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27 Equipment calibration--Calibration is usually per- Interpretation of the results formed once at the beginning of the data collection Type of analysis conducted--the information col- season (or every two years), with verification testing lected can be used for assessing the overall structural taken at control segments during data production. capacity of the pavement (e.g., computing a surface Measurement environment--Annual variations in pave- modulus of an effective Structural Number or deter- ment friction have been detected; therefore, annual test- mining the moduli of the various pavement layers ing of the network is recommended (61). Temperature using backcalculation). has been shown to be one of the contributing factors (64). Software used--the backcalculation software used Some states use seasonal (typically monthly) correction typically affects the resulting layer properties. factors for the measured friction. Ground Penetrating Radar Structural Evaluation Some agencies have used GPR to determine layer thickness Sources of variability on FWD measurements include the data. This device operates by using electromagnetic waves to following: identify and locate interfaces between layers within the pave- ment, which in turn allows for determination of layer thick- Equipment used--Different FWDs use slightly differ- nesses. For GPR to distinguish layer separations, the pavement ent configurations and sensing technologies. In addi- layers must have different dielectric properties. Additionally, tion, available devices use a variable number of sensors. higher frequency waves yield better resolution, whereas lower Equipment operation/testing protocol frequencies allow for further penetration into the pavement, Load--Most agencies use 9,000 lb, whereas some resulting in upper layer profiles being more accurate than those add additional tests at variable load levels to assess of lower layers (40). Testing has shown that GPR provides the nonlinearity of some of the materials. accurate layer thicknesses if calibrated with just a few cores, Sensor spacing--Several devices and testing pro- and the GPR measurements can be used to influence future tocols use different sensor spacing; however, the coring requirements (65). LTPP data collection guidelines have helped stan- dardize them. EFFECTS OF NETWORK SIZE Sitting errors--Some protocols call for one or two ON QUALITY MANAGEMENT initial drops to improve the contact between the plate and the pavement and the repeatability of the The size of the network appears to have an effect on the quality measurements. management procedures. For example, it takes considerably Equipment calibration is important to correct sys- more effort to conduct quality assurance checks for large net- tematic errors in the sensor measurements and there works than for smaller ones. Because large agencies have to are regional sites that have been established for this review large amounts of data they appear to be more motivated purpose, as discussed in chapter four. to develop formal quality management plans. Figure 12 shows Testing spatial frequency--Although closely spaced that large agencies (e.g., with more than 25,000 lane-miles) tests are preferred for accurately assessing the struc- were noticeably more likely to have a formalized quality man- tural capacity of the pavements, this reduces produc- agement plan, or have one under development, than were the tivity and increases cost. small agencies. This is logical given that agencies with larger Lane tested--Testing in Indiana showed that structural networks would receive higher quantities of data, and the capacity in one direction of an Interstate highway was occurrence of systematic errors could result in large quantities nearly identical to the capacity in the opposing direc- of poor data. Larger networks are also more costly to maintain tion. However, non-interstate roads showed more vari- on an annual basis, making development of new and improved ability and more variable results can be expected in quality management methods more cost-effective. highways where opposite lanes were constructed at dif- ferent times and/or with different structural materials Network size also appears to play a minor role in the and designs. condition data quality management process. Agencies with Measurement environment--Environmental factors have larger networks (e.g., more than 25,000 lane-miles) under substantial influence on the pavement response and thus their management collected data less frequently than agen- on the measured deflections cies with fewer than 5,000 lane-miles. This trend held not Temperature affects the stiffness of the asphalt-based only for highways, but arterials, collector, and local roads materials. Deflection adjustment factors have been as well. The same was true for smoothness data collection; developed at the national (LTPP) and state level to agencies with larger networks generally collected data less account for temperature variations. often than those with smaller networks. This is illustrated Moisture--The presence of water affects the bearing in Figure 13, which summarizes the average (considering capacity of soils and unbounded pavement materials. the various functional categories) data collection frequency

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28 100% 9% 25% 80% 35% 50% 36% 17% 60% 75% 35% 40% 55% 58% 0% 50% 20% 25% 29% 0% 0% Less than Between 5,000 Between Between More than 5,000 miles and 10,000 10,000 and 25,000 and 50,000 miles miles 25,000 miles 50,000 miles No No; but under development Yes FIGURE 12 Percentage of agencies having a quality management plan as a function of network size. 100% 0% 4% 0% 0% 2% 20% 27% 80% 34% 36% 61% 60% 40% 80% 73% 56% 62% 20% 39% 0% Less than Between 5,000 Between Between More than 5,000 miles and 10,000 10,000 and 25,000 and 50,000 miles miles 25,000 miles 50,000 miles Every 4 years or more Every 2 to 3 years Once a year (a) Surface Distress 100% 0% 0% 0% 8% 13% 25% 30% 80% 25% 36% 59% 60% 40% 75% 70% 63% 56% 20% 41% 0% Less than Between 5,000 Between Between More than 5,000 miles and 10,000 10,000 and 25,000 and 50,000 miles miles 25,000 miles 50,000 miles Every 4 years or more Every 2 to 3 years Once a year (b) Smoothness FIGURE 13 Temporal data collection frequency for (a) surface distress and (b) smoothness as a percent of agencies collecting the pavement condition indicator.