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82 A Manual for Design of Hot Mix Asphalt with Commentary and ground roofing shingles or shingle tabs. Another class of non-conventional materials is novel additives--chemicals, compounds, or other materials--designed to provide some benefit to HMA, but which have not yet been thoroughly evaluated with laboratory tests and field trials. Care should be used in evaluating these mixtures using the criteria presented in the manual or elsewhere for HMA. Performance Predictions Using the AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) Some agencies and mixture designers may be interested in using the MEPDG to predict the performance of a pavement incorporating specific HMA mixtures. Such an analysis using the MEPDG will include the effect of both pavement structure and HMA mixture properties on performance. In some cases, such as bottom-up fatigue cracking, layer thicknesses or subgrade support conditions will dominate. In other cases, such as rutting in an overlay of an existing pavement, HMA mixture effects will be more important. This section provides an introduction to the MEPDG and how it can be used to predict the performance of an HMA mixture for a specific pavement section. The MEPDG is a comprehensive, state-of-the-practice tool for the design of new and rehabilitated pavement structures. Readers interested in using this tool are encouraged to study the MEPDG user manual and other detailed documentation for the MEPDG. The MEPDG is substantially different than most pavement design procedures used in the past by highway agencies. The MEPDG is based on mechanistic-empirical pavement design principles. Critical stresses and strains from vehicle and environmental loading are computed using mechanistic theory. These critical stresses and strains are then empirically related to the occurrence of distresses such as rutting and cracking in the pavement. Most agencies have experience with the 1993 AASHTO Pavement Design Guide, which is based on limited empirical pavement performance equations from the AASHO Road Test conducted in the late 1950s and early 1960s. The distress prediction models in the MEPDG have been calibrated using data for a large number of pavement sections in the Long-Term Pavement Performance (LTPP) database. Pavement sections used in the calibration were located throughout the United States. The MEPDG is an analysis tool. The output from the MEPDG is the predicted performance of a trial pavement section, not pavement thickness design. As discussed in more detail below, some of the distress prediction models in the MEPDG provide a link between HMA material properties and pavement performance that can be used after the mixture design is completed to verify that an HMA mixture will provide acceptable performance for a specific project. MEPDG Input Levels The MEPDG requires a large amount of information about the pavement being analyzed. This includes data concerning traffic, climate, subgrade soils, the condition of existing pavements for rehabilitation design, and the thicknesses and material properties for each layer of the pavement, including existing pavement layers for rehabilitation design. To provide flexibility for users with different capabilities, the MEPDG uses a three-level hierarchical scheme of data input: Level 1. The input parameter is measured directly. This level provides the most accurate information about the input parameter. The primary Level 1 material property input for HMA is the measured dynamic modulus of the mixture that will be used in the pavement. Level 2. The input parameter is estimated from correlations or regression equations that are embedded in the MEPDG. For Level 2, the dynamic modulus for HMA materials is estimated from gradation, volumetric properties, and measured binder properties.

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Evaluating the Performance of Asphalt Concrete Mixtures 83 Level 3. The input parameter is based on default values provided by the MEPDG software. For Level 3, the dynamic modulus for HMA is estimated from gradation, volumetric properties, and the binder grade. Testing or data collection costs decrease as the hierarchical level increases from Level 1 to Level 3, but the accuracy of the input data also decreases. If performance predictions from the MEPDG are to be used to verify a specific mixture design, Level 1 inputs should be used for all of the HMA material properties. Other levels can be used for the traffic, climate, and the material properties of the other layers. The overall accuracy of the predicted performance, however, will depend on the accuracy of all of the input data, not just the HMA material properties. MEPDG Performance Models for HMA The MEPDG can analyze flexible, semi-rigid, rigid, and composite pavements. For pavements with HMA surfaces, the MEPDG includes performance models to predict the following distresses: Rut depth for HMA layers, unbound aggregate layers, and the subgrade Transverse thermal cracking Alligator cracking due to bottom-initiated fatigue Longitudinal wheel path cracking due to surface-initiated fatigue Reflection cracking Roughness A detailed discussion of the form of the MEPDG performance models is beyond the scope of this manual. The interested reader should refer to the MEPDG user manual and other detailed documentation for the MEPDG. The MEPDG does not include models for durability distresses such as raveling or moisture damage. It is assumed that the potential for these forms of distress will be minimized through proper HMA mixture design. The MEPDG also does not include a model to predict changes in the skid resistance of the pavement with time and traffic. HMA Material Property Inputs HMA material properties are not direct inputs to some of the distress prediction models. The reflection cracking model included in the MEPDG is an empirical function that delays the appearance of existing joints and cracks depending on the thickness of the HMA and the condition of the underlying pavement. The roughness model predicts the International Roughness Index (IRI) for the pavement based on the initial roughness, the amount of rutting and cracking obtained from the other models, and site factors including pavement age, soil type, freezing index, and precipitation. Table 6-5 summarizes the HMA materials properties used by each of the performance models. The dynamic modulus and binder grade data are used by the MEPDG to generate a dynamic modulus master curve for each HMA layer. This requires testing the dynamic modulus at multiple temperatures and frequencies as described in AASHTO PP 61-09. The dynamic modulus master curve is used for the computation of the traffic-induced strains that are used by the rutting, alligator cracking, and longitudinal cracking models. It is also a direct input into the damage models used for alligator and longitudinal cracking. The dynamic modulus testing should be conducted on short-term oven-aged mixture (4 hours at 135C per AASHTO R30), compacted to the expected in-place air void content of the pavement. The alligator and longitudinal cracking models also require in-place volumetric properties of the HMA layers, specifically the air void content and the effective binder content. These volumetric

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84 A Manual for Design of Hot Mix Asphalt with Commentary Table 6-5. Summary of HMA materials properties used by the MEPDG performance models. Thermal Alligator Longitudinal Reflection HMA Property Rutting Cracking Cracking Cracking Cracking Roughness Dynamic Modulus X X X Indirect* Binder Grade X X X Indirect* In-Place Air Void X X X Indirect* Content In-Place Effective X X Indirect* Binder Content In-Place VMA X Indirect* Low Temperature X Indirect* Creep Compliance Low Temperature X Indirect* Tensile Strength * The MEPDG estimates roughness from rutting and cracking predictions, which in turn depend on various physical properties as noted here. properties are direct inputs to the models and have a major effect on the predicted load-associated cracking distress. As discuss previously, the resistance of HMA to fatigue cracking increases with an increase in the effective binder content and a decrease in in-place air void content. For thermal cracking analysis, the in-place VMA of the surface mixture is needed to estimate the coefficient of thermal contraction. Creep compliance and tensile strength data for the surface mixture are obtained from AASHTO T 322. The specimens used in this testing should be compacted to the expected in-place air void content of the pavement, then long-term oven aged in accordance with AASHTO R 30 before testing. Overview of Using the MEPDG to Verify an HMA Mixture Design As discussed previously, the MEPDG is a comprehensive pavement analysis tool that can predict the performance of a given pavement section. The accuracy of the predicted performance depends, in part, on the accuracy of the input data. Detailed information on traffic, climate, subgrade soils, and unbound layers, and existing pavement conditions for rehabilitation design are needed in addition to materials properties for the HMA layers. The User Manual for the MEPDG provides guidance for the selection of specific input data. The MEPDG can be used to predict the amount of rutting, bottom-up fatigue cracking, top-down fatigue cracking, and thermal cracking in a pavement section for mixture-specific HMA properties. The change in roughness caused by these distresses can also be predicted. Any or all of these may be used as criteria to judge the acceptability of the HMA mixture for the specific pavement analyzed. Reflective cracking should not be used as a criterion because the MEPDG model for reflective cracking is empirical and is not affected by the properties of the HMA. Rut Resistance To evaluate only the rutting resistance of an HMA mixture, the E* AMPT Specification Criteria Program as described in NCHRP Report 580, not the MEPDG, should be used. This program uses the calibrated rutting model included in the MEPDG, but does not require all of the MEPDG input data for traffic, climate, and properties of the other layers of the pavement. In this approach, rutting in the HMA layer is assumed to be insensitive to underlying layer properties. The E* AMPT Specification Criteria Program provides a predicted rut depth in each HMA layer specified by the user. If rutting will be used in conjunction with other forms of distress to judge the acceptability of the HMA mixture, then a complete analysis using the MEPDG must be performed. In this case,

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Evaluating the Performance of Asphalt Concrete Mixtures 85 the rut depth in each layer of the pavement will be predicted as a function of time for the pavement section. Fatigue Cracking To evaluate the potential for bottom-up (alligator) and top-down (longitudinal) cracking, a complete analysis must be performed using the MEPDG. The user is cautioned that fatigue cracking is more sensitive to traffic, subgrade support conditions, and pavement layer thicknesses than to HMA properties. It may not be possible to adjust HMA properties to obtain acceptable cracking performance if the pavement is not thick enough or the subgrade support is poor. The MEPDG provides separate predictions of alligator and longitudinal cracking with time for the pavement section being analyzed. Alligator cracking is expressed as the percent of the total lane area. Longitudinal cracking is expressed as feet of longitudinal cracking per lane mile. Thermal Cracking To evaluate a mixture for resistance to low temperature cracking, a thermal cracking analysis must be performed with the MEPDG. All climatic data needed for this analysis are stored within a database supplied with the MEPDG; therefore, the user need only specify the longitude and latitude of the pavement and the required material properties. The MEPDG provides a prediction of transverse thermal cracking with time for the pavement section being analyzed. Thermal cracking is expressed as feet of transverse cracking per lane mile. Surface Roughness Within the MEPDG, the change in roughness in a pavement section depends on the initial roughness, the predicted rutting and cracking, and site factors including pavement age, soil type, freezing index, and precipitation. To analyze changes in roughness, a complete analysis must be performed with the MEPDG. In many cases, the initial roughness and site factors, which are not associated with the HMA mixtures used in the pavement, will dominate the prediction. MEPDG Predictions Using the MEPDG as an analysis tool for HMA mixtures is conceptually simple. The basic steps are summarized below. Additional detail for each step is provided in the MEPDG User Manual. 1. Select a trial pavement section. For verification of a mixture design, the pavement section will usually be specified based on the original design of the pavement. 2. Select the performance criteria that will be used. As discussed above the MEPDG predicts the development of various distresses with time for the trial pavement section. The performance criteria used to evaluate the HMA mixture will generally be determined by the specifying agency based on its pavement management policies. 3. Obtain the necessary inputs for the trial pavement section. This is the most time-consuming step. The MEPDG requires a large amount of information about the pavement being analyzed. This includes data concerning traffic, climate, subgrade soils, the condition of existing pavements for rehabilitation design, and the thicknesses and material properties for each layer of the pavement, including existing pavement layers for rehabilitation design. For verification of an HMA mixture, Level 1 material property inputs should be used for the HMA mixture being analyzed. For the remaining inputs, other level data can be used, keeping in mind that the accuracy of the distress predictions depends on the accuracy of the input data. 4. Run the MEPDG software and examine the inputs and outputs for engineering reason- ableness. The software summarizes the inputs. This summary should be examined to ensure that no errors were made during the data input process. If input errors are discovered, fix the errors and rerun the analysis. The software also summarizes the pavement layer moduli

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86 A Manual for Design of Hot Mix Asphalt with Commentary for each month of the analysis. These summaries should be examined to ensure that they are reasonable. Temperature and aging change the modulus of HMA layers over time. Frost and moisture content change the modulus of unbound materials on a seasonal basis. Finally, the software summarizes all distresses by month over the design life of the pavement. These should be examined carefully to see if they appear reasonable and then compared to the performance criteria. 5. Modify the HMA mixture properties to improve performance. The evolution of distress over the design life of the pavement should be studied carefully to identify potential adjustments that can be made to the mixture to improve the predicted performance. The next section presents guidance for adjusting HMA mixtures based on the distresses predicted by the MEPDG. Mixture Adjustments Based on MEPDG Predictions The distress prediction models in the MEPDG are driven by the stiffness of the HMA layers (dynamic modulus and creep compliance), the low-temperature strength of the HMA surface layer, and the in-place volumetric properties of the HMA layers. Therefore, to change the predicted level of distress by changing HMA mixture properties, the change must affect the properties listed above. The effects of changing HMA mixture properties are specific to the distress type, and it is not uncommon that actions taken to improve HMA rutting performance result in an adverse effect on cracking performance. The exception to this rule is the in-place air void content. Decreasing the in-place air void content of the mixture will improve the performance for all distresses. Recommended mixture adjustments are presented below for rutting, alligator cracking, longitudinal cracking, and thermal cracking. It is recommended that users of the MEPDG perform a sensitivity analysis for the pavement section to determine the magnitude of adjustment needed. In some cases, the adjustments may not be possible with the mixture types and binder grades available. In such cases, changes to the pavement structure may be needed to obtain acceptable performance predictions. HMA Layer Rutting Within the MEPDG, the only way to decrease the predicted rutting within the HMA layers of a pavement is to increase the dynamic modulus of the mixture. The E* AMPT Specification Criteria Program, described in NCHRP Report 580, can be used to determine the minimum dynamic modulus needed to keep the predicted rutting below a specified level. The MODULUS spreadsheets in the EXCELTM workbook that accompanies this manual provide tools for estimating mixture dynamic modulus values from mixture composition. These tools should be used to estimate mixture properties needed to meet the minimum dynamic modulus determined from the E* AMPT Specification Criteria Program. The mixture design factors that affect the dynamic modulus are listed below in order of importance: High-Temperature Binder Grade. The high-temperature binder grade has the greatest effect on the dynamic modulus of the HMA mixture. Increasing the high temperature binder grade one level will increase the dynamic modulus of the mixture approximately 25%. Design VMA. VMA is the sum of air void content and effective binder content in the mixture, which are the components of HMA that deform under load. The modulus of HMA increases with decreasing VMA. A 1% decrease in design VMA will increase the dynamic modulus approximately 5%. Nominal Maximum Aggregate Size (NMAS). Larger NMAS mixtures have lower design VMA. Increasing the nominal maximum aggregate size of the mixture one level will increase the dynamic modulus approximately 5%. In-Place Air Void Content. In-place air void content affects the in-place VMA of the mixture. The MEPDG predicts performance based on the properties of the in-place mixture. Decreasing in-place air void content 1% will increase the dynamic modulus approximately 5%.

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Evaluating the Performance of Asphalt Concrete Mixtures 87 Filler Content. Increasing the filler content of the mixture will increase the dynamic modu- lus. Within the filler contents allowed for dense-graded mixtures, a 1% increase in the percent passing the #200 sieve will increase the dynamic modulus approximately 1.5%. Alligator Cracking (Bottom-Up Fatigue Cracking) Within the MEPDG, alligator cracking depends on pavement thickness, subgrade support conditions, and the properties of the lowest asphalt-bound layer in the pavement. Fatigue cracking can be decreased by increasing the pavement thickness, improving subgrade support, or enhancing the HMA properties for the lowest layer. Alligator cracking is generally more sensitive to changes in thickness and subgrade support than to changes in the properties of the bottom HMA layer. The effective binder content, VBE, and in-place density are direct inputs to the fatigue cracking model in the MEPDG. Increasing the effective binder content and decreasing the in-place air void content of the lowest HMA layer will substantially decrease the predicted alligator cracking in the pavement. As discussed previously, use of dense-graded mixtures with higher design VMA will decrease the predicted alligator cracking compared to that for mixtures with more typical VMA values. The effective binder content of these mixtures is up to 1% higher than that for the standard mixtures. The effective binder content can also be increased by decreasing the nominal maximum aggregate size of the lowest HMA layer. A one-level decrease in nominal maximum aggregate size also increases the effective binder content by 1%. The effect of decreasing air void content is similar to that of increasing effective binder content. Alligator cracking is affected to a lesser degree by the dynamic modulus of the lowest HMA layer. For pavements with 5 inches or more of HMA, alligator cracking predicted by the MEPDG decreases with an increase in the dynamic modulus. For pavements with 3 inches or less of HMA, the predicted alligator cracking decreases with a decrease in the dynamic modulus. As discussed above for rutting, changing binder grade is the most efficient way of changing the dynamic modulus of HMA. Longitudinal Cracking (Top-Down Fatigue Cracking) Within the MEPDG, top-down cracking depends heavily on the properties of the surface HMA layer. Since effective binder content and in-place density are direct inputs to the fatigue model in the MEPDG, these properties for the surface HMA layer have a major effect on the predicted longitudinal cracking. Increasing the effective binder content and decreasing the in-place air void content of the surface HMA layer will substantially decrease the predicted longitudinal cracking in the pavement. As discussed previously, the use of dense-graded mixtures with higher design VMA will decrease the predicted longitudinal cracking compared to that for the standard mixtures. The effective binder content of these mixtures is up to 1% higher than that for the standard mixtures. The effective binder content can also be increased by decreasing the nominal maximum aggregate size of the surface HMA layer. A one-level decrease in nominal maximum aggregate size also increases the effective binder content by 1%. The effect of decreasing air void content is similar to that for increasing effective binder content. Longitudinal cracking is affected to a lesser degree by the dynamic modulus of the surface HMA layer. Decreasing the dynamic modulus of the surface layer will decrease the amount of longitudi- nal cracking that occurs in the pavement. As discussed above for rutting and alligator cracking, changing binder grade is the most efficient way of changing the dynamic modulus of HMA. Thermal Cracking Within the MEPDG, the predicted thermal cracking depends on the environment at the project location, the total thickness of the HMA, and the properties of the surface HMA layer.

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88 A Manual for Design of Hot Mix Asphalt with Commentary Table 6-6. Summary of effect of mixture composition on performance predictions. Alligator Alligator Thermal Cracking Cracking Longitudinal HMA Property Rutting Cracking HMA 5 in HMA < 3 in Cracking High Temperature Increase to Increase to Decrease to Decrease to Binder Grade improve improve improve improve Low Temperature Decrease Binder Grade to improve Design VMA Decrease to Increase to Increase to Increase to improve improve improve improve Design VFA Increase to improve Filler Content Increase to improve In-Place Air Void Decrease to Decrease to Decrease to Decrease to Decrease to Content improve improve improve improve improve For a given project, the predicted thermal cracking can be decreased by increasing the HMA thickness or improving the low-temperature properties of the surface layer. The predicted amount of thermal cracking will decrease with an increase in either the tensile strength or creep compliance of the surface mixture. Low-temperature tensile strength increases with increasing voids filled with asphalt, VFA. A 5% increase in VFA will increase the low-temperature tensile strength approximately 85 psi. In-place properties of the HMA layer are used in the MEPDG predictions; therefore, the in-place air void content also affects the tensile strength of the mixture. For a given binder content, decreasing the in-place air void content increases VFA and the tensile strength of the mixture. Polymer-modified binders exhibit approximately 8% higher low-temperature strengths compared to neat binders. The creep compliance of the mixture is affected by the same properties that affect the dynamic modulus of the mixture. Low temperature binder grade is by far the most important factor affecting the creep compliance of the mixture. Decreasing the low temperature grade by one level increases the creep compliance by approximately 25%. VMA and in-place air void content have smaller effects. Increasing the VMA or in-place air void content 1% will increase the creep compliance by approximately 5%. Summary Table 6-6 summarizes the effects of mixture composition on performance predictions using the MEPDG. The properties highlighted in bold for each distress have the greatest effect on the predicted performance. A Note on Modulus, HMA Mix Design, and Pavement Design Using the MEPDG It is likely that many state highway agencies will eventually adopt the MEPDG for designing flexible pavements. In most cases, pavement designs--at least preliminary designs--will be done well in advance of developing or selecting HMA mix designs for a given pavement. This will involve making assumptions about the type of mixture used, and most importantly, its E* values as a function of temperature. In such situations, the potential performance of the HMA mixture should be verified by comparing the E* value assumed in the pavement design with that developed by the mix design. These latter E* values can be determined in two ways. For pavements subject to relatively low traffic levels (below 3 million ESALs), estimated values for E*

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Evaluating the Performance of Asphalt Concrete Mixtures 89 can be used; the HMA Tools spreadsheet can be used to provide such estimates at virtually any combination of frequency and temperature. For more critical pavements, an E* master curve should be measured and compared with the E* values assumed during development of the pavement design. If there are discrepancies, the mix design should be modified--in general, the most effective way of modifying E* values for an HMA mix design is to change the binder: the stiffer the binder, the higher the E* values will be. The HMA Tools modulus prediction tool can be used to estimate modulus early in the mix design process, even for critical mixtures that will eventually require E* testing. Thus, potential mix designs that do not provide proper E* values need not be evaluated further. As with other aspects of the MEPDG and related performance testing, there will likely be many differences in the way E* values will be used in both the pavement design and mix design process and differences in when these requirements will be implemented. Engineers and technicians responsible for mix design should refer to the appropriate state standards for details of verifying mix design modulus. Bibliography AASHTO Standards M 320, Performance-Graded Asphalt Binder R 30, Mixture Conditioning of Hot-Mix Asphalt (HMA) PP 60-09, Preparation of Cylindrical Performance Test Specimens Using the Superpave Gyratory Compactor (SGC) PP 61-09, Developing Dynamic Modulus Master Curves for Hot Mix Asphalt (HMA) Using the Asphalt Mixture Performance Tester (AMPT) T 320, Determining the Permanent Shear Strain and stiffness of Asphalt Mixtures Using the Superpave Shear Tester (SST) T 321, Determining the Fatigue Life of Compacted Hot Mix Asphalt (HMA) Subjected to Repeated Flexural Bending. T 322, Determining the Creep Compliance and Strength of Hot Mix Asphalt (HMA) Using the Indirect Tensile Test Device T 324, Hamburg Wheel-Track Testing of Compacted Hot Mix Asphalt (HMA) TP 63-09, Determining the Rutting Susceptibility of Asphalt Paving Mixtures Using the Asphalt Pavement Analyzer (APA) TP 79-09, Determining the Dynamic Modulus and Flow Number for Hot Mix Asphalt (HMA) Using the Asphalt Mixture Performance Tester (AMPT) Other Publications Aschenbrener, T., R. B. McGennis, and R. L. Terrel (1995) "Comparison of Several Moisture Susceptibility Tests to Pavements of Known Field Performance," Journal of the Association of Asphalt Paving Technologists, Vol. 64. Bonaquist, R. (2008) NCHRP Report 629: Ruggedness Testing of the Dynamic Modulus and Flow Number Tests with the Simple Performance Tester, TRB, National Research Council, Washington, DC, 137 pp. Bonaquist, R., D. W. Christensen, and W. Stump (2003) NCHRP Report 513: Simple Performance Tester for Super- pave Mix Design: First Article Development and Evaluation TRB, National Research Council, Washington, DC, 169 pp. Bonaquist, R. (2008) NCHRP Report 614: Refining the Simple Performance Tester for Use in Routine Practice, TRB, National Research Council, Washington, DC, 153 pp. Bukowski, J. R., and T. Harman (1997) Minutes of the Superpave Mixture Report Task Group, Meeting of September 1997. Christensen, D. W., and R. F. Bonaquist (2006) NCHRP Report 567: Volumetric Requirements for Superpave Mix Design, TRB, National Research Council, Washington, DC, 57 pp. Christensen, D. W., R. Bonaquist, and D. Jack (2000) Evaluation of Triaxial Strength as a Simple Test for Asphalt Concrete Rut Resistance, Final Report, PennDOT University-Based Research, Education and Technology Transfer Program, The Pennsylvania State University, State College, PA, August. NAPA (2001) Moisture Susceptibility of HMA Mixtures: Identification of Problems and Solutions, Lanham, MD, 24 pp.

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90 A Manual for Design of Hot Mix Asphalt with Commentary The Asphalt Institute, Causes and Prevention of Stripping in Asphalt Pavements (ES-10), 2nd Ed., 8 pp. The Asphalt Institute, Moisture Sensitivity (MS-24), 1st Ed., 48 pp. User Manual for the M-E Pavement Design Guide (2007) March. Von Quintus, H., J. Mallela, and M. Buncher, Transportation Research Record 2001 "Quantification of Effect of Polymer-Modified Asphalt on Flexible Pavement Performance," TRB, National Research Council, Wash- ington, DC Witczak, M. W., et al. (2000) "Specimen Geometry and Aggregate Size Effects in Uniaxial Compression and Constant Height Shear Tests," Journal of the Association of Asphalt Paving Technologists, Vol. 69. Witczak, M. W. (2007) NCHRP Report 580: Specification Criteria for Simple Performance Tests for Rutting, TRB, National Research Council, Washington, DC, 108 pp. Zaniewski, J. P., and G. Srinivasan (2004) Evaluation of Indirect Tensile Strength to Identify Asphalt Concrete Rutting Potential, Asphalt Technology Program, Department of Civil and Environmental Engineering, West Virginia University, Morgantown, WV, May.