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38 CHAPTER 2 Materials Testing for Construction Quality Determination This chapter focuses on the effectiveness of the NDT tech- or accepted. The DSPA accurately identified most of the areas nology and device for measuring or judging the quality with anomalies or material differences. The GeoGauge did a of construction of unbound materials and HMA mixtures. reasonable identification of the areas, followed by the DCP "Effectiveness" is defined as the ability or capability of the NDT and LWD. The EDG and GPR devices did a poor job in iden- technology or device to detect changes in unbound materials tifying the different areas. Table 17 demonstrates the success or HMA mixtures. The research problem statement noted rate by each device in identifying the physical differences of that, with the development of the MEPDG, layer modulus will the unbound material within a project. become a more important property and should be considered The DSPA and GeoGauge have acceptable success rates, a quality characteristic. Thus, the emphasis of the interpretation while the EDG and GPR have unacceptable rates. Significantly, of data presented in Chapter 5 (available in NCHRP Web-Only the modulus measuring devices (DSPA, GeoGauge, DCP, and Document 133) was on identifying those NDT devices that LWD) found all the hypotheses to be true for the crushed aggre- can consistently and accurately determine when changes gate materials (TH-23 and US-280 projects), while the volumet- occur within the construction process, as well as confirm the ric devices (GPR and EDG) rejected all the hypotheses. This assumptions used in pavement structural design. observation suggests systematic differences between the tech- nologies. Some of the important differences observed between 2.1 Identification of Material the technologies and devices and the reason for the higher suc- Anomalies and Differences cess rates for the DSPA and GeoGauge are listed as follows: The testing under the Part A field evaluation was to con- The DSPA and GeoGauge induce small dynamic stress firm that the NDT technologies can identify differences in waves into the material being tested. These small responses construction quality of unbound pavement layers and HMA emphasize the effect of changes in the density and moisture mixtures. The specific hypothesis used for this part of the content of the material being tested. Significantly, both field evaluation was that the NDT technology and device can devices measure the responses in a relatively limited area detect changes in the physical condition of pavement materials and depth. In fact, the sensors for the DSPA (refer to Fig- and soils that affect flexible pavement performance. Tables 14 ures 2 and 3) were spaced so the measured responses would and 15 present the anomalies and different conditions placed be confined to the layer being tested. The GeoGauge mea- along each project. surements have a deeper influence, so its results can be A standard t-test and the SNK mean separation procedure influenced by the supporting layer. The depth of influence using a 95 percent confidence level were used to determine depends on the thickness and stiffness of the material being whether the areas with anomalies were significantly different tested. from the other areas tested. The following subsections sum- The DCP is a point-based test and estimates the modulus marize the results from the statistical analyses of the data of the material from the average penetration rate through collected within Part A of the field evaluation. the material. The penetration rate is dependent on the dry density of the material. However, there are other physical properties that have a greater effect on the penetration rate. 2.1.1 Unbound Layers The amount and size of the aggregate particles can have a Table 16 tabulates the results for checking the hypothesis larger effect on the estimated modulus than for the DSPA for the unbound material layers. The shaded cells in Table 16 or GeoGauge, especially for fine-grained soils with some designate those where the hypothesis was incorrectly rejected aggregates. For example, the DCP found all the hypotheses

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39 Table 14. Local anomalies in the unbound materials and soils placed along each project included in Part A. Project Unbound Sections Description of Differences Along Project Identification No planned difference between the points SH-21 Subgrade, Area 2, No IC Rolling tested. High Plasticity Clay; With IC rolling, the average density should Caldwell, Texas Area 1, With IC Rolling increase; lane C received more roller passes. Prior to IC rolling, Lane A (which is further Lane A of Sections 1 & 2 I-85 Embankment, from I-85) had thicker lifts & a lower density. Low Plasticity Clay; After IC rolling, the average density should Auburn, Alabama All sections tested increase & the variability of density measurements should decrease. Construction equipment had disturbed this TH-23 Embankment, South Section Lane C area. In addition, QA records indicate that this Silt-Sand-Gravel area has a lower density. Mix; Spicer, The area with the higher density and lower Minnesota North Section Lane A moisture content--a stronger area. SH-130, Improved Embankment, No planned differences between the areas All sections tested Granular; tested. Georgetown, Texas Curb and gutter section; lane C was wetter than Section 2 (middle section) the other two lanes because of trapped water TH-23, Crushed Lane C along the curb from previous rains. The water Aggregate Base; extended into the underlying layers. Spicer, Minnesota Section 1 (south section) Area with a higher density and lower moisture Lane A content--a stronger area. Records indicate that this area was placed with US-280, Crushed higher moisture contents and is less dense. It is Stone Base; Opelika, Section 4 also in an area where water (from previous Alabama rains) can accumulate over time. Table 15. Different physical conditions (localized anomalies) of the HMA mixtures placed along projects within Part A. Project HMA Sections Description of Differences Along the Project Identification TH-23 HMA QA records indicate lower asphalt content in this Section 2, Middle or Base; Spicer, area--asphalt content was still within the Northeast Section Minnesota specifications. Section 2, Middle; QA records indicate higher asphalt content in this area, I-85 SMA All Lanes but it was still within the specifications. Overlay; Auburn, This part or lane was the last area rolled using the Alabama Lane C, All Sections rolling pattern set by the contractor, and was adjacent to the traffic lane. Densities lower within this area. Initial Test Sections, Segregation identified in localized areas. In addition, defined as A; Section QA records indicate lower asphalt content in this area 2, All Lanes of the project. Densities lower within this area. Supplemental Test Sections Near US-280 HMA Crushed Stone Base Segregation observed in limited areas. Base Mixture; Sections, Defined as Opelika, Alabama B. IC Roller Compaction Effort Higher compaction effort was used along Lane C. Section, Defined as C. SH-130 HMA Base Mixture; All Sections No differences between the different sections tested. Georgetown, Texas

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40 Table 16. Effectiveness of NDT devices to identify areas of unbound layers with anomalies or different physical conditions. NDT Device Project Hypothesis EDG, DSPA, DCP, Defl., GPR Geo., ksi pcf ksi ksi ksi Lane A 14.65 107.6 12.6 25.2 5.20 --- Pre-IC Lanes Rolling 15.99 108.1 16.3 34.0 5.62 --- B,C,D Lane A is weaker No Yes Yes Yes No --- I-85 Low Area 1 21.61 108.3 17.1 39.4 6.93 9.99 Plasticity Soil Post-IC Area 2 23.00 107.7 19.0 40.4 6.21 11.78 Embankment No Planned Difference Yes No No Yes Yes No Pre-IC 15.65 108.0 15.4 31.8 5.51 --- All areas Post-IC 22.31 108.0 17.7 39.9 6.57 --- Post-IC area is stronger Yes No Yes Yes Yes --- Area 2 No IC --- --- 19.6 23.6 11.9 --- Area 1 With IC --- --- 22.9 27.1 9.1 --- SH-21 High Area 1 is stronger --- --- Yes Yes No --- Plasticity Clay With IC Lane C --- --- 20.1 30.4 9.9 12.9 Rolling Lanes A,B --- --- 24.4 25.4 8.7 8.00 Lane C is stronger --- --- No Yes No Yes So. Area Lanes A,B 18.24 122.7 10.5 43.6 15.16 5.65 No. Area Lanes B,C 29.16 124.1 10.1 35.7 19.01 4.77 No Planned Difference No No Yes No No No TH-23 Silt- Lane C 19.33 122.9 7.5 31.1 11.47 5.58 Sand-Gravel So. Area Lanes A,B 18.24 122.7 10.5 43.6 15.16 5.65 Mix Embankment Lane C is weaker No No Yes Yes Yes No Lane A 20.32 123.9 12.6 51.7 18.52 4.69 No. Area Lanes B,C 29.16 124.1 10.1 35.7 19.01 4.77 Lane A is stronger No No Yes Yes No No Lane A 10.29 123.2 25.4 33.9 21.60 24.2 All lanes Lane B 9.30 123.0 25.5 34.7 20.95 27.8 SH-130 Lane C 9.78 123.8 24.77 33.3 20.74 21.2 Granular No Planned Difference Yes Yes Yes Yes Yes No Improved Embankment Area 1,2 9.74 123.5 26.3 36.5 20.64 24.6 All areas Area 3 9.88 123.1 22.3 28.9 22.01 24.1 No Planned Difference Yes Yes No No Yes Yes South & Lanes A,B 9.37 129.8 14.4 100.4 42.05 16.75 Middle Lane C 10.62 129.8 10.8 50.7 21.33 8.31 Sections Lane C is weaker No No Yes Yes Yes Yes TH-23 So. Area Lanes A,B 9.79 129.9 15.0 110.7 46.45 19.38 Crushed Middle Lane C 10.38 129.8 9.8 28.0 18.55 7.95 Aggregate Section Base All other areas 9.54 129.8 12.8 75.0 33.14 12.31 Lane C, middle section, is No No Yes Yes Yes Yes weaker Lanes A & B, south No No Yes Yes Yes Yes section, are stronger US-280 Lane 4 11.57 148.2 35.1 117.4 34.31 18.53 All areas Crushed Stone Lanes 1,2,3 11.95 147.4 47.9 198.6 50.29 46.46 Base Lane 4 is weaker No No Yes Yes Yes Yes NOTE: The results in the shaded or black cells represent areas where the hypothesis was rejected based on a 95 percent confidence interval, and are inconsistent with the construction records and experimental plan. Table 17. Success rate demonstrated by each device in identifying the physical differences of the unbound material. NDT DSPA GeoGauge DCP LWD GPR EDG Device Success 86 79 64 64 33 25 Rate, %

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41 to be true for the coarse-grained materials and rejected the wet densities from the dielectric values measured with many of the hypotheses for the fine-grained embankment the GPR. Obviously, water contents are not constant within materials with varying amounts of coarse aggregate. a specific area. Errors in the water content will be reflected The LWD induces larger strains into the underlying in the wet density for a specific test. In addition, varying materials. The measured deflections or responses are affected plasticity of the fines and in the gradation of the material is by a much larger area and depth than for the DSPA, difficult to identify with the GPR and EDG by themselves. GeoGauge, and DCP. The modulus calculated from the Variability of the measurements is another reason for the deflections is dependent on the thickness and stiffness of outcome. The GeoGauge had lower variability, followed by the material being tested, as well as the thickness and stiffness the DSPA and DCP. The deflection-based methods had the of the supporting layers. In fact, some resulting modulus greatest variability. The lower the variability, the higher the values were lower than expected for the type of material probability to identify a difference, if a difference exists, being tested (TH-23 embankment and areas of the US-280 given the same number of tests (refer to Section 2.3). crushed stone). The LWD found all the hypotheses to be true where the layer thicknesses were well defined, but In summary, the DSPA and GeoGauge are considered rejected many of the hypotheses for the materials where the acceptable in identifying localized differences in the physical layer thickness was less defined--the embankments. condition of unbound materials. Both the GPR and EDG devices are dependent on the den- sity and water content measurements made with other tra- 2.1.2 HMA Layers ditional test methods. Any errors within those traditional methods are included in the GPR and EDG results. Average Table 18 contains the results of checking the hypotheses for water contents were assumed for each area in calculating the HMA layers. The shaded cells in Table 18 designate those Table 18. Effectiveness of NDT devices to identify areas of HMA layers with anomalies or different physical conditions. NDT Device Project Hypothesis PSPA FWD GPR PQI Section 2 Lanes A,B 285.0 568.9 6.18 149.9 Sections 1,3 Lanes A,B 262.0 405.4 10.14 146.6 I-85 SMA Section 2 is Stronger or Stiffer Yes Yes Yes Yes Overlay Lane C Section 2,3 288.5 NA 8.51 141.6 Lane C Sections 1 215.4 NA 8.62 140.3 Section 1 is Weaker/Less Dense Yes NA No Yes Section 2 All Lanes 454.4 NA 7.04 145.2 Sections 1,3 All Lanes 489.8 NA 6.64 146.6 TH-23 HMA Section 2 is Weaker Yes NA Yes Yes Base Section 4 All Lanes 499.5 NA NA 143.9 No Planned Difference; Sections 1,3,4 Yes NA NA No Initial Sections Section 1 499.9 203.3 7.03 148.0 US-280 Supplemental Sections Sections 1,2 555.0 877.2 5.50 140.4 HMA Base Supplemental Area is Stronger/Denser Yes Yes Yes No Section 1 All Lanes 499.9 203.3 7.03 148.0 Section 2 All Lanes 423.9 125.9 6.81 154.5 US-280 Section 1 is Stronger/Denser Yes Yes No No HMA Base, Longitudinal Joints Confined Joint 305.8 125.5 7.70 145.7 Initial Sections Joints are Less Dense/Weaker Yes No Yes Yes Segregated Areas All Lanes 329.9 144.5 7.28 147.1 Segregated Areas are Less Dense/Stiff Yes No No Yes Section 1 All Lanes 559.8 569.0 5.55 140.4 Section 2 All Lanes 550.2 1185.3 5.45 140.5 US-280 No Planned Difference Yes No Yes Yes HMA Base, Longitudinal Joints All Lanes 596.0 379.0 5.78 135.8 Supplemental Sections Joints are Les Dense/Weaker No Yes No Yes Segregated Areas All Lanes 391.3 707.0 5.64 136.6 Segregated Areas are Less Dense/Stiff Yes No No Yes Section 1 All Lanes 384.9 NA 5.95 126.5 Section 2 All Lanes 292.6 NA 5.61 124.0 I-35/SH-130 Section 3 All Lanes 461.7 NA NA 125.1 HMA Base Section 2 is Weaker/Less Dense Yes NA Yes Yes Joints All Lanes 297.5 NA 5.08 118.8 Joints are Less Dense/Stiff Yes NA No Yes