Comparing the Volumetric and Mechanical Properties of Laboratory and Field Specimens of Asphalt Concrete (2016)

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24 C H A P T E R 3 This chapter describes the experimental program used to generate and analyze the data required to meet the project objectives. 3.1 Determine Process-Based Factors Research conducted in Phases I and IA of this project indi- cated that the effects of some process-based factors on the vari- ability of properties from the three specimen types should be quantified. Several discussions with NCHRP were held to iden- tify the most relevant construction-based factors to consider. The factors of interest are listed in Table 3-1. 3.2 Mixture Evaluation This section summarizes the volumetric and mechanical test methods conducted in this project. Chapter 4 describes the test procedures used in detail. Table 3-2 presents the volu- metric properties evaluated and their respective test proce- dures. Table 3-3 presents the mechanical test procedures used in this study. 3.3 Test Factorial Design In the experimental plan, each process-based factor was var- ied between two contrasting levels (low and high) based on a 2k factorial design, where k is the number of factors. Based on the proposed factorial design, the total number of test combina- tions for each volumetric and mechanical property of inter- est was 25 factor combinations multiplied by three specimen types for a total of 96 combinations. Each test combination was conducted in triplicate to determine within-specimen variability. In total, 96 test combinations × 8 volumetric prop- erties × 3 replications = 2,304 properties (576 samples) were required for the full factorial design in order to assess the vari- ability in volumetric properties, and 96 test combinations × 3 mechanical properties × 3 replications = 768 test samples were needed for the assessment of the variability in the selected mechanical properties. The number of mechanical samples assumes that the axial dynamic modulus was only to be con- ducted for LL and PL samples, given sample size limitations. Given the large numbers of required test samples, a frac- tional factorial design was used to reduce the number of tests required to assess the influence of the factors shown in Table 3-1. A quarter fractional design reduced the number of test samples (25-2 = 8 × 3 specimen types = 24 test combi- nations) to 24 × 8 × 3 = 576 for the volumetric properties and 24 × 3 × 3 = 216 for the mechanical properties. These numbers were manageable for the proposed volumetric and mechani- cal properties. Results of the fractional factorial analysis allow the quantification of causes of variability within and among the three specimen types. However, a main effects model must be used, which eliminates 2-factor and higher order inter- actions from the model. All conclusions presume the validity of the main effects model. To illustrate, Table 3-4 presents a sample of the factor com- binations that were to be conducted to assess levels and causes of variability within and among the three specimen types for asphalt binder content (AC). Table 3-4 was repeated for each specimen type and the differences (D) between the three speci- men types (PF–PL, PL–LL, and PF–LL) were calculated. The statistical analysis software (SAS) PROC FACTEX feature was used to develop the fractional factorial design. Definitions of factors 1 through 5 are given in Table 3-1. A negative sign indicates that the factor is at the low level and a positive sign indicates that the factor is at the high level. For each factor combination presented in Table 3-4, the researchers quantified the responses (i.e., D between the AC averages [for the three replications] measured for the three specimen types, and the levels of variability measured for LL, PL, and PF specimens). The main effect of a given factor (1 to 5) is a measure of the change in response (i.e., variability) due to a change in an indi- vidual factor. The main effect for each factor is determined based on Equation 3: Experimental Program

25 Table 3-1. Description of process-based factors. Factor Evaluation Method 1. Baghouse Fines Evaluate the effects of using baghouse fines on volumetric and mechanical mix properties. Evaluate mixtures both with and without using baghouse fines. In addition, sample baghouse fines and characterize to determine if the type of baghouse fines has an effect. 2. Reheating Reheating is determined by allowing the mixture to cool to room temperature, then heating to compaction temperature and compacting. Prepare specimens after mixture is allowed to cool for a period of 3 days. 3. Aggregate Absorption Measure absorption of the aggregates in the mixture using water absorption. Mixtures are classified as having either high or low absorption. 4. Aggregate Degradation Toughness of the aggregates in the mixture is used to determine the amount of aggregate degradation in the mixture. Classify mixtures as either soft or hard, based on the toughness of the aggregates used in the mixture. Aggregate degradation shall be measured using the Micro Duvall. 5. Aggregate Stockpile Moisture Monitor aggregate stockpile moisture. Produce HMA mixtures after a significant rain event and during dry conditions. Table 3-3. Mechanical testing method. Mechanical Property Test Method Loaded-Wheel Test AASHTO T 324 Axial Dynamic Modulus AASHTO T 342 Indirect Dynamic Modulus Kim et al. (2004) 8 (3)1e d R i i i i n∑ = = where ei = main effect for factor i = 1, 2, 3, 4, and 5; n = number of design runs (n = 8); Ri = response; and di = ± sign from Table 3-4 (i.e., -1 and 1). For example, to calculate the main effect for asphalt absorp- tion by aggregates, e3, on the differences between PL and LL, Equation 4 is used: ( ) ( )(( ( )( ( ( ) ( )( ( )( ))= − ∆ + − ∆ + − ∆ + − ∆ + + ∆ + ∆1 2 3 4 7 8 8 (4) 3e  where D = differences between PL and LL averages for each factor combination presented in Table 3-4. Table 3-4. SAS fractional factorial design output. Factor Combinaon Number Factor ID Response IDBaghouse Return Mixture Reheang Aggregate Absorpon Aggregate Degradaon Aggregate Moisture 1a - - - - - R1 2 + - - - - R2 3 - + - - - R3 4 + + - - - R4 5 … … … … … … 6 … … … … … … 7 - + + + + R7 8 + + + + + R8 aFor example, AC is measured for a mix produced with no baghouse fines and for a mixture prepared with low absorption and soft aggregates. Prior to production, the moisture in the aggregates’ stockpile is low. Testing was conducted at the plant with no reheating. Volumetric Property Test Method Air Voids AASHTO T 166 AASHTO T 209 AASHTO T 269 Mixture Maximum Specific Gravity, Gmm AASHTO T 209 Asphalt Binder Content AASHTO T 164 Aggregate Gradation AASHTO T 30 Aggregate Bulk Specific Gravity, Gsb AASHTO T 84 AASHTO T 85 Table 3-2. Volumetric testing method.

26 For example, AC is measured for a mix produced with no baghouse fines and for a mix prepared with low absorption and soft aggregates. Before production, the moisture in the aggregate stockpile is low. Testing was conducted at the plant with no reheating. The fractional factorial design is clarified in Table 3-5 to show the factor combinations required to complete the main effects model. The researchers managed to collect mixtures that satisfied six of the eight conditions shown in Table 3-5, but Mixtures 2 and 4 were difficult to locate or impractical for contractors to produce and were excluded. Therefore, the research was completed by the collection of 13 mixtures com- monly produced in different climatic regions of the United States. However, because of complications in production, only 11 mixtures were included in the analysis. 3.4 Mixture Descriptions Mixture descriptions are provided in Table 3-6. All JMFs are presented in Appendix D which is available on the project web page. Drum plants were used in the production of each mixture. Mixture ID Baghouse Fines Reheang Aggregate Absorpon Aggregate Degradaon Aggregate Moisture Content Mix 1 No No Low So
High Mix 2 * No No High Hard Low Mix 3 No Yes Low Hard Low Mix 4* No Yes High So High Mix 5 Yes No Low Hard High Mix 6 Yes No High So Low Mix 7 Yes Yes Low So Low Mix 8 Yes Yes High Hard High • Not produced Table 3-5. Fractional factorial design. Mix ID Source Design Asphalt Binder Content PG Asphalt Binder Used % RAP Binder Replacement Ratio Comments 1WI Mathy Construction of Onalaska, WI from a project on U.S. Highway 61 5.7% 64-28 20% 17% Medium traffic (2,000,000 ESAL) 3MN Minnesota DOT from a project on Highway 8 in Chisago County near Lindstrom, MN 5.0% 64-28 25% 26% The ‘no reheat’ specimens were not provided for this mixture, which was acceptable because it satisfies the factorial presented in Table 3-5. 5WI Stark Asphalt of Milwaukee, WI, from a project on a segment of State Highway 60 5.3% 64-28 15% 13% The nominal maximum aggregate size of the mixture was 12.5 mm. 5LA90 Prairie Construction of Opelousas, LA, from a project on U.S. Highway 90 4.1% 64-22 20% 29% 5LA61 Barriere Construction of Metairie, LA, from construction on U.S. Highway 61 4.7% 76-22m 14% 21% Elastomeric-polymer-modified 5VA Virginia DOT from a mixture produced by Superior Paving Corp 5.2% 64-22 30% 29% 5SD South Dakota DOT from a mixture produced by Spencer Quarry 5.3% 58-34 20% 28% Hydrated lime was used as an anti-strip and was introduced using a pug mill at the plant, prior to drying the aggregate. Table 3-6. Mixture descriptions.

27 Mix ID Source Design Asphalt Binder Content PG Asphalt Binder Used % RAP Binder Replacement Ratio Comments 6FL Community Asphalt from the rehabilitation of a state highway in Lee County, FL 6.0% 76-22 15% 17% 7IA Mathy Construction of Onalaska, WI, from construction on U.S. Highway 169 in Humboldt County, IA 6.2% 58-28 12% 9.6% 5.0% 82-22 CRM 0% 0%8LA Diamond B Construction of Amite, LA, from a project on State Highway 441 in Tangipahoa Parish, LA The design asphalt binder content was 5.0% using a polymer-modified PG 70- 22M asphalt binder. The paving mixtures PL and PF were produced using PG 82-22 asphalt binder modified with crumb rubber. To remain consistent with the plant-produced mixture, the asphalt binder used for LL specimen fabrication was PG 82-22. The mixture contained 0% RAP. The plant was having trouble getting density at the JMF asphalt binder content. Therefore, the target asphalt binder content was increased to 5.4% to obtain laboratory and field air void values meeting specifications. The need for the higher asphalt binder content may be attributed to the use of crumb rubber in plant production, which increased the binder stiffness over that of the original PG 70-22M asphalt binder. Table 3-6. (Continued).