can require an expensive field sampling and testing effort. • Agency-based design inputs to minimize design variability. • Training of agency staff in ME design fundamentals, MEPDG procedures, and the AASHTOWare Pavement ME Design™ software. ACTIVITIES TO AID IMPLEMENTATION The amount of research that has been conducted related to the MEPDG is extensive. In addition, local and national research efforts related to material and traffic characterization, perfor- mance prediction, and model development will continue in the foreseeable future. Based on agency survey responses, the following provides a list of activities that would aid in the implementation effort (in rank order, highest to lowest number of responses): • Training in AASHTOWare Pavement ME Design™ software functionality and operation (36 responses). • Assistance with calibrating models to local conditions (36 responses). • Dedicated website for sharing technical information (35 responses). • Training in interpretation of results (33 responses). • Training for obtaining inputs (32 responses). • Training in ME design principles (29 responses). • Training on how to modify pavement sections to meet design criteria (26 responses). • Establishment of an expert task or user group (25 responses). • Ability to share databases with other agencies (18 responses).