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Evaluation of Bonded Concrete Overlays on Asphalt Pavements (2022)

Chapter: Chapter 4 - Field Performance of Selected Projects

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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
×
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Suggested Citation:"Chapter 4 - Field Performance of Selected Projects." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of Bonded Concrete Overlays on Asphalt Pavements. Washington, DC: The National Academies Press. doi: 10.17226/26760.
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33   The following provides a brief overview of the data collected and analyzed for each selected BCOA project (individual project portfolios are provided in Appendix C). As noted previously, each project was evaluated using an automated distress survey; a GPR survey; a detailed on-site evaluation incorporating a visual distress survey and faultmeter testing; ultrasonic tomography; FWD testing; coring, DCP measurements, and unbound layer sampling; and laboratory testing. Each evaluation method is summarized in the following subsections. A summary of tests per- formed for this evaluation is shown in Table 17 (see also Appendix D). Automated Distress Surveys Automated distress surveys were conducted in September 2018 on the 20 selected BCOA projects (approximately 176 mi of total length) using a high-speed, high-resolution laser crack measurement system (Figure 16), together with downward-facing images of the pavement surface. The automated condition surveys were used to identify crack type, severity, extent, and transverse and longitudinal profile (Figure 17). Automated distress surveys were conducted in both directions in the outside travel lane (i.e., truck lane). Identified pavement distress included transverse cracking, longitudinal cracking, corner breaks, spalls, patches and patch deteriora- tion, transverse joint faulting, and roughness, as measured by the IRI and determined in accor- dance with ASTM E1926. The majority of 0.10-mi segments surveyed (1,048 segments, or 60%) were in service for 6 to 10 years, 36 segments (2%) for 11 to 15 years, 234 segments (13%) for 16 to 20 years, 262 seg- ments (15%) for 21 to 25 years, and 172 segments (10%) for 26 or more years (Figure 18). On the basis of agency responses, most segments were subjected to low (714 segments, or 41%) or moderate (722 segments, or 41%) traffic, with a few subjected to high traffic (316 seg- ments, or 18%) (Figure 19). Low traffic level is defined as less than 5,000 AADT, moderate is 5,000 to 20,000 AADT, and high is more than 20,000 AADT. For each project, IRI and faulting data from the automated pavement condition surveys were filtered to omit data points outside the project boundaries and at non-BCOA areas (e.g., bridges). The filtered data were aggregated to create average values for each 0.10-mi segment. The downward pavement surface images were used to perform a distress inspection to identify and locate slabs with corner breaks and longitudinal and transverse cracks. The percentage of cracked slabs was determined using the number of slabs for each segment on the basis of slab size and lane width for each project. For all three data sets—IRI, faulting, and percentage of cracked slabs—the values from the ancillary direction (westbound or southbound) were reoriented so that each 0.10-mi station data point was aligned on the same spatial location for both survey directions. The final data sets for C H A P T E R 4 Field Performance of Selected Projects

34 Evaluation of Bonded Concrete Overlays on Asphalt Pavements Figure 16. Data collection vehicle for automated pavement condition survey. (Source: Courtesy of APTech.) Test No. of Projects No. of 0.10-mi Segments Quantity Automated distress survey 20 1,757 175.7 mi GPR survey 20 1,757 175.7 mi Detailed on-site evaluation Visual (manual) distress survey 19a 56 23.8 mi Faultmeter 14 40 921 tests Ultrasonic tomography 15 43 1,433 tests FWD 18 53 3,905 stations Coring BCOA cores 13 38 146 Asphalt cores 12 36 113 DCP and unbound material sampling 11 31 56 tests Laboratory testing Soil classification 12 34 37 tests Atterberg limits 12 34 37 tests Aggregate gradation of base 3 7 7 tests Aggregate gradation of subgrade 10 29 30 tests Concrete compressive strength 7 21 24 tests Concrete split tensile strength 10 28 58 tests Coefficient of thermal expansion 16 29 30 tests Asphalt complex (dynamic) modulus 4 12 14 tests Hamburg wheel tracking 11 14 25 tests Asphalt bulk-specific gravity 5 14 56 tests Concrete–asphalt shear 9 11 20 tests a Because of traffic control contractual constraints, one project was removed from the detailed site investigations. Table 17. Summary of testing. each project and direction were plotted on a single graph, which was used to identify a good, fair, and poor segment for each project in each direction (Figure 20). Plots for all projects are included in Appendix E. For each good, fair, and poor segment, a detailed distress survey was performed to account for other distress such as spalling, shattered slabs, patching, blowups, and durability cracking. As shown in Table 18, good, fair, and poor conditions were based on the categories established by the National Highway Performance Program (NHPP) (Federal Register 2017). Pavement condition within a given project may not be uniform along the entire roadway length; there- fore, identifying segments in good, fair, and poor condition, in strict conformance to criteria shown in Table 18, was not always possible. A pavement section is considered in overall good condition if all three conditions (IRI, crack- ing, faulting) are in good condition; a pavement section is considered in overall poor condition

Field Performance of Selected Projects 35   Figure 17. Example of automated pavement condition survey. (Source: Image courtesy of APTech.) 0 1048 36 234 262 172 0 300 600 900 1200 0 - 5 6 - 10 11 - 15 16 - 20 21 - 25 > 26 N o. o f S eg m en ts Age (years) Figure 18. Number of 0.10-mi segments evaluated, by age. if two or more of the conditions are in poor condition (Federal Register 2017). The identification of good, fair, and poor segments, in accordance with NHPP, is further illustrated in Figure 21. Performance results for all projects are summarized in Table 19. On average, the highest IRI and the most faulting, corner breaks, and transverse cracking occur with the 4- × 4-ft slabs. The 6- × 6-ft slabs, on average, have the lowest distress and IRI compared with 4- × 4-ft and 12- × 12-ft slabs. The highest level of distress with the 12- × 12-ft slabs was in longitudinal cracking. In accordance with the NHPP, on average, all of the BCOA projects evaluated were considered in good condition in relation to average transverse joint faulting and percentage of cracked slabs. On average, in relation to IRI, the 4- × 4-ft slabs were in poor condition, whereas the 6- × 6-ft and 12- × 12-ft slabs were in fair condition.

36 Evaluation of Bonded Concrete Overlays on Asphalt Pavements 714 722 316 0 300 600 900 1200 Low Moderate High N o. of Se gm en ts Traffic Volume Figure 19. Number of 0.10-mi segments evaluated, by trafc volume. IL CH27-10 (NB) 0% 5% 10% 15% 20% 25% 30% 0 50 100 150 200 250 300 350 0 5280 10560 15840 21120 % Sl ab s C ra ck ed IR I ( in /m i) Fa ul tin g (m ils ) Station (feet) Faulting IRI Cracking Ri ve rB rid ge Ri ve rB rid ge Ri ve rB rid ge O ve rp as sB rid ge CH 28/Mt Auburn Rd Pit Rd Pebble Springs Rd I-72 (under) Macon St Rd Old Rt 36/ W. HarristownBlvd Note: Cracking data point for each segment is shown at the end of the segment Recommended Poor Segment: NB 4,752 - 5,280 Recommended Good Segment: NB 12,144 - 12,672 Good Pavement focus areas Fair Pavement focus areas Poor Pavement focus areas Recommended Fair Segment: NB 20,064 - 20,592 Figure 20. Example of graph used to identify good, fair, and poor condition segments.

Field Performance of Selected Projects 37   Overall Condition Good Fair Poor IRI (in./mi) ≤95 95–170 ≥170 Transverse Cracking (% area) ≤5 5–15 ≥15 Faulting (in.) ≤0.10 0.10–0.15 ≥0.15 Table 18. NHPP pavement condition categories. (Source: Federal Register 2017.) Poor Good Fair Crack 5 IRI Fault Fair Fair 175 95 0.15 0.10 15 5 Good Good Good Good Good Poor Poor Figure 21. Selection of good, fair, and poor condition segments. IRI, faulting, corner breaks, and longitudinal, transverse, and total cracking for each project are summarized in Table 20. All projects had average faulting values at or below 0.10 in. or were in good condition based on the NHPP. In addition, all projects had less than 5% transverse- cracked slabs or were in good condition based on the NHPP. Of the nine 4- × 4-ft projects, six have IRI values in poor condition, one in fair condition, and two in good condition. For the 6- × 6-ft projects, 14 were in good condition and 12 had IRI in fair condition. All four of the 12- × 12-ft projects had IRI in fair condition.

38 Evaluation of Bonded Concrete Overlays on Asphalt Pavements The IL SR-53 northbound segments (4- × 4-ft slabs) had higher than average total cracking, faulting, and IRI; further investigation indicated that the BCOA layers were underdesigned for this project. The LA US-167 (4- × 4-ft slabs) had higher than average joint faulting and MO US-60 (4- × 4-ft slabs) had higher than average joint faulting and corner breaks. Three of the four 12- × 12-ft projects, both directions of CO US-6, and westbound for MN TH-30, had high levels of longitudinal cracking. Several projects had slabs with longitudinal cracking and corner breaks, which are not included as NHPP condition categories. Figures 22 through 27 further illustrate the occurrence of condition and distress for all 0.10-mi segments evaluated. Nearly half the 0.10-mi segments (815 segments, or 47%) indicated an IRI of 95 in./mi or less, 771 segments (or 44%) had an IRI between 95 and 170 in./mi, and 157 segments (or 9%) had an IRI 170 in./mi or greater. Nearly all 0.10-mi segments (1,722, or 99%) had faulting 0.10 in. or less, 20 segments (1%) had faulting between 0.10 and 0.15 in., and only one segment had faulting greater than 0.15 in. The majority of 0.10-mi segments had less than 5% of slabs with corner breaks, longitudinal cracking, and transverse cracking (1,699, 1,456, and 1,733 segments, or 97%, 84%, and 99% of segments, respectively), 185 segments (11%) had 5% to 10% cracked slabs, and 173 segments (10%) had more than 15% cracked slabs. Performance at BCOA intersection locations was compared with BCOA performance at non- intersection locations. For this analysis, signalized intersections were identified for each project. Intersections were divided into three segments: a 500-ft lead-in segment ending at the stop bar, a 500-ft lead-out segment beginning at the stop bar in the opposite direction, and the inter- section proper bounded by the two stop bars. The station location for each intersection seg- ment (start of lead-in, first stop bar, second stop bar, end of lead-out) was identified and used to filter the IRI, faulting, and cracked slab data within each intersection. Signalized intersection pavement conditions were evaluated to determine whether a unique performance difference is caused by stop-and-go conditions. Information obtained from 62 intersections from nine projects was used in the analysis. A summary of intersection results is shown in Table 21. IRI (in./mi) 4- x 4-ft 7 to 21 5 (9) 92 276 181 63 6- x 6-ft 7 to 21 13 (26) 70 157 104 26 12- x 12-ft 21 to 26 2 (4) 98 139 116 18 Faulting (in.) 4- x 4-ft 7 to 21 5 (9) 0.03 0.10 0.05 0.03 6- x 6-ft 7 to 21 13 (26) 0.02 0.06 0.03 0.01 12- x 12-ft 21 to 26 2 (4) 0.04 0.07 0.05 0.01 Corner breaks (% slabs) 4- x 4-ft 7 to 21 5 (9) 0.1 7.4 1.7 2.3 6- x 6-ft 7 to 21 13 (26) 0.0 0.8 0.1 0.2 12- x 12-ft 21 to 26 2 (4) 0.5 1.1 0.8 0.3 Longitudinal cracking (% slabs) 4- x 4-ft 7 to 21 5 (9) 0.1 3.8 1.0 1.1 6- x 6-ft 7 to 21 13 (26) 0.0 3.7 0.8 1.0 12- x 12-ft 21 to 26 2 (4) 5.6 30.7 15.5 10.7 Transverse cracking (% slabs) 4- x 4-ft 7 to 21 5 (9) 0.0 1.7 0.3 0.5 6- x 6-ft 7 to 21 13 (26) 0.0 1.2 0.2 0.3 12- x 12-ft 21 to 26 2 (4) 0.1 0.3 0.3 0.1 Total cracking (% slabs) 4- x 4-ft 7 to 21 5 (9) 0.2 12.8 3.0 3.9 6- x 6-ft 7 to 21 13 (26) 0.0 4.2 1.1 1.2 12- x 12-ft 21 to 26 2 (4) 7.0 31.5 16.6 10.5 a 5.5- x 5.5-ft and 6-ft x variable-length slab sizes are included in the 6- x 6-ft summary. b Excluding LA US-425, testing included both directions and each direction is quantified as a run. c See Table 18 for definitions of good, fair, and poor condition. Condition Slaba Age (years) No. of projects (no. of runs)b Min. Max. Avg.c SD Table 19. Summary of automated distress survey for all projects.

Project ID Slab Size Length (mi) Region Age (years) IRI (in./mi) Faulting (in.) Cracking (% of slabs) Min. Max. Avg. SD Min. Max. Avg. SD Corner Longitu- dinal Trans- verse Total CO I-70 EB 6- x 6-ft 4.5 W 7 73 146 92 16 0.02 0.06 0.03 0.01 0.0 0.0 0.0 0.0 CO I-70 WB 6- x 6-ft 4.5 W 7 85 144 102 12 0.02 0.03 0.02 0.00 0.0 0.0 0.0 0.0 CO SH-83A NB 6- x 6-ft 1.8 W 19 91 226 146 46 0.04 0.11 0.06 0.02 0.2 0.7 0.0 0.9 CO SH-83A SB 6- x 6-ft 1.8 W 19 71 239 135 41 0.03 0.11 0.06 0.02 0.3 0.3 0.1 0.7 CO SH-83B NB 6- x 6-ft 2.0 W 14 98 244 154 37 0.03 0.10 0.06 0.02 0.6 2.2 0.2 3.0 CO SH-83B SB 6- x 6-ft 2.0 W 14 98 191 146 23 0.03 0.08 0.06 0.01 0.8 2.4 0.1 3.2 CO SH-121A NB 6- x 6-ft 3.3 W 19 66 208 91 25 0.03 0.06 0.03 0.01 0.0 0.4 0.2 0.6 CO SH-121 A SB 6- x 6-ft 3.3 W 19 74 511 117 73 0.02 0.11 0.04 0.02 0.0 2.0 0.0 2.1 CO SH-121 B NB 6- x 6-ft 2.1 W 8 56 123 76 17 0.02 0.04 0.03 0.00 0.1 0.9 0.0 1.0 CO SH-121 B SB 6- x 6-ft 2.1 W 8 61 135 83 21 0.03 0.06 0.04 0.01 0.0 0.3 0.0 0.3 CO US-6 EB 12- x 12-ft 12.0 W 21 71 140 98 14 0.01 0.08 0.04 0.01 0.5 13.4 0.3 14.1 CO US-6 WB 12- x 12-ft 12.0 W 21 68 180 106 23 0.02 0.11 0.05 0.02 0.7 30.7 0.1 31.5 IA US-71 NB 6- x 6-ft 9.1 NC 7 66 139 85 13 0.02 0.05 0.02 0.00 0.1 0.8 0.1 1.0 IA US-71 SB 6- x 6-ft 9.1 NC 7 58 137 78 10 0.01 0.05 0.02 0.01 0.0 2.2 0.1 2.4 IL CH-10 EB 6- x 6-ft 8.5 NC 10 65 157 93 21 0.01 0.07 0.02 0.01 0.2 0.1 0.0 0.3 IL CH-10 WB 6- x 6-ft 8.5 NC 10 65 202 90 22 0.01 0.05 0.02 0.01 0.3 0.2 0.0 0.5 IL CH-27 NB 5.5- x 5.5-ft 4.1 NC 16 103 244 142 30 0.02 0.07 0.03 0.01 0.1 0.3 0.1 0.5 IL CH-27 SB 5.5- x 5.5-ft 4.1 NC 16 109 245 157 32 0.02 0.08 0.03 0.01 0.1 0.0 0.1 0.3 IL SR-53 NB 4- x 4-ft 4.4 NC 7 123 356 176 43 0.03 0.07 0.04 0.01 7.4 3.8 1.7 12.8 IL SR-53 SB 4- x 4-ft 4.4 NC 7 154 406 249 68 0.03 0.13 0.07 0.02 0.8 0.1 0.2 1.1 KS I-70 EB 6- x 6-ft 7.3 NC 8 79 132 109 10 0.02 0.05 0.02 0.01 0.0 0.0 0.0 0.1 KS I-70 WB 6- x 6-ft 7.4 NC 8 66 362 89 34 0.02 0.11 0.03 0.01 0.1 0.1 0.0 0.2 LA US-167 NB 4- x 4-ft 1.1 S 21 207 369 276 43 0.08 0.17 0.10 0.02 1.1 1.1 0.3 2.5 LA US-167 SB 4- x 4-ft 1.1 S 21 138 356 227 66 0.05 0.15 0.09 0.03 0.6 0.6 0.0 1.3 LA US-425 NB 4- x 4-ft 1.7 S 16 112 237 152 39 0.02 0.04 0.03 0.00 0.1 0.1 0.1 0.3 MN CSAH-7 NB 6- x 6-ft 2.5 NC 10 65 234 90 33 0.03 0.06 0.03 0.01 0.1 2.2 0.5 2.8 MN CSAH-7 SB 6- x 6-ft 2.5 NC 10 63 147 89 23 0.02 0.06 0.03 0.01 0.3 3.7 0.2 4.2 MN CSAH-22 EB 6- x 6-ft 3.2 NC 8 64 134 92 16 0.02 0.06 0.03 0.01 0.0 0.0 0.0 0.1 MN CSAH-22 WB 6- x 6-ft 3.3 NC 8 71 152 99 16 0.02 0.06 0.04 0.01 0.1 0.0 0.0 0.1 MN I-35 NB 6- x 6-ft 6.6 NC 10 59 98 70 7 0.02 0.05 0.03 0.00 0.1 0.1 0.9 1.1 MN I-35 SB 6- x 6-ft 6.6 NC 10 65 124 88 13 0.03 0.06 0.04 0.01 0.1 0.1 1.2 1.4 MN TH -30 EB 12- x 12-ft 8.6 NC 26 74 205 121 29 0.02 0.08 0.05 0.01 1.1 5.6 0.3 7.0 MN TH -30 WB 12- x 12-ft 8.6 NC 26 83 211 139 34 0.02 0.13 0.07 0.02 0.9 12.3 0.3 13.6 MO US-60 EB 4- x 4-ft 1.2 NC 20 149 232 186 33 0.02 0.08 0.04 0.02 1.7 1.3 0.1 3.2 MO US-60 WB 4- x 4-ft 1.2 NC 20 143 264 180 43 0.02 0.09 0.03 0.02 3.1 0.8 0.1 4.0 MT SR-16 NB 4- x 4-ft 0.5 W 18 77 103 92 11 0.02 0.03 0.03 0.00 0.3 1.0 0.1 1.3 MT SR-16 SB 4- x 4-ft 0.5 W 18 83 109 94 10 0.02 0.03 0.03 0.00 0.1 0.1 0.0 0.2 PA SR-119 NB 6- x 6-ft 4.1 NA 9 65 185 102 28 0.02 0.10 0.04 0.02 0.0 0.3 0.0 0.3 PA SR-119 SB 6- x 6-ft 4.1 NA 9 52 150 98 24 0.02 0.07 0.04 0.01 0.0 1.1 0.0 1.1 NOTE: See Table 18 for definitions of good, fair, and poor condition. EB = eastbound; NA = North Atlantic; NB = northbound; NC = North Central; S = Southern; SB = southbound; W = Western; WB = westbound. Table 20. Summary of automated condition survey.

815 771 157 0 400 800 1200 1600 2000 ≤ 95 95 - 170 ≥ 170 N o. o f S eg m en ts IRI (in/mi) Figure 22. Automated pavement condition survey results for IRI. 1722 20 1 0 400 800 1200 1600 2000 ≤ 0.10 0.10 - 0.15 ≥ 0.15 N o. o f S eg m en ts Faulting (inch) Figure 23. Automated pavement condition survey results for faulting. 1699 42 2 0 400 800 1200 1600 2000 ≤ 5 5-10 ≥ 15 N o. o f S eg m en ts Corner Breaks (%) Figure 24. Automated pavement condition survey results for corner breaks.

1385 185 173 0 400 800 1200 1600 2000 ≤ 5 5-10 ≥ 15 N o. o f S eg m en ts Total Cracking (%) Figure 27. Automated pavement condition survey results for total cracking. 1456 132 155 0 400 800 1200 1600 2000 ≤ 5 5-10 ≥ 15 N o. o f S eg m en ts Longitudinal Cracking (%) Figure 25. Automated pavement condition survey results for longitudinal cracking. 1733 10 0 0 400 800 1200 1600 2000 ≤ 5 5-10 ≥ 15 N o. o f S eg m en ts Transverse Cracking (%) Figure 26. Automated pavement condition survey results for transverse cracking.

42 Evaluation of Bonded Concrete Overlays on Asphalt Pavements Statistical analyses were used to determine the difference in performance between inter section and nonintersection locations. The performance parameters analyzed were IRI, faulting, and total cracking (corner, longitudinal, and transverse). Individual projects were analyzed first to identify any trends or differences within a given project. An analysis of variance (ANOVA) was performed to evaluate the statistical significance of all segments within a given project. In most cases, no statistically significant difference was found between intersections and nonintersection segments within a given project (Table 22). However, sample variances from intersection and nonintersection segments were not equal, which is one of the required assumptions when performing a one-factor ANOVA test. There- fore, two-tailed t-tests were conducted assuming different sample variances. The null hypothesis for the t-test assumes the means from both samples are the same. If the t-test results do not agree, the null hypothesis can be rejected (i.e., sample means are not the same). The results indicated NOTE: EB = eastbound; NB = northbound; SB = southbound; WB = westbound. a Values shown in parentheses represent the number of total project segments. b Values shown in parentheses represent average values for total project. Project ID Slab Size No. of Inter- sectionsa IRI (in./mi)b Faulting (in.)b Cracked Slabs (%)b Corner Longitu- dinal Trans- verse CO SH-83A NB 6- x 6-ft 3 (20) 205 (154) 0.07 (0.06) 3.1 (0.6) 2.4 (2.2) 0.8 (0.2) CO SH-83A SB 6- x 6-ft 3 (20) 168 (146) 0.05 (0.06) 0.0 (0.8) 4.8 (2.4) 0.0 (0.1) CO SH-83B NB 6- x 6-ft 2 (18) 129 (146) 0.05 (0.06) 0.0 (0.2) 0.0 (0.7) 0.0 (0.0) CO SH-83B SB 6- x 6-ft 2 (18) 179 (135) 0.05 (0.06) 1.3 (0.3) 1.3 (0.3) 0.0 (0.1) CO SH-121A NB 6- x 6-ft 6 (21) 116 (76) 0.04 (0.03) 1.5 (0.1) 0.4 (0.9) 0.0 (0.0) CO SH-121A SB 6- x 6-ft 6 (21) 153 (83) 0.05 (0.04) 0.0 (0.0) 0.0 (0.3) 0.0 (0.0) CO SH-121B NB 6- x 6-ft 5 (33) 114 (91) 0.04 (0.03) 0.0 (0.0) 0.0 (0.4) 0.0 (0.2) CO SH-121B SB 6- x 6-ft 5 (33) 116 (117) 0.05 (0.04) 0.0 (0.0) 2.5 (2.0) 0.0 (0.0) CO US-6 EB 12- x 12-ft 2 (120) 84 (98) 0.02 (0.04) 0.0 (0.5) 0.0 (13.4) 0.0 (0.3) CO US-6 WB 12- x 12-ft 2 (120) 119 (106) 0.04 (0.05) 0.0 (0.7) 0.0 (30.7) 0.0 (0.1) IL SR-53 NB 4- x 4-ft 1 (44) 200 (249) 0.05 (0.07) 5.7 (7.9) 1.0 (3.8) 1.9 (1.7) IL SR-53 SB 4- x 4-ft 1 (44) 169 (176) 0.04 (0.04) 0.0 (0.8) 0.0 (0.1) 0.0 (0.2) LA US-167 NB 4- x 4-ft 3 (11) 345 (276) 0.12 (0.10) 1.9 (1.1) 1.4 (1.1) 0.0 (0.3) LA US-167 SB 4- x 4-ft 3 (11) 353 (227) 0.11 (0.09) 1.9 (0.6) 3.1 (0.6) 0.0 (0.0) MO US-60 EB 4- x 4-ft 2 (7) 123 (186) 0.04 (0.04) 0.7 (1.7) 2.2 (1.3) 0.0 (0.1) MO US-60 WB 4- x 4-ft 2 (12) 139 (180) 0.03 (0.03) 2.4 (3.1) 0.0 (0.8) 0.0 (0.1) PA SR-119 NB 6- x 6-ft 7 (41) 132 (102) 0.05 (0.04) 0.0 (0.0) 1.2 (0.3) 0.0 (0.0) PA SR-119 SB 6- x 6-ft 7 (41) 114 (98) 0.05 (0.04) 0.0 (0.0) 8.9 (1.1) 0.0 (0.0) Table 21. Summary of automated condition survey at intersections. Project ID IRI (in./mi) Faulting (in.) Cracked Slabs (%) CO SH-83A NB Not significant Not significant Not significant CO SH-83A SB Not significant Not significant Not significant CO SH-83B NB Not significant Not significant Not significant CO SH-83B SB Not significant Not significant Not significant CO SH-121A NB Significant Significant Not significant CO SH-121A SB Significant Significant Not significant CO SH-121B NB Not significant Not significant Not significant CO SH-121B SB Not significant Not significant Not significant CO US-6 EB Not significant Significant Not significant CO US-6 WB Not significant Not significant Not significant LA US-167 NB Not significant Not significant Not significant LA US-167 SB Not significant Not significant Not significant MO US-60 EB Significant Not significant Not significant MO US-60 WB Not significant Not significant Not significant PA SR-119 NB Significant Not significant Not significant PA SR-119 SB Not significant Not significant Significant NOTE: EB = eastbound; NB = northbound; SB = southbound; WB = westbound. Table 22. ANOVA of automated condition survey.

Field Performance of Selected Projects 43   that about 38% of the projects showed a statistical difference in pavement performance between intersections and nonintersections for a given project (Table 23). Because the number of 0.10-mi segments at each intersection included only two to five samples, compared with 30 to 100 segments over the project length, the sample size effect could be large. Cohen’s d statistic was used to evaluate the data set. The results showed that in 40% of the cases the sample size effect is high to very high, indicating a meaningful statistical conclusion would be based on individual projects (Table 24). To overcome this issue, the analysis used segments from the entire data set (i.e., combining data from all BCOA projects). From this analysis, the results showed a significant difference between intersection and nonintersection segments. Table 25 includes a summary of results Project ID IRI (in./mi) Faulting (in.) Cracked Slabs (%) CO SH-83A NB Equal Equal Equal CO SH-83A SB Not equal Equal Equal CO SH-83B NB Equal Equal Not equal CO SH-83B SB Not equal Equal Equal CO SH-121A NB Not equal Not equal Equal CO SH-121A SB Not equal Not equal Not equal CO SH-121B NB Not equal Equal Not equal CO SH-121B SB Equal Equal Equal CO US-6 EB Equal Equal Not equal CO US-6 WB Equal Equal Not equal LA US-167 NB Equal Equal Equal LA US-167 SB Equal Equal Equal MO US-60 EB Not equal Equal Equal MO US-60 WB Equal Equal Equal PA SR-119 NB Not equal Equal Equal PA SR-119 SB Equal Not equal Equal NOTE: “Equal” indicates the null hypothesis can be accepted, that is, the means of the two data sets are equal. “Not equal” indicates the null hypothesis can be rejected, that is, the means of the two data sets are not equal. EB = eastbound; NB = northbound; SB = southbound; WB = westbound. Table 23. Automated condition survey: t-test with unequal variance. Project ID IRI (in./mi) Faulting (in.) Cracked Slabs (%) CO SH-83A NB 1.0 0.1 1.1 CO SH-83A SB 1.3 0.3 0.3 CO SH-83B NB 0.5 0.6 1.4 CO SH-83B SB 1.5 0.5 0.7 CO SH-121A NB 2.0 2.1 0.4 CO SH-121A SB 1.7 1.3 0.9 CO SH-121B NB 1.1 0.4 0.5 CO SH-121B SB 0.0 0.7 0.1 CO US-6 EB 1.0 1.8 1.1 CO US-6 WB 0.3 0.5 1.8 LA US-167 NB 0.5 0.2 0.5 LA US-167 SB 0.8 0.7 0.6 MO US-60 EB 2.4 0.2 0.1 MO US-60 WB 1.1 0.6 0.5 PA SR-119 NB 1.3 0.7 0.5 PA SR-119 SB 0.6 0.9 0.8 NOTE: 0.01–0.1 = very small effect; 0.2–0.4 = small effect; 0.5–0.7 = medium effect; 0.8–1.2 = large effect; and > 1.2 = very large effect. EB = eastbound; NB = northbound; SB = southbound; WB = westbound. Table 24. Effect of sample size in automated condition survey.

44 Evaluation of Bonded Concrete Overlays on Asphalt Pavements from the statistical analysis. In general, the eect on sample size when using the entire data set has a low to medium eect, meaning the results from ANOVA and t-test can be accepted. Figures 28 through 30 show IRI, faulting, and cracking for all BCOA segments, along with the average for intersection and nonintersection segments. e results indicate intersection IRI and faulting are 36% and 17% higher than nonintersection segments, respectively. e average total cracking at intersections was about 3% compared with 11% at nonintersection segments. However, three projects, CO US-6-10, CO US-6-20, and IL SR-53-10, have a high slab-cracking percentage on nonintersection segments compared with intersection segments. If these three projects are considered outliers and removed from the analysis, average percentage of cracked slabs at intersections is 3%, compared with 1% for the nonintersection segments. Ground-Penetrating Radar Surveys GPR surveys were conducted on the same sections as the automated distress surveys between August and October 2018. GPR testing included all projects in both directions in the outside travel lane (i.e., the truck lane). GPR data were collected in both wheelpaths using a 1-GHz horn antenna system at a nominal rate of four scans per foot of travel on each BCOA project. All Locations IRI(in./mi) Faulting (in.) Cracked Slabs (%) ANOVA Significant Significant Significant t-test Reject Reject Reject d statistic 0.6 0.3 0.6 Table 25. Automated condition survey: statistical summary. NOTE: Error bars indicate ±1 standard deviation. EB = eastbound; NB = northbound; SB = southbound; WB = westbound. 0 100 200 300 400 500 600 CO SH -1 21 B N B CO SH -1 21 B SB CO SH -1 21 A N B CO SH -1 21 A SB CO SH -8 3A N B CO SH -8 3A S B CO SH -8 3B N B CO SH -8 3B SB CO U S- 6 EB CO U S- 6 W B IL S R- 53 N B IL S R- 53 SB LA U S- 16 7 N B LA U S- 16 7 SB M O U S- 60 E B M O U S- 60 W B PA S R- 11 9 N B PA S R- 11 9 SB Av er ag e Project ID All IR I( in /m i) Intersection Non-Intersection Figure 28. IRI for intersection and nonintersection segments.

Field Performance of Selected Projects 45   0 20 40 60 80 100 CO SH -1 21 B N B CO SH -1 21 B SB CO SH -1 21 A N B CO SH -1 21 A SB CO SH -8 3A N B CO SH -8 3A S B CO SH -8 3B N B CO SH -8 3B SB CO U S 6 EB CO U S 6 W B IL S R 53 N B IL S R 53 S B LA U S 16 7 N B LA U S 16 7 SB M O U S 60 E B M O U S 60 W B PA S R 11 9 N B PA S R 11 9 SB Av er ag e Project ID All To ta lC ra ck in g (% ) Intersection Non-Intersection NOTE: Error bars indicate ±1 standard deviation. EB = eastbound; NB = northbound; SB = southbound; WB = westbound. Figure 30. Total cracked slabs in intersection and nonintersection segments. NOTE: Error bars indicate ±1 standard deviation. EB = eastbound; NB = northbound; SB = southbound; WB = westbound. 0.00 0.05 0.10 0.15 0.20 0.25 CO SH -1 21 B N B CO SH -1 21 B SB CO SH -1 21 A N B CO SH -1 21 A SB CO SH -8 3A N B CO SH -8 3A S B CO SH -8 3B N B CO SH -8 3B SB CO U S 6 EB CO U S 6 W B IL S R 53 N B IL S R 53 S B LA U S 16 7 N B LA U S 16 7 SB M O U S 60 E B M O U S 60 W B PA S R 11 9 N B PA S R 11 9 SB Av er ag e Project ID All Fa ul tin g (in ch ) Intersection Non-Intersection Figure 29. Faulting in intersection and nonintersection segments.

46 Evaluation of Bonded Concrete Overlays on Asphalt Pavements A vehicle equipped with an electronic distance-measuring instrument mounted to the rear wheel provided synchronous distance data for GPR testing locations (Figure 31). e GPS unit pro- vided high-resolution, dierentially corrected geospatial information. GPR data were collected in both directions on each project from within the survey vehicle; however, the analysis only included the 0.10-mi good, fair, and poor segments. ickness was determined in accordance with ASTM D4748. GPR operates by transmitting short pulses of electromagnetic energy into the pavement using an antenna attached to a survey vehicle. ese pulses are reected to the antenna with an arrival time and amplitude related to the location and nature of dielectric discontinuities in the material (e.g., concrete, asphalt, reinforcing steel). e reected energy is captured and may be displayed on an oscilloscope to form a series of pulses referred to as the radar waveform. e waveform contains a record of the properties and thicknesses of the layers within the pavement (Figure 32). e sequence of scans shown in Figure 32 is frequently coded in color or gray scale to produce the B-scan representation. e B-scan provides the equivalent of a cross-sectional view of the pavement, with the individual pavement layers showing as colored horizontal bands. Layer thickness is calculated from the arrival time of the reection from the top and bottom of each layer as follows (Roddis, Maser, and Gisi 1992): ( ) = ε . 5.9 (2) a Thickness in t Figure 31. GPR survey vehicle. Figure 32. Structure of the GPR signal for pavements. Concrete Asphalt Concrete Bottom Reflection

Field Performance of Selected Projects 47   where t = time (nanoseconds), and εa = relative dielectric permittivity or “dielectric constant” of the pavement layer. The dielectric constant of the surface pavement layer can be computed by measuring the ratio of the radar reflection from the pavement surface to the radar amplitude incident on the pave- ment. The incident amplitude on the pavement is determined by measuring the reflection from a metal plate on the pavement surface, as the metal plate reflects 100% of the incident energy. Using these data, the concrete surface dielectric constant, εc, can be obtained as follows (Roddis, Maser, and Gisi 1992): ( ) ( )ε = + −         (3)c pl pl 2 A A A A where A = amplitude of reflection from pavement surface, and Apl = amplitude of reflection from metal plate. Table 26 shows typical dielectric constants and associated GPR velocities for pavement materials. The range of dielectric constant for concrete is large because density, moisture, and aggregate composition vary. Similar calculations can be made for the dielectric constant of the asphalt base material and for granular subbase material. These calculations are automated in a proprietary data analysis software program that computes pavement layer thickness and changes in pave- ment layer properties. The GPR data, when displayed in a grayscale B-scan, show the pavement cross section, as in Figure 33. A sample of the analyzed data with the bottom of the concrete and asphalt layer reflec- tions “traced” by the GPR analyst is shown in Figure 34. The white and black bands indicate stronger reflections and occur when the dielectric contrast is high. The gray regions indicate weaker reflections and occur when there is little dielectric contrast. The software uses the GPR analyst–traced data to calculate layer thickness. Table 27 provides the GPR-determined thicknesses of the BCOA and asphalt layer for each good, fair, and poor segment, and all segments combined. Reported GPR values represent the average of individual readings calculated over a ≥1-ft interval. Core and GPR-determined layer thicknesses were compared to assess the accuracy of the GPR measurement. Eight cores were obtained from most of the projects with known geospatial locations. Only the GPR-determined layer thicknesses closest to the core locations were used in the comparison analysis. In general, the BCOA layer thickness measurements between the two methods agreed, showing an average difference of only 2.5% (Figure 35). However, the average percentage difference in thickness for the asphalt layer was 39.6% (Figure 36). It is important to note that asphalt layer thicknesses measured from cores at KS I-70 ranged from 18 to 27 in. Velocity (in./nanosecond) 3.5 3.94 4.1 4.3 4.5 4.7 4.9 5.1 5.3 5.5 5.7 5.9 6.1 Dielectric constant 11.0 9.0 8.2 7.4 6.8 6.3 5.8 5.3 4.9 4.6 4.3 4.0 3.8 Typical range for concrete pavements Typical range for asphalt pavements Table 26. GPR velocities and dielectric constants for pavement materials.

NOTE: EB = eastbound; NB = northbound; SB = southbound; WB = westbound. a As reported by agency; NA = not available, that is, thickness is unknown. b Values shown in parentheses represent standard deviation. c NA = not available, that is, the underlying asphalt layer was not visible or detectable by GPR testing. d Northbound segments were evaluated as good segments and southbound as fair and poor segments. Project ID BCOA Design (in.) Asphalt Layer (in.)a Slab Size BCOA (in.)b Asphalt Layer (in.)b, c Good Fair Poor All Good Fair Poor All CO I-70 WB 6.0 8 6- x 6-ft 6.5 (0.2) 6.4 (0.4) 6.4 (0.3) 6.5 (0.3) 14.3 (1.3) 12.1 (1.0) 12.0 (1.1) 12.8 (1.6) CO SH-83Ad 5.0 6 6- x 6-ft 6.5 (0.8) 7.8 (1.0) 8.5 (1.3) 7.6 (1.4) 8.8 (1.0) 8.1 (1.2) 8.0 (1.3) 8.3 (1.2) CO SH-83B SB 6.0 7 6- x 6-ft 6.2 (0.4) 6.1 (0.4) 6.1 (0.5) 6.1 (0.5) 6.3 (0.5) 5.3 (0.7) 7.2 (1.4) 6.4 (1.3) CO SH-121A NB 6.0 5.5 6- x 6-ft 6.0 (0.3) 6.0 (0.4) 6.1 (0.4) 6.0 (0.4) NA NA NA NA CO SH-121B NB 6.0 6 6- x 6-ft 6.3 (0.7) 6.3 (0.4) 6.3 (0.4) 6.3 (0.5) NA NA NA NA CO US-6 EB 5.5 6 12- x 12-ft 5.7 (0.3) 5.4 (0.3) 5.4 (0.3) 5.5 (0.3) 8.0 (0.9) 11.8 (1.3) 14.2 (0.8) 10.8 (2.7) IA US-71 NB 6.0 6 6- x 6-ft 6.8 (0.2) 6.5 (0.4) 6.6 (0.3) 6.6 (0.4) 10.4 (0.5) 3.8 (0.6) 10.0 (1.0) 8.1 (3.1) IL CH-27 NB 5.25 10 5.5- x 5.5-ft 5.3 (0.2) 5.4 (0.1) 5.4 (0.2) 5.4 (0.2) 5.3 (0.8) 5.1 (1.0) 5.5 (1.1) 5.4 (1.0) IL SR-53 NB 4.0 6 4- x 4-ft 3.5 (0.3) 4.0 (0.8) 4.4 (0.9) 3.7 (0.7) 6.0 (0.5) 3.6 (0.8) 4.0 (1.1) 4.8 (1.3) KS I-70 WB 6.0 17.75 6- x 6-ft 6.2 (0.4) 6.0 (0.4) 6.8 (0.2) 6.3 (0.5) 6.2 (0.6) 4.6 (1.4) 5.8 (0.4) 5.6 (1.1) LA US-167 NB 4.0 6 4- x 4-ft 5.3 (0.7) 5.7 (0.6) 5.1 (0.4) 5.4 (0.7) 9.0 (3.6) 7.4 (0.9) 7.8 (0.8) 8.0 (2.1) LA US-425 NB 4.0 NA 4- x 4-ft 4.6 (0.4) 4.4 (0.6) 4.1 (0.3) 4.4 (0.5) 11.1 (0.9) 12.2 (1.1) 6.1 (0.6) 9.8 (2.8) MN CSAH-7 NB 5.0 4 to 8 6- x 6-ft 5.8 (0.7) 5.1 (0.5) 4.8 (0.3) 5.2 (0.7) 7.9 (1.2) 9.1 (1.0) 6.4 (1.4) 7.8 (1.6) MN CSAH-22 EB 6.0 3 6- x 6-ft 5.7 (0.6) 6.0 (0.3) 6.6 (0.8) 6.2 (0.7) 3.5 (0.7) 4.2 (0.8) 6.2 (1.9) 4.8 (1.7) MN I-35 SB 6.0 12.5 6- x 6-ft 6.4 (0.5) 6.2 (0.3) 6.5 (0.4) 6.5 (0.5) NA NA NA NA MN TH-30 WB 6.0 4.25 12- x 12-ft 6.4 (0.3) 6.3 (0.3) 6.1 (0.3) 6.2 (0.3) 7.7 (0.9) 8.3 (1.0) 7.9 (1.0) 7.9 (1.0) MO US-60 WB 4.0 6 4- x 4-ft 4.7 (0.3) 5.8 (0.4) 4.5 (0.3) 5.0 (0.7) 4.5 (0.5) 4.7 (0.7) 5.2 (0.4) 4.8 (0.6) MT SR-16 NB 4.0-9.0 6 4- x 4-ft 4.4 (0.3) 4.5 (0.5) 4.2 (0.4) 4.4 (0.4) NA NA NA NA PA SR-119 SB 6.0 7.5 to 10 6- x 6-ft 6.6 (0.5) 6.3 (0.5) 7.1 (0.4) 6.6 (0.6) 5.9 (1.5) 6.2 (2.0) 3.7 (1.4) 5.0 (2.0) Table 27. GPR-determined average BCOA layer thickness. Figure 33. Example B-scan of concrete and asphalt layers. (Source: Infrasense.) Figure 34. Example B-scan showing concrete and asphalt layers “traced” by analyst.

Field Performance of Selected Projects 49   Core GPR NOTE: Error bars indicate ±1 standard deviation. 0 5 10 15 20 25 30 CO I- 70 CO S H- 83 A CO S H- 83 B CO U S- 6 IA U S- 71 IL C H- 27 IL S R- 53 KS I- 70 LA U S- 16 7 LA U S- 42 5 M N C SA H- 22 M N C SA H- 7 M N T H- 30 M O U S- 60 As ph al t L ay er T hi ck ne ss (i nc h) Project ID Figure 36. Core versus GPR measurements of asphalt layer thickness. 0 2 4 6 8 10 12 CO I- 70 CO S H- 12 1A CO S H- 12 1B CO S H- 83 A CO S H- 83 B CO U S- 6 IA U S- 71 IL C H- 27 IL S R- 53 KS I- 70 LA U S- 16 7 LA U S- 42 5 M N C SA H- 22 M N C SA H- 7 M N I- 35 M N T H- 30 M O U S- 60 M T SR -1 6 PA S R- 11 9 BC O A La ye r T hi ck ne ss (i nc h) Project ID Core GPR NOTE: Error bars indicate ±1 standard deviation. Figure 35. Core versus GPR measurements of BCOA layer thickness.

50 Evaluation of Bonded Concrete Overlays on Asphalt Pavements and were significantly thicker than those from the GPR measurement, which ranged from 6 to 7 in. Core measurements of asphalt layer thickness on several projects, namely IL SR-53, KS I-70, and LA US-167, also varied significantly, with a difference between minimum and maximum thickness greater than 7 in. GPR-measured asphalt thicknesses were more uniform, however. Finally, a large difference was found on CO US-6, where the GPR measurements were slightly more than twice the core measurement. A two-tailed t-test was performed to determine whether a significant difference in BCOA and asphalt layer thicknesses exists between core and GPR measurements. The null hypothesis for the t-test assumes the means from both samples are the same. About 84% of the cases showed no statistical significance between the two methods when determining the BCOA layer thick- ness. For the asphalt layer thickness, 58% of the cases showed no significant difference between the two methods. The results from the t-test are shown in Table 28. Detailed On-Site Evaluations The detailed project site evaluations were conducted on each BCOA project during an 8-hour lane closure (or as allowed by agency lane-closure restrictions). Site evaluations at three 0.10-mi segments on each of the 19 projects (total of approximately 24 mi) included visual distress surveys, ultrasonic tomography testing, FWD testing, faultmeter testing, coring, DCP testing, and unbound material sampling. Results of the detailed site evaluations for each project are provided in Appendix C. Visual Distress Surveys and Faultmeter Testing Detailed visual distress surveys included the use of FHWA-accredited pavement raters in accordance with the Distress Identification Manual for the Long-Term Pavement Performance Program (Miller and Bellinger 2014). Visual distress surveys were conducted on each good, fair, and poor segment of each BCOA project (Figure 37). Condition assessments were used NOTE: NA = not available, that is, layer not detected by GPR or core not obtained. Project ID BCOAa Asphalta CO I-70 Equal Equal CO SH-83A Equal Equal CO SH-83B Equal Equal CO SH-121A Equal NA CO SH-121B Equal NA CO US-6 Not equal Not equal IA US-71 Equal Equal IL CH-27 Equal Not equal IL SR-53 Not equal Not equal KS I-70 Equal Not equal LA US-167 Equal Not equal LA US-425 Equal Equal MN CSAH-7 Equal Equal MN CSAH-22 Equal Equal MN I-35 Equal NA MN TH-30 Not equal Not equal MO US-60 Equal Equal MT SR-16 Equal NA PA SR-119 Equal NA a “Equal” indicates null hypothesis accepted, data set means are equal; “not equal” indicates null hypothesis is rejected, data set means are not equal. Table 28. Comparison of BCOA and asphalt layer thickness, t-test results.

Field Performance of Selected Projects 51   to determine current conditions (e.g., cracking, spalling, corner breaks), as well as to identify other common distress types specific to BCOAs, including slab migration. Surface distress was tabulated and summed over each 0.10-mi segment. Visual distress surveys were conducted on all 19 projects (57 good, fair, and poor segments). Visual distress survey results for each project are provided in Appendix F. As shown in Table 29 (and further illustrated in Figure 38), the predominant type of distress on all projects regardless of feature (e.g., slab thickness, slab size, joint sealing) was concrete patching (predominantly 12- × 12-ft slabs on MN TH-30), joint seal damage (predominantly on Colorado projects), map cracking (predominantly on Colorado projects), and longitudinal cracking (predominantly 12- × 12-ft slabs on CO US-6). When comparing cracking distress (excluding map cracking), the 4- × 4-ft slabs had 15% transverse cracking, 7% longitudinal cracking, and 4% corner breaks and the 6- × 6-ft slabs had 2% transverse cracking, 4% longitudinal cracking, and no corner breaks. Figure 37. Visual distress survey. (Source: NCE.) Distress Type 4- x 4-ft 6- x 6-ft a 12- x 12-ft Total %b Total Total Corner breaks (no. joints) 71 4 6 0 0 0 Longitudinal cracking, unsealed (ft) 544 7 653 4 544 17 Longitudinal cracking, sealed (ft) 0 0 0 0 213 6 Transverse cracking, unsealed (no.) 277c 15 52 2 26 10 Transverse cracking, sealed (no.) 0 0 0 0 7 3 Longitudinal joint seal damage (ft) 0 0 11,779 10 349 8 Transverse joint seal damage (ft) 0 0 3,532 64 278 11 Longitudinal joint spalling (ft) 276 4 160 1 32 1 Transverse joint spalling (ft) 56 0 65 0 341 10 Map cracking (ft2) 7,438 8 44,483d 20 5 0 Scaling (ft2) 3 0 2,138e 1 0 0 Polished aggregate (ft2) 5 0 18,770f 8 0 0 Asphalt patch (ft2) 2,124 2 0 0 0 0 Concrete patch (ft2) 1,749 2 542 0 3,004g 91 Total slabs (no.) 5,558 6,180 274 a Includes 5.5- x 5.5-ft and 6- x 6-ft variable slabs. b % of projects. c Approximately 75% occurs on IL SR-53. d Approximately 95% occurs on CO I-70, CO SH-83A, and CO SH-83B. e Predominantly occurs on CO SH-121B. f Predominantly occurs on CO SH-83A and CO SH-121-B. g Predominantly on MN TH-30. %b %b Table 29. Summary of visual distress survey.

52 Evaluation of Bonded Concrete Overlays on Asphalt Pavements Each good, fair, and poor segment was tested with a faultmeter (Figure 39). Faultmeter tests were conducted at the FWD joint locations and in accordance with the Distress Identification Manual for the Long-Term Pavement Performance Program (Miller and Bellinger 2014). Faultmeter measurements on all project sites were low, ranging from −0.7 to 0.30 in., with an average of 0.04 in. and a standard deviation of 0.04 in. (Table 30). A summary of faultmeter test results by slab size is illustrated in Figure 40. The majority (95%) of measurements on the 4- × 4-ft slabs had less than 0.12 in. of faulting, all of the measurements 2% 4% 4% 15% 8% 7% 2% 1% 8% 1% 2% 20% 4% 73% 11% 12% 23% 19% 91% 0% 20% 40% 60% 80% 100% Scaling Asphalt Patching Corner Breaks Polished Aggregate Joint Spalling Transverse Cracking Map Cracking Longitudinal Cracking Joint Seal Damage Concrete Patching % of total measure (area, ft, joints) 4- x 4-ft 6- x 6-ft 12- x 12-ft Figure 38. Visual distress by slab size. Figure 39. Faultmeter. (Source: NCE.)

Field Performance of Selected Projects 53   MN TH-30 26 12- x 12-ft Good 45 0.00 0.03 0.02 0.01 Fair 34 −0.07 0.30 0.07 0.07 Poor 49 0.06 0.24 0.13 0.05 MO US-60 20 4- x 4-ft Good 15 0.00 0.12 0.02 0.03 Fair 15 0.00 0.04 0.01 0.02 Poor 15 0.00 0.04 0.00 0.01 MT SR-16 18 4- x 4-ft Good NA a Fair NA a Poor NA a PA SR-119 9 6- x 6-ft Good NA b Fair NA b Poor NA b NOTE: NA = not available. a Testing not conducted because of traffic control restrictions. b Testing not conducted because of equipment failure. Project ID 2019 Age (years) Slab Size Segment Faulting (in.) No. Min. Max. Avg. SD CO I-70 7 6- x 6-ft Good NA a Fair NA a Poor NA a CO SH-83A 19 6- x 6-ft Good 15 0.00 0.08 0.03 0.03 Fair 15 −0.04 0.04 0.01 0.02 Poor 15 −0.04 0.08 0.03 0.04 CO SH-83B 14 6- x 6-ft Good 15 0.00 0.08 0.02 0.03 Fair 15 0.00 0.08 0.04 0.03 Poor 15 0.00 0.16 0.06 0.04 CO SH-121A 19 6- x 6-ft Good 15 0.00 0.04 0.01 0.02 Fair 15 0.00 0.04 0.01 0.02 Poor 15 0.00 0.08 0.04 0.02 CO SH-121B 8 6- x 6-ft Good 15 0.00 0.08 0.03 0.02 Fair 15 0.00 0.04 0.02 0.02 Poor 15 0.00 0.04 0.01 0.02 CO US-6 21 12- x 12-ft Good 15 0.00 0.04 0.01 0.02 Fair 15 −0.04 0.04 0.00 0.01 Poor 15 0.00 0.04 0.01 0.02 IA US-71 7 6- x 6-ft Good NA b Fair NA b Poor NA b IL CH-27 16 5.5- x 5.5-ft Good 15 0.00 0.08 0.03 0.02 Fair 15 0.00 0.04 0.03 0.01 Poor 10 0.00 0.04 0.02 0.02 IL SR-53 7 4- x 4-ft Good 15 0.00 0.16 0.06 0.05 Fair 15 0.00 0.28 0.08 0.08 Poor 11 0.00 0.16 0.09 0.05 KS I-70 8 6- x 6-ft Good NA b Fair NA b Poor NA b LA US-167 21 4- x 4-ft Good 15 0.00 0.04 0.01 0.02 Fair 15 0.00 0.24 0.06 0.05 Poor 15 0.00 0.08 0.04 0.03 LA US-425 16 4- x 4-ft Good NA a Fair NA a Poor 15 0.00 0.08 0.02 0.03 MN CSAH-7 10 6- x 6-ft Good 49 −0.02 0.09 0.03 0.03 Fair 49 −0.01 0.10 0.03 0.02 Poor 49 −0.01 0.11 0.04 0.03 MN CSAH-22 8 6- x 6-ft Good 49 −0.06 0.09 0.02 0.03 Fair NA a Poor 49 −0.05 0.11 0.03 0.03 MN I-35 10 6- x 6-ft Good 49 −0.02 0.06 0.02 0.02 Fair NA a Poor 49 0.00 0.11 0.04 0.03 Table 30. Summary of average faultmeter results.

54 Evaluation of Bonded Concrete Overlays on Asphalt Pavements on the 6- × 6-ft slabs had faulting less than 0.20 in., and most of the measurements (80%) on the 12- × 12-ft slabs had faulting less than 0.12 in. For the 4- × 4-ft slabs, 58 measurements (41%) indicated no faulting, 76 measurements (54%) had faulting between 0 and 0.12 in., six measure- ments (5%) had faulting between 0.16 and 0.24 in., and one measurement had faulting greater than 0.24 in. For the 6- × 6-ft slabs, 89 measurements (17%) had no faulting and 423 measure- ments (83%) had faulting between 0 and 0.12 in. The 12- × 12-ft slabs had the largest range of faulting, with 113 measurements (80%) less than 0.12  in., 57 measurements (20%) between 0.12 in. and 0.24 in., and three measurements (2%) greater than 0.24 in. Figures 41 through 45 illustrate IRI, cracking, and faulting results from the automated dis- tress survey and detailed site evaluations in relation to in-service BCOA age (ranging from 7 to 26 years). The NHPP good, fair, and poor criteria (see Table 18) have been added to each figure to further illustrate BCOA performance. The majority of 4- × 4-ft segments (7 of 9 segments) had IRI values greater than 170 in./mi (poor condition), all 6- × 6-ft segments had IRI values less than 170 in./mi (14 segments below 95 in./mi, good condition, and 12 segments between 95 in./mi and 170 in./mi, fair condition), and all four 12- × 12-ft segments had IRI between 95 in./mi and 170 in./mi (fair condition) (Fig- ure 41). In addition, most of the 4- × 4-ft segments had IRI values in poor condition after 20 years. Based on the results of the automated distress survey, all segments, except one 4- × 4-ft segment and all four 12- × 12-ft segments, had less than 5% cracked slabs (good condition) (Figure 42). Faulting, measured as part of the automated distress survey, indicated all but one 4- × 4-ft segment had faulting less than 0.10 in. (good condition) (Figure 43). The visual distress survey indicated slightly different results from the automated distress survey: 41 segments (73%) had less than 5% cracked slabs (good condition), 12 segments (21%) had 5% to 15% cracked slabs (fair condition), and three segments (5%) had more than 15% cracked slabs (poor condition, not shown) (Figure 44). The visual distress survey showed results similar to the faultmeter, except all but one 12- × 12-ft segment had measurements less than 0.10 in. (good condition) (Figure 45). 58 54 15 7 5 89 301 105 17 1 35 56 22 23 20 11 3 2 1 0 50 100 150 200 250 300 350 400 450 0.00 0.04 0.08 0.12 0.16 0.20 0.24 0.28 0.31 N o. o f S eg m en ts Faulting (inch) 4x4 6x6 12x12 Figure 40. Average faulting by slab size.

Field Performance of Selected Projects 55   0 50 100 150 200 250 300 0 5 10 15 20 25 30 IR I ( in /m i) In-Service Age (years) 4x4 6x6 12x12 Poor Good Fair Figure 41. Automated distress survey, IRI. 0 10 20 30 40 0 5 10 15 20 25 30 To ta l C ra ck in g (% sl ab s) In-Service Age (years) 4x4 6x6 12x12 Poor Fair Good Figure 42. Automated distress survey, cracked slabs.

56 Evaluation of Bonded Concrete Overlays on Asphalt Pavements 0.00 0.05 0.10 0.15 0.20 0 5 10 15 20 25 30 Fa ul tin g (in ch ) In-Service Age (years) 4x4 6x6 12x12 Poor Fair Good Figure 43. Automated distress survey, faulting. 0 5 10 15 20 0 5 10 15 20 25 30 To ta l C ra ck in g (% sl ab s) In-Service Age (years) 4x4 6x6 12x12 Fair Poor Good Figure 44. Visual distress survey, cracked slabs.

Field Performance of Selected Projects 57   Statistical Analysis of Automated and Visual Distress Surveys and Faultmeter Testing A statistical analysis was conducted to compare the results of the automated pavement con- dition surveys and the visual distress surveys. Automated condition survey results for the 0.10-mi good, fair, and poor locations were extracted for direct comparison with the visual dis- tress survey results for faulting, corner breaks, longitudinal cracking, transverse cracking, and total cracking (Figures 46 through 50). 0.00 0.05 0.10 0.15 0.20 0 5 10 15 20 25 30 Fa ul tm et er (i nc h) In-Service Age (years) 4x4 6x6 12x12 Fair Poor Good Figure 45. Visual distress survey, faulting. R² = 0.3562 0.00 0.03 0.06 0.09 0.12 0.15 0.00 0.03 0.06 0.09 0.12 0.15 Au to m at ed C on di tio n Su rv ey (i nc h) Faultmeter (inch) Figure 46. Automated condition survey versus visual distress survey, faulting.

R² = 0.5952 0% 10% 20% 30% 40% 50% 0% 10% 20% 30% 40% 50% Au to m at ed C on di tio n Su rv ey (% sl ab s) Visual Distress Survey (% slabs) Figure 47. Automated condition survey versus visual distress survey, slabs with corner breaks. R² = 0.73 0% 10% 20% 30% 40% 50% 0% 10% 20% 30% 40% 50% Au to m at ed C on di tio n Su rv ey (% sl ab s) Visual Distress Survey (% slabs) Figure 48. Automated condition survey versus visual distress survey, longitudinal cracking. R² = 0.55 0% 10% 20% 30% 40% 50% 0% 10% 20% 30% 40% 50% Au to m at ed C on di tio n Su rv ey (% sl ab s) Visual Distress Survey (% slabs) Figure 49. Automated condition survey versus visual distress survey, slabs with transverse cracking.

Field Performance of Selected Projects 59   The paired t-test was the statistical analysis used to evaluate the difference between the means of the automated and manual distress survey results. The t-test results indicated that a statistical difference in data set means exists between the data collection methods, except for longitudinal cracking (Table 31). Furthermore, Table 32 provides information on the percentage difference between the auto- mated and visual distress surveys. The automated method, on average, overestimated faulting and corner breaks by 93% and 33%, respectively, while underestimating longitudinal, trans- verse, and total cracking by 35%, 20%, and 26%, respectively. To assess the variability between the two pavement condition survey methods, an F-test (95% confidence level) was conducted (Table 33). The F-test results indicate that, aside from the methods being statistically different, the variability for each method is statistically different Figure 50. Automated condition survey versus visual distress survey, cracked slabs. R² = 0.86 0% 10% 20% 30% 40% 50% 0% 10% 20% 30% 40% 50% Au to m at ed C on di tio n Su rv ey (% sl ab s) Visual Distress Survey (% slabs) Condition Statistic t Critical Null Hypothesis p-Value Result Faulting 3.47 2.03 Not equal 0.00 Not equal Corner breaks 2.57 2.00 Not equal 0.01 Not equal Longitudinal cracking 1.05 2.00 Equal 0.30 Equal Transverse cracking 2.22 2.00 Not equal 0.03 Not equal Total cracking 3.09 2.00 Not equal 0.00 Not equal NOTE: “Equal” indicates the null hypothesis can be accepted, that is, the means of the two data sets are equal. “Not equal” indicates the null hypothesis can be rejected, that is, the means of the two data sets are not equal. α = 0.05. Table 31. t-test results of automated and visual distress surveys. Condition Difference (%) Avg. Min. Max. Faulting 93 −32 600 Corner breaks 33 −100 596 Longitudinal cracking −35 −100 120 Transverse cracking −20 −100 9 Total cracking −26 −100 295 Table 32. Difference in measurements in automated versus visual distress surveys.

60 Evaluation of Bonded Concrete Overlays on Asphalt Pavements for corner breaks, longitudinal cracking, and transverse cracking and is not statistically dif- ferent for faulting and total cracking. Although the methods are statistically different, a linear correlation does exist. Statistical Analysis of BCOA Features A multifactor statistical analysis was conducted to test factors and interactions potentially affecting BCOA performance. The factors used for the screening analysis were slab size, in-service age, joint sealing, synthetic macrofibers, ESALs, BCOA and asphalt layer thickness, and the interactions between slab size and BCOA thickness and BCOA and asphalt layer thick- ness. The results from this analysis, shown in Table 34, indicate BCOA performance is affected by certain features: • Faulting: The factors found to influence faulting were slab size (measured by area), BCOA thickness, the interaction between slab size and BCOA thickness, and the interaction between BCOA and asphalt layer thickness. For BCOA thickness greater than 6  in., increasing the asphalt layer thickness reduces the potential for faulting. In-service age, joint sealing, synthetic macrofibers, ESALs, and asphalt layer thickness showed no effect on faulting. • Corner breaks: The factors affecting corner breaks are slab size, in-service age, synthetic macro- fibers, ESALs, and the interactions of slab size–BCOA thickness and BCOA–asphalt layer thickness. Although these factors are significant, the number of corner breaks on in-service pavements was minimal. • Longitudinal cracking: None of the factors evaluated affected longitudinal cracking. • Transverse cracking: None of the factors evaluated affected transverse cracking. • Total cracking: None of the factors evaluated affected total cracking. Condition Statistic F Critical Null Hypothesis p-Value Result Faulting 1.18 1.92 Equal 0.62 Equal Corner breaks 4.27 1.71 Not equal 0.00 Not equal Longitudinal cracking 1.77 1.71 Not equal 0.04 Not equal Transverse cracking 2.09 1.71 Not equal 0.01 Not equal Total cracking 1.28 1.71 Equal 0.36 Equal NOTE: “Equal” indicates the null hypothesis can be accepted, that is, the variances of the two data sets are equal. “Not equal” indicates the null hypothesis can be rejected, that is, the variances of the two data sets are not equal. Table 33. F-test results for automated and visual distress surveys. Factor Fa ul tin g C or ne r Br ea ks Lo ng itu di na l C ra ck in g Tr an sv er se C ra ck in g To ta l C ra ck in g Lo ng itu di na l Sp al lin g Tr an sv er se Sp al lin g To ta l Sp al lin g Slab size (area) 0.01a 0.00a 0.22 0.05 0.19 0.77 0.60 0.65 In-service age 0.51 0.00a 0.65 0.34 0.61 0.02a 0.09 0.04a Joint sealing NA 0.32 0.92 0.12 0.84 0.12 0.58 0.43 Synthetic macrofibers 0.82 0.00a 0.66 0.75 0.66 0.03a 0.24 0.14 ESALs 0.75 0.00a 0.58 0.62 0.57 0.35 0.13 0.19 BCOA layer thickness 0.00a 0.15 0.96 0.31 0.99 0.10 0.42 0.61 Asphalt layer thickness 0.46 0.09 0.58 0.76 0.60 0.12 0.33 0.49 Slab size–BCOA thickness 0.00a 0.01a 0.68 0.17 0.63 0.14 0.60 0.46 BCOA–asphalt layer thickness 0.03a 0.00a 0.54 0.10 0.49 0.00a 0.77 0.30 NOTE: NA = not available. a Null hypothesis can be rejected; factor is statistically significant. Table 34. Summary of p-values for factors’ effect on performance.

Field Performance of Selected Projects 61   • Longitudinal joint spalling: The factors showing an effect were in-service age, synthetic macro fibers, and the interaction of BCOA–asphalt layer thickness. As in-service age increases, increased spalling is observed. The use of synthetic macrofibers, however, reduces the amount of spalling. • Transverse joint spalling: None of the factors evaluated affected transverse spalling. • Total spalling: In-service age was the only factor that affected total spalling. Because projects were constructed at different times and have been subjected to different traffic loads, the evaluated factors were normalized to 20-year design ESALs. The same multi- factor statistical analysis was performed as that summarized in Table 34. In the normalized ESAL analysis, in-service age and ESALs were excluded and only slab size, joint sealing, synthetic macrofibers, BCOA and asphalt layer thickness, and the interactions of slab size–BCOA and BCOA–asphalt layer thickness were included. Corner breaks were excluded because data were insufficient for the normalized data set. The normalized ESAL analysis, as shown in Table 35, found the following: • Slab size has an effect on all distress types except total cracking. • BCOA layer thickness has an effect on all distress types except total cracking, transverse joint spalling, and total spalling. • Joint sealing, macrofibers, and asphalt layer thickness have no effect on performance. • Slab size and BCOA layer thickness influenced faulting, longitudinal cracking, transverse cracking, and longitudinal joint spalling. • The combination of slab size and BCOA thickness and BCOA and asphalt layer thicknesses have an effect on faulting, longitudinal cracking, transverse cracking, and longitudinal joint spalling. The previous analysis showed joint sealing, synthetic macrofibers, and asphalt layer thick- ness having no effect on performance. The influence of BCOA thickness and asphalt thickness overweighed the effects of other factors. Since there is an interest in the effect of joint sealing and synthetic macrofibers on BCOA performance, an independent analysis could be conducted. The same multifactor statistical analysis was performed using the normalized ESAL approach; however, only joint sealing and synthetic macrofibers were analyzed. The statistical analysis showed the same results as the multifactor analysis, indicating that joint sealing and synthetic macrofibers have no effect on performance (Table 36). The statistical analysis results are only applicable to the projects included in this research and are not generalizable for BCOA. Furthermore, it is difficult to assess the effect of joint sealing Factor Fa ul tin g Lo ng itu di na l C ra ck in g Tr an sv er se C ra ck in g To ta l C ra ck in g Lo ng itu di na l Sp al lin g Tr an sv er se Sp al lin g To ta l Sp al lin g Slab size (area) 0.00a 0.00a 0.00a 0.48 0.00a 0.01a 0.01a Joint sealing NA 0.30 0.32 0.73 0.17 0.51 0.48 Synthetic macrofibers 0.40 0.57 0.51 0.21 0.68 0.89 0.88 BCOA layer thickness 0.00a 0.00a 0.00a 0.79 0.00a 0.36 0.30 Asphalt layer thickness 0.31 0.37 0.37 0.15 0.68 0.85 0.87 Slab size–BCOA thickness 0.00a 0.00a 0.00a 0.70 0.00a 0.19 0.14 BCOA–asphalt layer thickness 0.00a 0.00a 0.00a 0.87 0.00a 0.22 0.18 NOTE: NA = not available. a Null hypothesis can be rejected; factor is statistically significant. Table 35. Summary of p-values for factors’ effect on performance of normalized ESALs.

62 Evaluation of Bonded Concrete Overlays on Asphalt Pavements and synthetic macrofibers on BCOA performance under uncontrolled conditions. To assess and quantify the effectiveness of joint sealing and synthetic macrofibers, more extensive and controlled research is needed. Ultrasonic Tomography The ultrasonic tomograph is a nondestructive testing device used to determine pavement thickness, location and position of steel, degree of bonding or delamination, and activation of the sawed contraction joint (Tran, Roesler, and Popovics 2017). The tomography device uses multiple dry contact sensors to transmit shear waves (50 kHz) into the concrete pavement (Figure 51). The sensors receive the direct and reflected shear waves, then an algorithm is used to produce 2-D or 3-D ultrasonic tomography of the layer tested, which can be used to iden- tify layer thicknesses, presence of reinforcement, voids, and delamination (Choi et al. 2016; Popovics et al. 2017). The depth of the pavement layers can be calculated if the shear wave speeds in the concrete layer are known. The device determines asphalt layer thicknesses by assuming its shear wave speed is similar to concrete, which can in reality be different depend- ing on temperature. Ultrasonic tomography testing was conducted with a MIRA device on three sets of five con- secutive slabs within each 0.1-mi good, fair, and poor segment. An example ultrasonic tomog- raphy scan is provided in Figure 52. Table 36. Statistical summary on the effect of joint sealing and synthetic macrofibers on distress in BCOAs. NOTE: NA = not available. Distress Joint Sealing Synthetic Macrofibers p-Value Null Hypothesis p-Value Null Hypothesis Faulting NA NA 0.59 Not significant Map cracking 0.30 Not significant 0.30 Not significant Longitudinal cracking 0.65 Not significant 0.71 Not significant Transverse cracking 0.70 Not significant 0.70 Not significant Total cracking 0.66 Not significant 0.71 Not significant Longitudinal spalling 0.57 Not significant 0.58 Not significant Transverse spalling 0.66 Not significant 0.66 Not significant Total spalling 0.65 Not significant 0.65 Not significant (a) (b) Figure 51. Ultrasonic tomography device (a) and operating face (b). (Source: J. Roesler.)

Field Performance of Selected Projects 63   The reflected shear wave amplitude and shear wave velocity at a particular location are displayed in the output on the left side of the image (the x and z coordinates can be ignored). The largest amplitude is the reflection of the shear wave at the concrete–asphalt interface. The depth of the largest amplitude corresponds with the thickness of the BCOA layer. Subsequent reflections below the concrete–asphalt interface may be the reflection at the asphalt base/subbase interface but can also be internal BCOA layer signal reflections and can be ignored. In general, a warm asphalt layer attenuates the shear wave signal, and little information can be discerned below the BCOA layer. Table 37 provides a comparison of ultrasonic tomography and BCOA core thickness results. Because the standard ultrasonic tomography algorithm cannot reliably calculate the second (i.e., asphalt) layer thickness, Table 37 provides a summary of BCOA layer thickness results only. BCOA: 6.3” (160mm) Slab-base interface Plot of reflected shear wave amplitude with pavement depth Internal signal reflections (can be ignored) Base-subbase/soil interface: 9.3” (235mm) Figure 52. Example ultrasonic tomography results. Project ID Ultrasonic Tomography Core No. of Readingsa Avg. (in.) SD (in.) No. of Coresa Avg. (in.) SD (in.) CO SH-121A 60 6.0 0.4 8 5.8 0.2 CO SH-121B 60 6.2 0.5 8 7.1 0.4 CO US-6 60 6.1 0.4 8 5.8 0.1 IA US-71 120 6.1 0.7 8 6.5 0.3 IL CH-27 14 5.0 0.5 8 5.4 0.2 IL SR-53 8 3.5 0.4 8 3.8 0.2 KS I-70 41 5.5 0.4 8 5.7 0.2 LA US-167 59 9.6 1.6 7 10.0 5.1 LA US-425 60 4.3 0.8 8 4.2 0.4 MN CSAH-7 97 5.2 0.6 8 5.8 0.9 MN CSAH-22 81 7.0 0.9 8 6.9 0.3 MN I-35 40 6.1 0.4 4 6.0 0.0 MN TH-30 60 6.0 1.1 8 6.3 0.3 MO US-60 40 4.3 0.7 8 4.4 0.2 MT SR-16 47 5.2 0.7 7 4.4 0.1 PA SR-119 20 6.8 0.5 8 6.9 0.2 a Indicates the number of ultrasonic tomography tests or cores per project. Table 37. Ultrasonic tomography versus core BCOA thickness measurements.

64 Evaluation of Bonded Concrete Overlays on Asphalt Pavements A goodness of fit between the ultrasonic tomography and core results is shown in Figure 53. Only the ultrasonic tomography results near the core locations were used in this analysis. If the outliers (shown as black circles) are removed, the goodness of fit (R2 = 0.993) is acceptable. A statistical analysis was performed to determine whether the BCOA layer thickness deter- mined from coring and the ultrasonic tomography analysis are significantly different (Table 38). The two-tailed t-test indicated the means are equal. The F-test results indicated the variance is not equal, however, based on the p-value, the findings are not significant. Therefore, based on the statistical analysis, the ultrasonic tomography accurately determines BCOA layer thickness as compared with coring. Falling Weight Deflectometer Testing An FWD device was used to conduct tests on each good, fair, and poor segment (Figure 54). The FWD results were used to measure the LTE across joints and to determine the stiffness of the various pavement layers. FWD test locations (center slab, transverse joint, and slab corner) were in accordance with the approach developed by King and Roesler (2014b). FWD loading ranged from 6,000 to 12,000 lb using sensors spaced at −8, 0, 12, 18, 24, 36, 48, and 60 in. FWD deflection data were used to backcalculate effective slab thickness, differential and overall deflections near transverse joints, and joint performance through measured LTE. BCOA structural All Data y = 1.02x R² = 0.927 Outliers Removed y = 1.0231x R² = 0.993 0 3 6 9 12 15 0 3 6 9 12 15 Co re (i nc h) Ultrasonic Tomography (inch) outlier(s) Figure 53. Ultrasonic tomography–determined thickness versus BCOA core thickness. Test Statistic Critical Null Hypothesis p-value Result t-test −1.19 2.05 Equal 0.24 Not significant F-test 0.72 0.53 Not equal 0.20 Not significant NOTE: “Equal” indicates the null hypothesis can be accepted, that is, the mean (variance) of the two data sets are equal. “Not equal” indicates the null hypothesis can be rejected, that is, the mean (variance) of the two data sets are not equal. α = 0.05. Table 38. t- and F-test results for ultrasonic tomography and BCOA core thickness.

Field Performance of Selected Projects 65   performance was based on two-dimensional finite element modeling using a procedure devel- oped by King and Roesler (2014b). This procedure establishes a backcalculated effective concrete thickness (concrete overlay + asphalt concrete layer + other support layers) as a metric to quan- tify the load-carrying capacity of BCOA pavements. The effective thickness approach is intended to determine the combined capacity of the BCOA in concrete effective thickness (Figure 55). The effective thickness (heff) can also be used as an indirect method for evaluating the condition of the concrete–asphalt bond (King and Roesler 2014b). The backcalculation procedure includes the AREA24 deflection profile for 4- × 4-ft slabs: = ∗ + ∗ +     AREA 6 1 2 (4)24 12 0 24 0 d d d d where d0, d12, and d24 = deflections at offset of 0, 12, and 24 in., respectively (in.). For larger slab sizes, the AREA36 parameter was used to backcalculate the effective thickness and modulus of subgrade reaction (k-value). Figure 55. BCOA pavement model. (Source: King and Roesler 2014a.) Figure 54. FWD testing device. (Source: Minnesota DOT.)

66 Evaluation of Bonded Concrete Overlays on Asphalt Pavements The LTE, calculated as the ratio of the deflection of the unloaded slab (approach slab) to the loaded slab (leave slab), was found using the following formula: ( ) = ∗LTE % 100% (5) d d unloaded loaded where dunloaded = deflection of the unloaded slab, and dloaded = deflection of the loaded slab. Relative stiffness is found using the following formula: ( )= − µ    12 1 (6) 3 2 1 4 l Eh k where l = relative stiffness, E = elastic modulus (psi), h = effective thickness (in.), µ = Poisson’s ratio, and k = modulus of subgrade reaction (pci, or pounds per cubic inch). An assumed modulus of elasticity of 5,000,000 psi and a Poisson’s ratio of 0.15 were selected for the composite pavement effective thickness calculation at each FWD test location and load level. Table 39 summarizes the average LTE, calculated k-value, and effective thickness results. The average transverse joint LTE, for all projects, ranged from 64% to 93% (average of 86% and standard deviation of 6%). These values (and those in the remainder of this discussion) represent LTE results for which the FWD test temperatures were less than 75°F (higher test temperatures occurred on 10 segments as noted in the table). Average LTEs were approximately equal for all good, fair, and poor segments (85%, 87%, and 86%, respectively). Only MN CSAH-22 had average LTE values lower than 75%. Four segments (9% of segments) had LTE less than 80%, 29 segments (66% of segments) had LTE between 80% and 90%, and 10 segments (25% of seg- ments) had LTE greater than 90%. The k-value ranged from 250 to 4,619 pci, with an average of approximately 935 pci (standard deviation of 556 pci). Such high values could be a result of joints not being fully activated (i.e., cracks did not propagate), short slab sizes, and effects of the underlying asphalt layer. Average estimated k-values were highest in the good segments compared with the fair and poor segments (1,059 pci, 893 pci, and 879 pci, respectively). Backcalculated effective thickness values for all projects ranged from 5.4 to 11.2 in. (average of 8.3 in., standard deviation of 1.9 in.). The average effective thicknesses of the poor and good sections were 8.5 in. (standard deviation of 1.6 in. and 1.4 in., respectively), suggesting poor- performing sections are not necessarily defined by inadequate effective thickness. The average difference in effective thickness within a given project site, for all projects, was 1.1 in. This average difference translates to approximately 13% variation in backcalculated effec- tive thickness. The effective thicknesses were greater than the measured field cores (BCOA layer only) for 78% of the core locations. The effective thicknesses ranged from −1.4 to 5.5 in. thicker than the average BCOA field core. The average effective thickness was 2.1 in. greater than the average BCOA core thickness.

Field Performance of Selected Projects 67   Project ID Segment Age (years) Surface Temp. (°F) LTE (%) k-value (pci) heff (in.) Avg. SD Avg. SD Avg. SD CO I-70 Good 7 66 85 10 4,619 4,006 11.0 1.4 Fair 7 77 90a 3 1,414 401 10.5 1.7 Poor 7 51 88 11 1,672 340 10.7 1.4 CO SH-83A Good 19 78 90a 7 639 275 9.8 1.4 Fair 19 72 87 8 1,154 333 8.4 1.1 Poor 19 63 91 5 1,123 214 10.5 2.0 CO SH-83B Good 14 52 83 12 506 150 8.2 1.0 Fair 14 50 78 16 514 221 8.6 1.4 Poor 14 52 84 10 613 152 7.6 0.9 CO SH-121A Good 19 54 87 7 884 103 8.5 0.8 Fair 19 62 90 3 769 56 8.6 0.7 Poor 19 60 92 3 928 135 7.7 0.4 CO SH-121B Good 8 49 89 3 1,283 303 7.9 1.1 Fair 8 64 89 5 1,232 200 8.1 0.5 Poor 8 57 83 12 1,194 585 8.2 0.6 CO US-6 Good 21 68 85 8 486 144 6.7 1.3 Fair 21 51 83 11 444 138 6.8 1.5 Poor 21 59 88 8 487 153 6.4 1.3 IA US-71 Good 7 62 92 4 382 86 8.3 0.5 Fair 7 56 92 3 364 49 8.0 0.3 Poor 7 60 87 6 536 99 8.5 0.8 IL CH-27 Good 16 57 89 3 625 69 7.5 0.2 Fair 16 67 92 3 402 11 8.0 0.1 Poor 16 45 90 3 672 33 7.7 0.1 IL SR-53 Good 7 57 87 8 891 261 7.3 1.3 Fair 7 83 86a 7 696 167 6.1 1.2 Poor 7 71 83 11 941 263 6.2 1.2 KS I-70 Good 8 75 96a 4 488 68 9.3 1.1 Fair 8 73 96 4 413 64 9.6 1.3 Poor 8 72 96 8 633 124 9.7 1.1 LA US-167 Good 21 65 91 6 960 261 7.2 0.5 Fair 21 63 89 4 891 85 7.2 0.4 Poor 21 65 90 13 1,115 404 8.1 0.7 LA US-425 Good 16 95 88a 5 2,338 458 10.3 0.9 Fair 16 104 89a 3 2,410 368 9.5 0.9 Poor 16 84 93a 2 1,335 276 9.9 1.1 MN CSAH-7 Good 10 57 83 10 443 164 6.6 0.9 Fair 10 53 81 7 548 182 5.4 0.8 Poor 10 47 78 9 250 35 6.7 0.7 MN CSAH-22 Good 8 53 64 13 820 35 7.4 0.9 Fair 8 NA NA NA NA NA NA NA Poor 8 50 75 15 846 345 9.6 3.2 MN I-35 Good 10 52 84 10 732 92 10.7 1.4 Fair 10 NA NA NA NA NA NA NA Poor 10 53 82 9 687 96 8.4 1.1 MN TH-30 Good 26 58 85 6 426 56 11.2 1.5 Fair 26 60 85 5 371 91 11.0 1.1 Poor 26 52 81 4 443 55 10.5 0.9 MO US-60 Good 20 NA NA NA NA NA NA NA Fair 20 72 80 7 1,671 515 6.5 0.5 Poor 20 NA NA NA NA NA NA NA MT SR-16 Good 18 30 87b 3 1,716 290 8.7 0.5 Fair 18 39 83 9 1,055 253 7.3 0.6 Poor 18 38 89 3 1,425 216 8.8 0.7 PA SR-119 Good 9 85 85a 2 821 148 6.5 0.4 Fair 9 100 83a 2 841 177 6.2 0.6 Poor 9 76 85a 2 922 152 7.0 0.4 NOTE: NA = not available. a High load transfer may be affected by high surface temperature. b Subgrade layer may be frozen; however, air temperatures were above 32°F for 7 days before testing. Table 39. LTE, k-value, and effective thickness.

68 Evaluation of Bonded Concrete Overlays on Asphalt Pavements A comparison of as-cored bond condition with calculated condition based on effective thick- ness is illustrated in Figure 56. If the effective thickness is approximately equal to or less than the BCOA thickness, it suggests the interface bond has deteriorated. If the effective thickness exceeds the BCOA thickness, it suggests at least a partial bond. Figure 56 illustrates four com- parison categories: • True bonded: Both core and effective thickness indicate at least a partial bond (28%). • True unbonded: Both core and effective thickness indicate a deteriorated bond (14%). • False bonded: The core is unbonded, but effective thickness suggests at least a partial bond (7%). • False unbonded: The core is bonded, but effective thickness suggests a deteriorated bond (52%). For the projects evaluated, FWD testing (i.e., effective thickness) appears able to estimate bond condition for approximately 41% of the cores. However, the coring operation could cause separation of the bond, resulting in fewer false unbonded conditions than estimated. Coring, Dynamic Cone Penetrometer Testing, and Unbound Material Sampling Four cores were scheduled to be extracted from each good and poor segment (Figure 57). Because of time limitations, not all cores were obtained as planned; nearly 150 cores were ulti- mately extracted. Extracted cores were 6 in. in diameter and extended through both the concrete and the underlying asphalt layer. Cores were extracted from slabs where ultrasonic tomography and FWD tests were conducted to assist in the calibration and verification of ultrasonic tomog- raphy results. 0 5 10 15 20 0 5 10 15 20 Eff ec tiv e Th ic kn es s ( in ch ) Measured Core Thickness (inch) True bonded True unbonded False unbonded False bonded At least partial Deteriorated bond Figure 56. Comparison of core and estimated bond condition.

Field Performance of Selected Projects 69   Two of the four cores were extracted at the slab center, one was bridging a transverse joint in the wheelpath, and the last was centered 9 in. away from the transverse joint in the right wheelpath. Cores obtained at the slab center were used to evaluate the degree of bonding repre- sentative of bonding at time of construction. Cores extracted on the transverse joint were used to assess joint activation through the asphalt base, moisture damage in the asphalt, slab–asphalt debonding, and near-surface asphalt failure. Cores obtained 9 in. away from a transverse joint and in the wheelpath were used to evaluate moisture damage and bonding of the core away from the joint. DCP tests were conducted at one center slab core location and one joint location for each good and poor segment, starting at the top of the first unbound layer (Figure 58). DCP tests were conducted in accordance with ASTM D6951. Results were used to estimate the thickness of unbound layers and in situ California bearing ratio values. After DCP testing, samples of the unbound pavement layers (i.e., base, subbase, and subgrade) were obtained by hand augering at the two center slab locations. Extracted cores and hand-augered material were packaged and shipped for laboratory testing. Figure 59 illustrates testing locations for ultrasonic tomography, FWD, faultmeter, DCP, coring, and unbound material sampling for projects with 4- × 4-ft slabs, and Figure 60 for all project sites with 5.5- × 5.5-ft, 6- × 6-ft, 6-ft × variable length, and 12- × 12-ft slabs. Table 40 summarizes layer type and thickness and Table 41 summarizes the subgrade modulus estimated from DCP results. Figure 57. Coring. (Source: NCE.) Figure 58. DCP testing. (Source: NCE.)

Center of slab Right wheelpath Not to scale Core (6 in) - center of slab Core (6 in)+ DCP + Unbound Layer Sample - center of slab Core (6 in) - centered over joint in wheelpath Core (6 in)+ DCP - ± 6 in from joint in wheelpath FWD (drops - seating, 6000, 9000, 12000 lbs) FWD + MIRA (3 repeat tests, pick up and replace MIRA after each test) Faultmeter Note: coring, DCP, and unbound layer sample conducted only in "good" and "poor" condition segments. 0.1-mile segment Segment 1 Segment 2 Segment 3 Centerline 1 2 1 2 4 3 3 4 Figure 59. Field-testing locations of 4- ë 4-ft slabs.

Right wheelpath Not to scale MIRA + Core (6 in) - center of slab MIRA + Core (6 in)+ DCP + Unbound Layer Sample - center of slab Core (6 in) - centered over joint ± 3 ft from lane/shoulder edge Core (6 in)+ DCP - ± 6 in from joint ± 3 ft from lane/shoulder edge FWD (drops - seating, 6000, 9000, 12000 lbs) FWD + MIRA (3 repeat tests, pick up and replace MIRA after each test) Faultmeter 0.1-mile segment Centerline Segment 1 Segment 2 Segment 3 1 2 4 3 1 2 43 Note: coring, DCP, and unbound layer sample conducted only in "good" and "poor" condition segments. Figure 60. Field-testing locations for slab sizes other than 4 ë 4 ft.

72 Evaluation of Bonded Concrete Overlays on Asphalt Pavements LA US-167 BCOA 14.0 14.0 14.0 14.0 14.0 0.0 4.8 a 4.8 4.1 4.6 0.4 Asphalt na na na na na na 8.7 a 8.7 9.3 8.9 0.3 Unbound Compacted clay Compacted clay LA US-425 BCOA 4.5 4.5 4.5 4.6 4.5 0.1 3.9 3.9 3.7 3.7 3.8 0.1 Asphalt 9.5 3.9 2.0 a 5.1 3.9 10.1 3.5 1.4 1.3 4.1 4.2 Unbound Soil cement layer over clayey silt Soil cement layer over clayey silt MN CSAH-7 BCOA 6.5 6.7 6.5 6.7 6.6 0.1 4.9 4.9 4.9 4.9 4.9 0.0 Asphalt 6.7 a a 6.7 6.7 0.0 a 8.1 a a 8.1 na Unbound Coarse sand Coarse sand MN CSAH-22 BCOA 6.5 6.7 6.7 6.5 6.6 0.1 7.3 7.1 7.1 7.1 7.1 0.1 Asphalt 3.2 3.2 3.2 3.3 3.2 0.1 6.7 6.7 6.3 6.5 6.6 0.2 Unbound Rocky sand Rocky sand MN I-35 BCOA 6.0 6.0 6.0 6.0 6.0 0.0 6.3 a a a na na Asphalt 14.0 a a a na na 10.0 a a a na na Unbound Black rocky sand soil MN TH-30 BCOA 6.1 5.9 6.1 5.9 6.0 0.1 6.7 6.7 6.3 6.5 6.5 0.2 Asphalt a a 5.7 a na na 5.5 5.5 a a 5.5 0.0 Soil cement a a 5.7 a na na 0.0 0.0 0.0 0.0 0.0 0.0 Unbound Clayey soil Clayey soil MO US-60 BCOA 4.4 4.5 4.6 4.6 4.5 0.1 4.3 4.1 4.3 4.4 4.3 0.1 Asphalt 4.8 4.8 4.8 4.5 4.7 0.1 5.6 5.4 5.4 5.6 5.5 0.1 Unbound Limestone aggregate base Limestone aggregate base MT SR-16 BCOA 4.5 4.5 4.3 4.5 4.5 0.1 4.3 4.3 4.3 4.1 4.3 0.1 Asphalt 3.5 3.7 3.9 3.5 3.7 0.2 2.8 3.0 2.6 3.0 2.8 0.2 Unbound Fill Fill PA SR-119 BCOA 6.7 6.7 6.7 6.7 6.7 0.0 7.1 7.1 7.1 7.1 7.1 0.0 Asphalt 9.1 a a a na na 8.3 a a a na na Unbound Aggregate base (possibly several ft deep) Asphalt-treated base (permeable) NOTE: na = not applicable. a Core not obtained because of lane-closure restriction. Route Layera Layer Thickness (in.) Good Segment Poor Segment Core No. Avg. SD Core No. Avg. SD 1 2 3 4 1 2 3 4 CO I-70 BCOA 6.8 6.5 7.0 6.9 6.8 0.2 5.9 6.2 6.1 5.9 6.0 0.1 Asphalt 15.9 15.2 15.2 14.12 15.1 0.7 12.6 12.5 12.2 11.2 12.1 0.6 Unbound Clay Clay CO SH-83A BCOA 5.7 5.3 5.5 5.3 5.5 0.2 10.4 10.2 10.4 10.6 10.4 0.2 Asphalt 9.1 9.1 9.1 9.5 9.2 0.2 7.5 7.7 7.5 7.5 7.5 0.1 Unbound Fine grained Fine grained CO SH-83B BCOA 5.9 5.9 5.7 5.9 5.9 0.1 6.1 a 5.9 5.9 6.0 0.1 Asphalt 12.6 12.6 13.0 12.8 12.7 0.2 12.8 a 13.0 12.8 12.9 0.1 Unbound Fine grained Fine grained CO SH-121A BCOA 5.9 5.9 5.9 6.1 6.0 0.1 5.7 5.7 5.7 5.5 5.7 0.1 Asphalt 7.3 7.3 7.1 6.9 7.1 0.2 7.7 7.9 7.9 7.9 7.8 0.1 Unbound Fill Fill CO SH-121B BCOA 7.3 7.7 7.5 7.7 7.5 0.2 6.7 6.7 6.7 6.9 6.7 0.1 Asphalt 3.7 3.7 3.7 3.3 3.6 0.2 5.7 5.5 5.7 5.5 5.6 0.1 Unbound Clayey sandy gravel Dirty aggregate base with some clay CO US-6 BCOA 5.7 5.8 5.9 5.7 5.8 0.1 5.7 5.8 5.9 5.7 5.8 0.1 Asphalt 3.5 3.2 3.3 3.3 3.4 0.1 3.5 3.2 3.3 3.3 3.4 0.1 Unbound Unspecified Unspecified IA US-71 BCOA 6.5 6.5 6.5 6.5 6.5 0.0 6.5 6.0 6.5 6.3 6.3 0.2 Asphalt 11.0 10.5 4.5 11.0 9.3 3.2 2.5 12.0 12.0 4.0 7.6 5.1 Unbound Unspecified Unspecified IL CH-27 BCOA 5.3 5.3 5.1 5.1 5.2 0.1 5.5 5.5 5.4 5.5 5.5 0.0 Asphalt 10.4 9.1 7.5 7.5 8.6 1.4 2.8 3.0 2.6 2.8 2.8 0.1 Unbound Sandy clay with some small aggregates Sandy clay with some small aggregates IL SR-53 BCOA 3.9 3.9 4.1 3.9 4.0 0.1 3.5 3.5 3.5 3.5 3.5 0.0 Asphalt 5.7 5.5 5.3 5.7 5.6 0.2 12.6 12.6 12.8 12.8 12.7 0.1 PCC 13.98 na na 4.72 na na Unbound High-plasticity clay with some small aggregates High-plasticity clay with some small aggregates KS I-70 BCOA 5.9 5.9 5.9 5.9 5.9 0.0 5.5 5.5 5.5 5.5 5.5 0.0 Asphalt 18.1 a 18.1 a 18.1 0.0 25.2 27.2 a a 26.2 1.4 Fly ash stabilized sand 0.59 na na na nana na na na na na na na na na na na na Unbound Black clay Black clay Black rocky sand soil Table 40. Summary of core results.

Field Performance of Selected Projects 73   Laboratory Testing Laboratory tests were conducted on all extracted field cores and unbound material samples. Laboratory testing encompassed AASHTO soil classification, Atterberg limits, and grada- tion; concrete compressive and split tensile strength; concrete coefficient of thermal expansion (CTE); dynamic modulus of asphalt core [via indirect tensile test (IDT) for creep]; Hamburg wheel testing of asphalt concrete cores; asphalt bulk-specific gravity; shear strength of concrete– asphalt bond; and gradation. Because the concrete and asphalt separated in many cores, only the static shear-strength tests were completed on intact cores. Dynamic shear tests in the wet and dry state, as well as direct tension tests of the concrete–asphalt interface, were originally part of the test plan but were not run because of the limited number of intact cores. The IDT creep test (converted to dynamic modulus), static shear-strength test, and Hamburg wheel tracking test were conducted to provide additional data on the asphalt layer. Results of the laboratory analysis are provided in Appendix C as part of each portfolio and in total in Appendix D. Concrete cores were stored in a dry environment for several months before testing. The 14 cores that required additional coring to meet compressive strength testing requirements were stored for at least a week before testing. Concrete cores were also trimmed to remove the bonded asphalt layer after shear testing and to obtain a smooth face (i.e., to remove the asphalt layer and tined surface). Soil Classification, Atterberg Limits, and Aggregate Gradation The Atterberg limits were determined in accordance with ASTM D4318 and soil classification in accordance with ASTM D3282. Liquid limits were determined using a Casagrande apparatus, and plastic limits were determined by rolling the specimen by hand (Figure 61). A summary of soil classification and Atterberg limits is provided in Table 42. The majority of aggregate base and subgrade materials tested were classified as granular materials, with less than 35% passing the No. 200 sieve (AASHTO soil classification A-1, A-2, and A-3). One poor subgrade sample Route Subgrade Modulus (psi) Good Segment Poor Segment Core No. Avg. SD Core No. Avg. SD 1 2 3 4 1 2 3 4 CO I-70 19,006 — — 23,946 21,476 3,493 — 10,865 8,877 — 9,871 1,406 CO SH-83A 23,946 — — 21,753 22,850 1,551 11,295 — — 10,202 10,749 773 CO SH-83B — 9,591 — 6,004 7,798 2,536 17,324 — — 14,580 15,952 1,940 CO SH-121A — b — b na na 8,466 — — 8,631 8,549 117 CO SH-121B — 10,202 — 11,716 10,959 1,071 — 13,833 a — na na CO US-6 9,669 — — 5,161 7,415 3,188 9,669 — — 8,403 8,856 1,150 IA US-71 a na na a na na IL CH-27 7,870 — — 7,429 7,650 312 8,213 — — 7,518 7,866 491 IL SR-53 a — — 6,401 na na 5,592 — — a na na KS I-70 8,877 — 8,877 — 8,877 0 4,825 — 3,982 — 4,404 596 LA US-167 6,785 — — 8,466 7,626 1,189 8,043 — b — na na LA US-425 a a MN CSAH-7 6,595 8,213 — — 7,404 1,144 — 5,903 — a na na MN CSAH-22 20,048 — 14,580 — 17,314 3,866 b — b — na na MN I-35 b — — a na na a — — a na na MN TH-30 6,595 — — a na na 8,213 5,050 — — 6,632 2,237 MO US-60 — 12,931 — 10,865 11,898 1,461 — 14,580 — 14,085 14,333 350 MT SR-16 — b — 30,436 na na — b — b na na PA SR-119 c c NOTE: — = DCP testing not conducted; na = not applicable. a Core not obtained because of lane-closure restriction. b Refusal. c Unable to clear aggregate base from core hole. Table 41. Summary of subgrade modulus from DCP testing.

74 Evaluation of Bonded Concrete Overlays on Asphalt Pavements Project ID Segment Layer AASHTO Soil Class Liquid Limit Plastic Limit Plasticity Index CO I-70 Good Subgrade A-2-7 43 30 13 Poor Subgrade A-2-6 34 22 12 CO SH-83A Good Subgrade A-2-4 29 22 7 Poor Subgrade A-1-b 33 29 5 CO SH-83B Good Subgrade A-3 Nonplastic na na Poor Subgrade A-1-b Nonplastic na na CO SH-121A Poor Aggregate base A-1-b Nonplastic na na Good Subgrade A-1-a Nonplastic na na CO SH-121B Good Aggregate base A-1-a Nonplastic na na Poor Aggregate base A-1-a 20 19 1 Good Subgrade A-2-4 37 27 10 Poor Subgrade A-2-6 38 27 11 CO US-6 Good Subgrade A-1-b 18 17 1 Poor Subgrade A-1-b Nonplastic na na IA US-71 Good Aggregate base A-1-b Nonplastic na na IL CH-27 Good Subgrade A-1-a 18 15 2 Poor Subgrade A-1-a Nonplastic na na IL SR-53 Good Subgrade A-2-4 20 17 2 Poor Subgrade A-2-7 43 27 16 KS I-70 Good Subgrade A-2-4 32 23 9 Poor Subgrade A-2-7 43 25 17 LA US-167 Good Subgrade A-3 Nonplastic na na Subgrade A-2-4 28 27 1 Poor Subgrade A-2-4 24 21 3 LA US-425 Good Subgrade A-2-4 41 34 7 Poor Subgrade A-1-b 24 24 0 MN CSAH-7 Good Subgrade A-1-b Nonplastic na na Poor Subgrade A-1-b Nonplastic na na MN CSAH-22 Good Subgrade A-1-b Nonplastic na na Poor Subgrade A-1-b Nonplastic na na MN I-35 Good Subgrade A-3 Nonplastic na na Poor Subgrade A-4 Nonplastic na na MN TH-30 Good Subgrade A-1-b Nonplastic na na Poor Subgrade A-1-b Nonplastic na na MO US-60 Good Aggregate base A-1-a Nonplastic na na MT SR-16 Good Aggregate base A-1-a Nonplastic na na Poor Aggregate base A-1-b Nonplastic na na PA SR-119 Good Subgrade A-1-a Nonplastic na na NOTE: na = not applicable. Table 42. Summary of soil classification and Atterberg limits. (a) (b) Figure 61. Liquid limit test apparatus (a) and plastic limit specimen (b). (Source: J. Roesler.)

Field Performance of Selected Projects 75   (MN I-35) was classified as a silty material, with more than 35% passing the No. 200 sieve. The liquid limits tested ranged from nonplastic to 43%, with a maximum plastic limit of 34%. Gradation of the materials sampled from each project was determined in accordance with ASTM D6913. Results of the gradation analysis are provided in the individual project portfolios (Appendix C). Concrete Compressive and Split Tensile Strength For the core sample, compressive strength was measured in accordance with ASTM C39 and split tensile testing in accordance with ASTM C496 (Figure 62). ASTM C39 calls for cylinders 11.8 in. high by 5.9 in. in diameter, which could not be obtained from any of the specimens, given that the maximum concrete thickness of the overlays was approximately 6.0 in. The stan- dard does allow for a correction factor for a length to diameter (L/D) ratio greater than 1, but for all the specimens, L/D is less than 1. Therefore, a modified technique to enable concrete test- ing was required. First, all cores were cut to a thickness of 4 in. The diameter of the specimens was approximately 6 in., which resulted in L/D of approximately 0.67 for all specimens. Next, a subset of the specimens was sampled and cored to a diameter of 2.75 in. to provide an L/D of approximately 1.45. The compressive strength of these cored cylinders was measured and corrected using the correction factors from Sim et al. (2013). Table 43 provides a summary of measured and corrected concrete compressive strength by project and core number. Split tensile strength was compared with the corrected compressive strength to build a corre- lation between the two tests. The correlation recommended by the American Concrete Institute building code, ACI 318, is as follows = ′6.74 (7)f fspt c where fspt = split tension (psi), and f c′ = compressive strength (psi). Using the same functional form = ′ ,f k fspt c the best fit curve was found to be = ′5.78 (8)f fspt c There is a poor correlation between split and compressive strength for the project cores, as well as a large variation in compressive strength relative to the split tensile strength, especially for specimens with higher compressive strength (Figure 63). A slightly better correlation was found by setting both the coefficient and the exponent as free variables using the following: ( )= ′7.17 (9)0.70f fspt c The resulting correlation is shown in Figure 64. Previous studies have recommended leaving both the coefficient and the exponent as free variables. Therefore, the improved correlation relationships were used to calculate the corrected compressive strength of all the split-tensile specimens, as shown in Table 44. Concrete Coefficient of Thermal Expansion CTE measurements were in accordance with AASHTO T 336. Although the specification requires a concrete sample of 7.0-in. thickness, only one of the field cores met this requirement.

76 Evaluation of Bonded Concrete Overlays on Asphalt Pavements Project ID Segment Core No. Required Min. (psi)a, b Measured (psi) Corrected (psi) CO SH-83A Poor 8 2,000 9,570 7,370 CO SH-121A Good 2 2,000 6,540 5,030 Poor 6 7,050 5,420 CO SH-121B Good 4 2,000 6,090 4,690 Poor 6 7,960 6,120 IA US-71 Good 3 500b 8,300 6,380 4 (7-day) 7,640 5,870 IL CH-27 Good 1 3,500 7,210 5,560 Poor 5 (14-day) 9,570 7,370 6 8,850 6,800 8 11,300 8,690 IL SR-53 Good 4 3,500 10,440 8,040 Poor 8 (14-day) 11,210 8,630 KS I-70 Good 4 450b 7,760 5,980 Poor 5 6,450 4,960 LA US-425 Good 1 3,000 6,450 4,960 Poor 8 6,220 4,790 MN TH-30 Good 8 3,000 6,800 5,240 MO US-60 Good 1 4,600 7,950 6,120 Poor 6 (28-day) 7,220 5,560 MT SR-16 Good 4 500b 10,790 8,300 Poor 8 10,070 7,750 PA SR-119 Good 2 3,750 9,940 7,640 Poor 8 (28-day) 8,250 6,340 a Based on agency standard specification. If the number of days is not specified, value is based on strength for opening to traffic. b Flexural strength. Table 43. Summary of concrete compressive strength. (a) (b) Figure 62. Compressive strength testing (a) and split tensile strength testing (b) of core samples.

Field Performance of Selected Projects 77   y = 5.8249x R² = 0.3189 – 200 400 600 800 65 70 75 80 85 90 95 f_ sp t ( lb /i n2 ) sqrt(f'c) Figure 63. Correlation between split and compressive strength. y = 0.9703x0.7021 R² = 0.3852 0 200 400 600 800 4000 5000 6000 7000 8000 9000 f_ sp t ( lb /i n2 ) f'c (lb/in2) Figure 64. Improved correlation between split and compressive strength. Consequently, the concrete portion of each core was cut to a height of approximately 4.0 in., and a stainless-steel cylinder 3.0 in. tall was placed underneath it during the test (Figure 65). CTE was determined using ( )α = α + − α (10)1 1 2 2 2 1 L L L L where L1 = measured thickness of the concrete (in.), L2 = height of stainless-steel cylinder (3 in.), α = measured CTE of the concrete-stainless-steel composite, α1 = CTE of concrete sample (× 10-6 in./in./°F), and α2 = CTE of stainless steel (8.5 × 10-6 in./in./°F).

78 Evaluation of Bonded Concrete Overlays on Asphalt Pavements MN I-35 Good 1 334 2 348 Poor 5 319 MN TH-30 Good 1 435 4 479 Poor 5 319 6 363 MT SR-16 Good 2 609 Poor 5 580 6 537 PA SR-119 Good 1 682 4 812 4,105 4,351 3,844 5,903 6,730 3,756 4,670 9,805 8,862 7,963 11,400 14,504 Project ID Segment Core No. Split Tensile (psi) Corrected Compressive (psi) CO I-70 Poor 5 435 6,005 6 377 4,873 CO SH-83A Good 1 406 5,540 2 305 3,553 4 508 7,513 Poor 5 421 5,729 6 319 3,844 8 479 6,773 CO SH-83B Good 1 464 6,657 2 392 5,250 4 377 4,844 Poor 5 479 6,904 CO SH-121A Good 1 406 5,294 Poor 5 348 4,322 8 450 6,208 CO SH-121B Good 2 334 4,206 Poor 5 450 6,237 8 450 6,396 CO US-6 Good 1 464 6,599 2 537 8,151 4 334 4,047 Poor 6 493 7,121 8 421 5,831 IA US-71 Good p4 450 6,353 p1 508 7,542 1 479 6,759 2 508 7,339 IL SR-53 Poor 5 435 5,990 KS I-70 Good 1 508 7,571 2 334 4,119 LA US-167 Good 1 566 8,615 Poor 8 348 4,424 LA US-425 Good 2 276 3,133 4 406 5,526 MN CSAH-7 Good 1 493 7,165 2 406 5,366 3 435 5,889 4 551 8,354 Poor 5 493 7,237 6 493 7,281 8 566 8,572 MN CSAH-22 Good 1 319 3,800 2 406 5,497 Poor 5 421 5,627 6 609 9,601 8 450 6,367 Table 44. Concrete split tensile and corrected compressive strength.

Field Performance of Selected Projects 79   This formula was derived from first principles of solid mechanics and verified using Core 1 from the LA US-167 project (where a 7-in. cylinder could be extracted). The CTE of this cylinder was measured per the specification and found to be 6.0 in./in./°F × 10-6. The core was cut to a thickness of 4.0 in., and the CTE was determined with the composite stainless-steel cylinder setup and found to be 6.1 × 10-6 in./in./°F. The difference between these two values is 2.7%, which is acceptable. Therefore, the modified approach for measuring CTE on thinner concrete layers was used for the other specimens. The measured CTE is summarized in Table 45. Asphalt Complex Modulus Complex modulus E* was determined using an IDT testing device in accordance with AASHTO TP9 (Figure 66). The asphalt portion of each core was cut into a cylinder with a length of 2 in. and a diameter of 6 in. and tested at 68°F and 0°F. The modulus at 0°F was taken as the reference value, and a master curve for each specimen was built by shifting the curves with a shift factor of aT. IDTs were conducted on 14 asphalt samples, representing 10 projects. Complex modulus plots are provided in the project portfolios (Appendix C). Hamburg Wheel Tracking Test Modified Hamburg wheel tracking tests were performed on asphalt cores to compare the performance of the underlying asphalt in accordance with AASHTO T 324-19 (Figure 67). Hamburg tests were run to only 1,000 passes for each sample, rather than the typical 10,000 passes, to reduce testing time. The 1,000 test cycles were determined sufficient to provide insight into those segments shown by deflection magnitude to exhibit more distress. The resulting magnitude of permanent deformation for each specimen is shown in Figure 68. None of the samples tested exceeded deflections of 0.30  in. CO SH-83A, CO SH-83B, IL CH-27, and PA SR-119 had the highest measured deflections. Comparisons of Hamburg max- imum deflection to total cracking from the visual distress surveys and to faultmeter measure- ments did not indicate strong correlations (R2 < 0.40). (a) (b) Figure 65. Testing equipment (a) and sample material with stainless-steel cylinder (b) for CTE measurement of cores.

80 Evaluation of Bonded Concrete Overlays on Asphalt Pavements Project ID Segment Core No. CTE (x 10-6 in./in./°F) CO I-70 Good 2 5.67 CO SH-83A Good 4 5.56 Poor 6 5.66 CO SH-83B Good 4 5.55 Poor 5 5.16 CO SH-121A Good 2 4.61 Poor 8 5.13 CO SH-121B Good 2 5.07 Poor 5 5.35 CO US-6 Good 2 5.05 Poor 6 4.61 IA US-71 Good 4 6.23 Poor 3 6.28 IL CH-27 Good 1 5.28 Poor 5 5.51 IL SR-53 Good 4 5.98 Poor 5 5.97 KS I-70 Good 4 5.99 Poor 5 5.71 LA US-167 Good 1 6.18 MN CSAH-7 Good 1 5.16 4 5.43 Poor 5 4.69 MN CSAH-22 Good 4 6.17 Poor 5 5.75 MN I-35 Good 1 6.32 MN TH-30 Good 1 5.83 Poor 6 5.78 PA SR-119 Good 4 6.05 Poor 6 6.13 Table 45. Measured CTE. Figure 66. IDT device.

Field Performance of Selected Projects 81   0.00 0.10 0.20 0.30 0.40 0.50 CO I-7 0 (C 1) CO I-7 0 (C 2) CO I-7 0 (C 3) CO I-7 0 (C 7) CO SH -8 3A (C 1) CO SH -8 3A (C 3) CO SH -8 3A (C 4) CO SH -8 3A (C 5) CO SH -8 3A (C 6) CO SH -8 3A (C 8) CO SH -8 3B (C 5) IA U S- 71 (C 1) IA U S- 71 (C 2) IA U S- 71 (C 3) IA U S- 71 (C 4) IL CH -2 7 (C 1) KS I-7 0 (C 1) LA SR -1 67 (C 8) LA SR -4 25 (C 1) M N C SA H- 22 (C 5) M N C SA H- 22 (C 6) M N C SA H- 22 (C 8) M N I- 35 (C 1) M N I- 35 (C 5) PA SR -1 19 (C 5) De fle cti on (in ch ) Project ID Maximum Deflection (inch) Average Deflection (inch) Figure 68. Permanent deformation of asphalt layers. (a) (b) Figure 67. Hamburg wheel testing device (a) and sample conguration (b).

82 Evaluation of Bonded Concrete Overlays on Asphalt Pavements Asphalt Bulk-Specific Gravity Bulk-specific gravity is an important characteristic for determining the optimum asphalt binder content in an asphalt mixture. To estimate a performance measure for the underlying asphalt layer, the asphalt bulk-specific gravity was determined on extracted cores. The bulk-specific gravity of each asphalt core specimen, previously cut into two for the Hamburg wheel test, was determined per AASHTO T 166-16 (Table 46). A comparison of asphalt bulk-specific gravity and BCOA performance (e.g., cracking, fault- ing) was conducted; however, no correlation appears to exist. Composite Concrete–Asphalt Shear Shear strength of the bonded concrete–asphalt cores was determined by performing a direct shear on the sample bond (Figure 69). Tests were conducted using a displacement control rate of 1 in. per minute up to a maximum displacement of 0.3 in. with the corresponding force mea- sured. The maximum (peak) shear force for each specimen was extracted from the shear load- displacement curves and used to calculate the shear strength of the bond. Table 47 summarizes the bond shear strength for each core sample tested and the failure mode of the concrete–asphalt core sample. In most cases, failure occurred at the bond itself (shown as “bond”). However, in some cases, failure began at the bond, but the crack eventually propagated through the asphalt (shown as “bond and cohesive”). In a few cases, failure occurred entirely in the asphalt layer (shown as “cohesive”). Table 46. Asphalt bulk-specific gravity. Project ID Segment Core No.a No. of Tests Bulk-Specific Gravity Absorption (%) Avg. SD Avg. SD CO I-70 Good 1 2 2.369 0.057 0.30 0.05 2 2 2.371 0.042 0.21 0.03 Poor 5 2 2.345 0.015 0.25 0.01 7 2 2.328 0.052 0.52 0.14 CO SH-83A Good 1 2 2.319 0.027 0.33 0.03 3 4 2.317 0.043 0.24 0.03 4 2 2.317 0.019 0.34 0.03 Poor 5 2 2.298 0.059 0.44 0.11 6 1 na na na na 8 3 2.314 0.025 0.24 0.06 CO SH-83B Poor 5 2 2.317 0.004 0.35 0.06 IA US-71 Good 1 2 2.287 0.016 0.41 0.04 2 2 2.261 0.013 0.37 0.02 3 2 2.314 0.006 0.34 0.06 4 2 2.315 0.027 0.36 0.04 Poor 5 2 2.259 0.040 0.47 0.07 6 1 na na na na 7 2 2.268 0.047 0.54 0.30 8 1 na na na na IL CH-27 Good 1 2 2.361 0.078 0.20 0.00 KS I-70 Good 1 2 2.163 0.012 1.07 0.11 LA US-167 Good 1 2 2.310 0.001 0.22 0.06 Poor 8 2 2.353 0.007 0.27 0.01 MN CSAH-22 Poor 5 2 2.293 0.043 0.28 0.01 6 2 2.348 0.063 0.36 0.11 8 2 2.283 0.049 0.48 0.28 MN I-35 Good 1 2 2.255 0.039 0.59 0.06 Poor 5 2 2.437 0.018 0.42 0.24 NOTE: na = not applicable. a Refer to Figure 59 and Figure 60 for core locations.

Field Performance of Selected Projects 83   (a) (b) Figure 69. Shear-strength testing device (a) and sample orientation (b). Project ID Segment Core No.a Max. Force (lb) Shear Strength (psi) Failure Mode CO I-70 Good 4 4,272 156 Bond and cohesive Poor 5 3,672 133 Bond 6 4,839 177 Bond 8 2,826 103 Bond CO SH-121B Good 1 4,811 176 Bond IL CH-27 Good 2 2,302 84 Bond and cohesive 4 1,540 56 Bond IL SR-53 Good 1 2,512 92 Bond and cohesive 2 3,174 116 Bond LA US-425 Poor 5 3,536 129 Bond 6 3,495 128 Bond MN TH-30 Good 2 1,048 38 Unconfined, sliding MO US-60 Good 3 2,603 95 Cohesive 4 3,702 135 Bond and cohesive Poor 5 2,324 85 Cohesive 7 2,387 87 Cohesive 8 4,862 178 Bond MT SR-16 Good 1 1,123 41 Bond PA SR-119 Poor 5 3,491 127 Cohesive 8 2,185 80 Bond and cohesive a Refer to Figure 59 and Figure 60 for core locations. Table 47. Bond shear strength.

84 Evaluation of Bonded Concrete Overlays on Asphalt Pavements Statistical Analysis of Laboratory Testing Results and BCOA Performance A screening effect test was conducted to determine the effect of laboratory testing results on BCOA performance. The results of the statistical evaluation, as summarized in Table 48, yielded the following conclusions: • Corner breaks: Subgrade liquid limit and plasticity index (PI) are significant factors. As the liquid limit and PI increase, corner breaks decrease. • Longitudinal cracking: Split tensile and compressive strength are significant. As split tensile strength increases, longitudinal cracking increases; however, as compressive strength increases, longitudinal cracking decreases. Results also showed that as the liquid limit and PI increase, longitudinal cracking decreases. • Transverse cracking: Split tensile strength and compressive strength are significant. As split tensile strength increases, transverse cracking decreases. As compressive strength increases, transverse cracking increases. • Total cracking: The analysis showed no statistical effect. • Longitudinal spalling: The analysis showed no statistical effect. • Transverse spalling: The analysis showed no statistical effect. • Patching: The analysis showed no statistical effect. Summary Project evaluations were conducted for each of the selected BCOA projects and included more than 175 mi each of automated distress and GPR surveys, nearly 24 mi of detailed visual distress surveys (in accordance with Miller and Bellinger 2014, the Distress Identification Manual for the Long-Term Pavement Performance Program), approximately 900 faultmeter tests, 1,000 ultra- sonic tomography tests, 3,900 FWD tests, 146 BCOA and 113 asphalt cores, and nearly 400 labo- ratory tests of concrete, asphalt, and unbound materials. The collected data were used to assess BCOA performance and to provide input values for the evaluation of BCOA design method results in comparison with as-built conditions. The following provides a summary of findings from the project site evaluations. Automated Distress Surveys Automated distress surveys were conducted on all 20 projects to determine IRI, faulting, and the percentage of slabs with corner breaks, longitudinal cracks, and transverse cracks. The results of the automated distress survey indicated that most segments were in good condition (based on NHPP), with minimal faulting and cracking. About half the segments (47%) had an Test p-Value Corner Breaks Longitudinal Cracking Transverse Cracking Longitudinal Spalling Transverse Spalling Patching Split tensile strength 0.62 0.00a 0.03a 0.55 0.85 0.56 Compressive strength 0.62 0.00a 0.03a 0.52 0.84 0.56 CTE 0.82 0.55 0.17 0.63 0.75 0.32 Asphalt–concrete shear bond 0.96 0.48 0.17 0.38 0.29 0.99 Hamburg wheel tracking test 0.10 0.59 0.31 0.26 0.40 0.90 Subgrade liquid limitb 0.49 0.08 0.58 0.93 0.68 0.09 Subgrade plasticity indexb 0.22 0.06 0.94 0.39 0.35 0.09 a Null hypothesis can be rejected; factor is statistically significant. b Analysis excludes projects with nonplastic soils. Table 48. Statistical analysis of laboratory tests and BCOA performance.

Field Performance of Selected Projects 85   IRI of 95 in./mi or less, 44% of segments had an IRI between 95 and 170 in./mi, and 9% of seg- ments had an IRI 170 in./mi or greater. Most all segments had faulting 0.10 in. or less (99% of segments). Furthermore, most segments had less than 5% of slabs with corner breaks (97% of segments), longitudinal cracking (84% segments), and transverse cracking (99% of segments). (Segments were of different ages and subjected to different traffic loadings, which likely accounts for some differences in performance.) In relation to slab size, the 4- × 4-ft slabs had the highest average IRI (181 in./mi), the highest average faulting (0.5 in.), the highest number of slabs with corner breaks (1.7%), and the highest number of transverse-cracked slabs (0.3%). The 6- × 6-ft slabs had the least distress and lowest IRI compared with the 4- × 4-ft and 12- × 12-ft slabs. The 12- × 12-ft slabs had the highest number of slabs with longitudinal cracking (16%). A statistical analysis was conducted using the automated distress survey results to determine whether pavement condition at intersection locations was different than at nonintersection locations. The results indicated that a significant difference exists between the performance of intersection and nonintersection locations. Specifically, intersection IRI and faulting were 36% higher and 17% higher, respectively, than in nonintersection locations. CO US-6 (12- × 12-ft slabs) and IL SR-53 (4- × 4-ft slabs) both had higher slab cracking at nonintersection locations than at intersections. Total cracking at intersection locations, removing CO US-6 and IL SR-53, was 3% versus 1% at nonintersection locations. Ground-Penetrating Radar Surveys GPR testing was conducted on all 20 projects, covering the same locations as the automated distress surveys. Analysis of GPR testing was conducted on the 0.10-mi good, fair, and poor segments selected for the detailed site evaluations. GPR-determined and core layer thickness were compared. BCOA layer thickness agreed between the two methods, with an average dif- ference between GPR and core thicknesses of only 2.5%. The average percentage difference for the asphalt layer thickness was significantly higher, with a nearly 40% difference between GPR- determined and core layer thickness. On the basis of a two-tailed t-test, 84% of the 0.10-mi seg- ments showed no statistical significance between GPR-determined and core-measured BCOA layer thickness, and 57% of the 0.10-mi segments showed no statistical difference between GPR- determined and core-measured asphalt layer thickness. Detailed On-Site Evaluations Detailed visual distress surveys were conducted using FHWA-accredited raters in accordance with the Distress Identification Manual for the Long-Term Pavement Performance Program (Miller and Bellinger 2014). Detailed visual distress surveys were conducted on all 0.10-mi good, fair, and poor segments on 19 projects (detailed site evaluations were not conducted on one project because of traffic control issues). Distress surveys were used to identify corner breaks, slab cracking, joint and crack spalling, joint seal damage, and other common BCOA distress types (e.g., slab migration). Predominant distress, regardless of project feature (e.g., age, layer thickness, slab size, joint sealing, synthetic macrofibers), included concrete patching, joint seal damage, map crack- ing, and longitudinal cracking. Three projects—IL SR-53 (4- × 4-ft slabs) and CO US-6 and MN TH-30 (12- × 12-ft slabs in service for 21 to 26 years, longest of all projects evaluated)—had the most distressed slabs compared with all other projects. Removing these projects resulted in low levels of distress for the remaining projects. For the 4- × 4-ft slabs, distress included trans- verse cracking (15% of slabs), longitudinal cracking (7% of slabs), and corner breaks (4% of

86 Evaluation of Bonded Concrete Overlays on Asphalt Pavements slabs). For the 6- × 6-ft slabs, distress included transverse cracking (2% of slabs) and longitudinal cracking (4% of slabs), but no corner breaks. The major distress for 12- × 12-ft slabs included longitudinal cracking (23% of slabs). Faultmeter tests were conducted at the FWD joint locations for 40 of the 0.10-mi good, fair, and poor segments. Faultmeter measurements ranged from 0 to 0.30 in., with an average of 0.04 in. and a standard deviation of 0.04 in. Average faultmeter measurements for the majority of 4- × 4-ft slabs, all 6- × 6-ft slabs, and most of the 12- × 12-ft slabs were less than 0.12 in. An analysis was conducted to determine whether a statistical significance exists between the auto- mated distress survey and the visual distress survey, specifically for faulting, corner breaks, and longitudinal, transverse, and total cracking. The paired t-test indicated a statistical difference exists between automated distress and visual distress collection methods in relation to faulting (93% difference), corner breaks (33% difference), transverse cracking (20% difference), and total cracking (26% difference). No statistical differences were found to exist with longitudinal crack- ing. In general, automated distress overestimates faulting and corner breaks and underestimates longitudinal, transverse, and total cracking. Although the methods were found to be statistically different, a linear correlation between the two does exist. To determine whether various features influence BCOA performance, several statistical analyses were conducted. A multifactor analysis was performed to test factors and interactions potentially affecting BCOA performance: slab size, in-service age, joint sealing, synthetic macro- fibers, ESALs, layer thickness, and slab size–BCOA thickness and BCOA–asphalt layer thick- ness interactions. From this analysis, for BCOA layer thicknesses greater than 6 in., increasing the asphalt layer thickness reduces the potential for faulting. Several factors, namely slab size, in-service age, use of synthetic macrofibers, ESALs, and the interaction of layer thicknesses and slab sizes, affect BCOA performance in relation to corner breaks. However, the number of corner breaks on the projects evaluated was minimal for all configurations. The use of synthetic macrofibers reduces the potential of spalling as in-service age increases. None of the evaluated factors influences longitudinal cracking, transverse cracking, total cracking, or transverse joint spalling. In-service age was the only factor that affected total spalling. The statistical analysis was further modified to account for differences in ESALs and in-service age by normalizing all projects to 20-year ESALs. In this analysis, only slab size, joint seal- ing, synthetic macrofibers, layer thicknesses, and slab size and layer thickness interactions were evaluated. In addition, because corner breaks were minimal, this distress was excluded from the analysis. The results of the normalized ESAL analysis indicated that slab size and layer thickness influence faulting, longitudinal cracking, transverse cracking, total cracking, and longitudinal joint spalling, whereas slab size influences transverse joint and total joint spalling. To further evaluate the effects of joint sealing and synthetic macrofibers, the normalized ESAL approach was used, but only these two factors were analyzed. Results indicated that joint seal- ing and synthetic macrofibers had no effect on performance for the projects evaluated. Ultrasonic Tomography Ultrasonic tomography tests were conducted with a MIRA device to determine pavement thickness and degree of bonding on three sets of five consecutive slabs on each 0.10-mi good, fair, and poor segment. The results of the ultrasonic tomography testing were summarized and com- pared with measured core layer thicknesses. Only ultrasonic tomography results in the vicinity of core locations were used in the comparison. The results of the statistical analysis indicated that ultrasonic tomography–determined BCOA layer thickness correlates well to core layer thickness. The standard ultrasonic tomography algorithm cannot reliably calculate the asphalt layer thickness. Therefore, identification of bonding condition using ultrasonic tomography requires

Field Performance of Selected Projects 87   extensive testing (i.e., numerous testing locations). Of the ultrasonic tomography tests con- ducted on the BCOA projects for this study, however, none appeared to indicate a poor bonding condition. Falling Weight Deflectometer Testing FWD tests were performed to determine LTE across transverse joints and to calculate the effective thickness for estimating the degree of bond between the BCOA and the asphalt layer. LTE for the majority of segments was 80% and greater; 9% of segments had LTE less than 80%, 66% of segments were between 80% and 90%, and 25% of segments had LTE higher than 90%. The primary benefit of calculating effective thickness is to assess bond condition without requiring core samples. Therefore, effective thickness was calculated and the results compared with the bond condition of the extracted cores. A statistical analysis determined that the bond condition was reasonably estimated on the basis of effective thickness for about 41% of the cores; however, the coring operation can cause separation of the bond, resulting in fewer false unbonded conditions than estimated. Coring, Dynamic Cone Penetrometer Testing, and Unbound Material Sampling Cores extracted from each good and poor segment were used to assess layer thickness and bond condition and then were shipped to a laboratory for further testing. When possible, DCP test- ing and unbound material sampling were also conducted. Results of the DCP testing were used to estimate the unbound layer thicknesses and in situ California bearing ratio values. Unbound material samples were extracted, bagged, and shipped to a laboratory for further testing. Laboratory Testing Laboratory tests were conducted on all concrete, asphalt, and unbound material samples extracted from the good and poor segments. Concrete testing included compressive and split tensile strength, CTE, and concrete–asphalt bond (conducted on intact cores). Asphalt test- ing included dynamic modulus (via IDT creep test) and the Hamburg wheel tracking test. Unbound samples were tested for the Atterberg limits, particle size distribution, and AASHTO soil classification. The majority of aggregate base and subgrade materials tested were classified as granular materials (AASHTO soil classification A-1 to A-3). Approximately half of the unbound materials were considered nonplastic, and materials identified as plastic had PIs ranging from 1% to 17%, with an average of 7% (standard deviation of 6%). Corrected concrete compressive strength and split tensile strength were determined on 58 cores from 17 projects in accordance with ASTM C39 and ASTM C496, respectively. Compressive strength for all cores tested ranged from 3,133 to 14,504 psi, with an average of 6,310 psi (standard deviation of 2,050 psi). Split tensile strength ranged from 276 to 812 psi, with an average of 447 psi (standard deviation of 100 psi). CTE tests were conducted in accordance with AASHTO T 336 on 30 cores, representing 16 projects. CTE results for all cores tested ranged from 4.6 to 6.3 × 10-6 in./in./°F, averaging 5.6 × 10-6 in./in./°F (standard deviation of 0.5 × 10-6 in./in./°F). IDTs were conducted in accordance with AASHTO TP9 on 14 asphalt samples representing 10 projects. IDT results were used to determine complex modulus. Complex modulus plots are included in the project portfolios (Appendix C).

88 Evaluation of Bonded Concrete Overlays on Asphalt Pavements To quantify the influence of the asphalt layer, Hamburg wheel testing (AASHTO T 324) was conducted on 25 asphalt samples representing 11 projects. Asphalt samples were subjected to 1,000 test cycles. A simple regression analysis did not indicate a strong correlation between maximum deflection and BCOA performance (total percentage of cracked slabs or faulting). Shear-strength tests of bonded concrete–asphalt cores were performed on 20 intact cores representing nine projects. Bond shear strength ranged from 38 to 178 psi and averaged 111 psi (standard deviation of 42 psi). Many of the laboratory testing results were used in the evaluation of the BCOA design methods. In addition, a statistical analysis indicated that liquid limit and PI are significant factors for corner breaks and longitudinal cracking, and that split tensile and compressive strength are significant factors for longitudinal and transverse cracking.

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The use of thin bonded concrete overlays on asphalt (BCOAs) as a rehabilitation treatment first gained momentum in the 1990s. Since the first documented thin BCOA application in the United States, in Louisville, Kentucky, in 1991, BCOAs have seen a dramatic increase in popularity.

The TRB National Cooperative Highway Research Program's NCHRP Research Report 1007: Evaluation of Bonded Concrete Overlays on Asphalt Pavements documents BCOA practices through a literature review and agency survey; documents performance through site investigations that assessed in-service design, construction, performance, preservation, and rehabilitation; and compares the results of current design methods with actual performance.

Supplemental to the report is NCHRP Web-Only Document 329: Bonded Concrete Overlays on Asphalt Pavements: Resources for Evaluation, which provides Appendices A through G of the contractor’s final report.

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