Performance-Related Specifications for Pavement Preservation Treatments (2017)

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47 The objective of this research was to develop comprehensive PRS guidelines and present examples to illustrate their application for select preservation treatments. This chapter describes the process for selecting these treatments and presents PRS guidelines for each of the treatments. 5.1 Treatment Identification and Selection Six preservation treatment types were identified for possible development of PRS guidelines and related examples based on the following: • State of the practice and common use by SHAs • Availability of data on initial material and construction quality characteristics and perfor- mance over time (for use in the empirical approach) • Known material and construction quality characteristics and performance measures (for use in the mechanistic-empirical approach) • Availability of test data during construction and performance (for use in the performance- based laboratory and field test approach) Three preservation treatments were identified for each pavement type. Also, three approaches were adopted for establishing relationships between quality characteristics and treatment per- formance for both pavement types: empirical, mechanistic-empirical, and performance-based laboratory and field test properties. Examples were presented to show how these three approaches can be used to establish rela- tionships between material and construction quality characteristics and performance. The examples illustrate the development of guidelines for three combinations of approaches and preservation treatments for each pavement type, as follows: Flexible pavements • Example 1: Empirical approach—microsurfacing • Example 2: Mechanistic-empirical approach—thin overlay • Example 3: Performance-based laboratory and field tests—chip seal Rigid pavements • Example 1: Empirical approach—joint resealing • Example 2: Mechanistic-empirical approach—diamond grinding • Example 3: Performance-based field tests—dowel-bar retrofit The appropriate selection of a preservation treatment and the corresponding design requires proper characterization of the pretreatment pavement condition. The pavement must be struc- turally sound, and the treatment must be applied at optimum time with respect to both distress Guidelines for Implementing PRS C h a p t e r 5

48 performance-related Specifications for pavement preservation treatments type and rate of deterioration in the existing pavement. Therefore, selection, timing, and location of a preservation treatment are the key components for its success (Peshkin and Hoerner 2005, Peshkin et al. 2004, Anderson et al. 2014). In this research, it was assumed that the existing condi- tions were considered and treatments were applied at the optimum timing (Tenison and Hanson 2009, Peshkin et al. 2004, Rada et al. 2013). Establishing relationships between material and construction quality characteristics and per- formance measures required various data attributes: identifying the most commonly used pres- ervation treatments for flexible and rigid pavements, establishing relationships between quality characteristics and performance measures of the selected treatments, determining the limits or boundaries for a particular quality characteristic based on observed or expected performance thresholds, and estimating the quality measures (e.g., PWL) based on the construction variabil- ity in the field (and estimating pay factor adjustments if required). 5.2 PRS Guidelines for Preservation Treatments The guidelines developed for each selected preservation treatment and related examples are presented in this section. Microsurfacing 1. Selection of preservation treatment Microsurfacing on flexible pavements is an application of a mixture of polymer-modified emulsified asphalt, mineral aggregate, mineral filler, water, and additives over the entire pave- ment surface (thin layer). Typically the treatment is used to inhibit raveling, weathering, asphalt aging and hardening, bleeding, moisture infiltration, minor surface irregularities, and to improve surface friction (Gransberg 2010). Performance measures such as surface friction and texture, cracking, rutting, raveling, bleeding, and stripping can be used to evaluate the effectiveness of microsurfacing (Henry 2000). 2. Select candidate material and construction characteristics In order to capture the change in surface irregularities, the mean profile depth (MPD) can be selected as an AQC because it can be measured just after treatment application in the field using NDT methods. Surface friction number (FN) can be designated as a performance indicator. However, other material and construction-related aspects may be considered to enhance the treatment effectiveness. Such design and construction aspects include • Emulsion type (e.g., based on climatic conditions) • Aggregate types and properties • Fillers and other additives (e.g., use of fine materials as “mixing aids” to improve workability and reduce curing time) • Material application rates 3. Establish AQC-performance relationships and set specification limits The relationship between the change in MPD and SLE due to a change in friction number is considered as an example. MPD and FN lower limits of 0.6 and 40, respectively, are chosen based on information reported in the literature. An empirical relationship of AQC to expected performance can be used if data are available. The relationship between MPD and FN shown in Equation 5-1 and the simulated MPD deterioration over time were used in these guidelines (Rajaei et al. 2014, Henry et al. 2000).

Guidelines for Implementing prS 49 30.62ln 54.912 (Eq. 5-1)FN CTMMPD( )= + where, CTMMPD = Mean profile depth measured by circular track meter (CTM) Agency practice for acceptable FN typically has ranged from 30 to 45; a value of 40 was chosen as the lower threshold associated with an MPD measurement of 0.6 (Rajaei et al. 2014). 4. Determine limits for AQC and quality measures A quality measure DPWL can be selected while AQL and RQL selection is based on pay equa- tion, SLE, and risk assessment. PWL is often used as a quality measure in pavement construc- tion practices. However, for preservation treatments, a modified version of PWL can be used to reflect a change in pavement quality due to a treatment, i.e., DPWL (PWL after treatment minus PWL before treatment). Such a quality measure is more appropriate for pavement preservation practices given that the goal is to extend the life of the existing pavement. However, a lower AQC (MPD in this case) limit needs to be established for before-and-after treatment PWL calcula- tions. AQL and RQL limits are subjective decisions based on the party setting specification limits. Although there are typical ranges for AQL (e.g., 90 to 95) and RQL (e.g., 60), these values can vary based on the corresponding pay adjustments, SLE, and risk analysis. However, AQL and RQL should reflect appropriate pay (i.e., 100% pay at AQL, justified disincentive between RQL and AQL, and corrective action below RQL). 5. Specify AQC measurement methods Well-established standards for measuring and evaluating surface friction and texture are available (Henry 2000, Rajaei et al. 2014, Henry et al. 2000); these should be used for specifying AQC measurement methods. 6. Establish a sampling and measurement plan Evaluation of surface texture requires a pass of conventional surface texture measuring devices along a pavement length. The following process may be used for establishing a sampling and measurement plan: • Identify the party performing acceptance testing. • Select an acceptance sampling plan type. Either a variable acceptance plan or a stratified sam- pling method are ideal to assess pay adjustments for varying levels of quality. • Develop verification sampling and testing procedures. The decision to use split or indepen- dent sampling techniques is related to the goals of the agency and on the AQC measurement methods. In practice, the agency’s verification test methods are used solely for verification, and the acceptance methods proposed by the contractor must be compared to the results of agency verification testing. • Select a verification sampling frequency. The verification sampling frequency should be approximately 10% of the acceptance sampling rate of the contractor. In practice, the frequency of verification sampling is selected based on economic, rather than statistical, reasons. • Determine a lot and sample size. The risks associated with incorrectly accepting or rejecting lot quality are related to the sample size which depends on the treatment type and AQC. All the data obtained from the continuous MPD data collection for a lot can be used in estimating PWL, and a minimum of five data points should be used to calculate PWL (i.e., a lot should be divided into a minimum of five sublots and one MPD value from each sublot). A lot size of 0.1 mile would provide a minimum of five average MPD values for calculating PWL.

50 performance-related Specifications for pavement preservation treatments 7. Select and evaluate quality measurement methods Using a quality measure, such as PWL, evaluate the PWL of each lot based on the specified AQC limits. The PWL of the entire lot from a project can then be related to improvement in pavement performance (SLE) to justify pay adjustments. 8. Develop pay adjustment factors for incentives and disincentives and assess risk Predict pavement performance as a function of quality levels in terms of DPWL. Convert the expected performance (SLE) into pay adjustments. Adjust AQL and RQL and pay relationships to minimize risk and ensure appropriate pay. The following steps can be used: • Relate DPWL (determined in Step 7) to SLE distribution (determined in Step 3). • Determine the pay adjustment factor based on LCC analysis. • Develop an EP curve that relates the pay factors to SLE due to treatment (and awards full pay at AQL). • Develop an operating characteristic (OC) curve that provides the probability of awarding a pay factor greater than 1 at AQL close to 50%. Thin Overlay 1. Selection of a preservation treatment The thin functional overlay typically used for flexible pavements as a preservation treatment involves the application of a thin layer of HMA to remove minor surface distresses and improve ride quality. Performance measures associated with thin overlays include cracking, rutting, and surface roughness. 2. Select candidate material and construction characteristics Several material and construction properties, such as layer thickness, asphalt mix volumetrics (binder content, air voids, VFA, and VMA), and field density, can be used as AQCs. However, because thin overlays are generally used to improve the functional performance of an exist- ing pavement, IRI which captures variation in vertical surface elevations and change in surface roughness can be used as an AQC to evaluate the quality of construction (i.e., smoothness after thin overlay application). 3. Establish AQC-performance relationships and set specification limits The relationship between change in IRI and SLE can be established by using the mechanistic- empirical pavement design guide (MEPDG) performance prediction models. Smooth thin overlay will reduce surface roughness and exhibit a low IRI. A smoother pavement surface results in less vehicle body and axle bounce, thereby reducing dynamic load damage and increasing pavement SLE. The mechanistic-empirical approach can be used to (1) measure before-and-after treatment surface profiles, (2) estimate dynamic load index (DLI) from pro- files based on Figure 5-1, (3) estimate relative damage based on DLI or IRI before and after the treatment using Equation 5-2 (regression parameters for the equation are listed in Table 5-1), and (4) calculate the life extension based on the change in relative damage using Equation 5-3. Relative damage 1 (Eq. 5-2)3 2a DLI b DLI c DLI( ) ( ) ( )= + + + Life extension (Eq. 5-3)R R RSLo( )= −

Guidelines for Implementing prS 51 where R is defined as follows: 100 1 1 Relative damage (Eq. 5-4)R = −  4. Determine limits for AQC and quality measures A quality measure, DPWL, can be selected while AQL and RQL selection is based on pay equa- tion, SLE, and risk assessment. Percent within limits (PWL) is often used as a quality measure in pavement construction practice. However, for preservation treatments, a modified version of PWL can be used to reflect a change in pavement quality due to a treatment, i.e., DPWL (PWL after treatment minus PWL before treatment). Such a quality measure is more appropriate for pavement preservation practices, given that the goal is to extend the life of the existing pavement. However, an upper AQC (IRI in this case) limit needs to be established for before-and-after treatment PWL calculations. AQL and RQL limits are subjective decisions based on the party Read original Profile Transfer profile into wavelength (frequency) domain by Fast Fourier Transform (FFT) Split transferred profile into two profiles that have different wavelength (frequency) ranges: * Profile 1 : 6.71-18 m or 22-59 ft(1.5-4 Hz at the speed of 96.6 km/h or 60 mph) * Profile 2 : 1.83-3.36 m or 6-11 ft(8-15 Hz at the speed of 96.6 km/h or 60 mph) Transfer profile 1 and 2 into space domain by Inverse Fast Fourier Transform (IFFT) Calculate variances from profile 1 and 2 Calculate DLI Figure 5-1. Procedure for determination of DLI from surface profile (Lee et al. 2002, Chatti and Lee 2002). Pavement type a b c R2 Rigid 2.81E-4 -6.75E-3 1.16E-1 0.954 Composite -2.52E-5 2.63E-3 5.31E-2 0.914 Flexible 2.67E-4 -5.81E-3 1.09E-1 0.932 Table 5-1. Example of regression parameters for Equation 5-2 (Chatti et al. 2001).

52 performance-related Specifications for pavement preservation treatments setting specification limits. Although there are typical ranges, e.g., 90 to 95 AQL and 60 RQL, these can vary based on the corresponding pay adjustments, SLE, and risk analysis. However, AQL and RQL should reflect appropriate pay (i.e., 100% pay at AQL, justified disincentive between RQL and AQL, and corrective action below RQL). 5. Specify AQC measurement methods A standard for measuring and evaluating surface roughness in terms of IRI (AASHTO PP37-04) is available and is recommended for measuring the longitudinal profile and calculating IRI (AASHTO 2010). 6. Establish a sampling and measurement plan Evaluation of longitudinal profile requires a pass of conventional profile-measuring devices along a project length in different wheel-paths. The following process may be used for establishing the sampling and measurement plan: • Identify the party performing acceptance testing. • Select an acceptance sampling plan type. A variable acceptance plan and stratified sampling method are ideal to award pay adjustments for varying levels of quality. • Develop verification sampling and testing procedures. The decision to use split or indepen- dent sampling techniques is related to the goals of the agency and on the AQC measurement methods. In practice, the agency’s verification test methods are used solely for verification, and the acceptance methods proposed by the contractor must be compared to the results of agency verification testing. • Select a verification sampling frequency. The verification sampling frequency should be approximately 10% of the acceptance sampling rate of the contractor. In practice, the frequency of verification sampling is selected based on economic, rather than statistical, reasons. • Determine a lot and sample size. The risks associated with incorrectly accepting or rejecting lot quality is related to the sample size which depends on the treatment type and AQC. All the data obtained from the continuous IRI data collection for a lot can be used in estimating PWL, and a minimum of five data points should be used to calculate PWL (i.e., a lot should be divided into a minimum of five sublots and one IRI value from each sublot). A lot size of 0.1 mile would provide a minimum of five average IRI values for calculating PWL. 7. Select and evaluate quality measurement methods Using a quality measure such as PWL, evaluate the PWL of each lot based on the previously specified AQC limits. The PWL of the entire lot from a project can then be related to improve- ment in pavement performance (SLE) to justify pay adjustments. 8. Develop pay adjustment factors for incentives and disincentives and assess risk Predict pavement performance as a function of quality levels in terms of DPWL. Convert the expected performance (i.e., SLE) into a pay adjustment. Adjust AQL and RQL and pay relation- ships to minimize risk and ensure appropriate pay. The following steps can be used: • Relate DPWL (determined in Step 7) to SLE distribution (determined in Step 3). • Determine the pay adjustment factor based on LCC analysis. • Develop an EP curve that relates the pay factors to SLE due to treatment (and awards full pay at AQL). • Develop an operating characteristic (OC) curve that provides the probability of awarding a pay factor greater than 1 at AQL close to 50%.

Guidelines for Implementing prS 53 Chip Seal 1. Selection of a preservation treatment Chip seals are typically used as preservation treatments for flexible pavements. This method involves the application of asphalt (typically an emulsion) to the pavement surface, followed by the application of rolled aggregate chips. Generally, chip seals are applied to seal longitudinal, transverse, and block cracking; inhibit and retard raveling/weathering; improve friction; improve ride quality; and/or inhibit moisture infiltration. Typical performance measures for chip seals are aggregate loss (raveling), stripping, bleeding, and flushing. 2. Select candidate material and construction characteristics Several material and construction properties such as emulsions and aggregate application rates, variability between design and target application rates, emulsion-aggregate adhesive strength, aggregate gradation, embedment depth, and mean profile depth (MPD) can be used as AQCs. 3. Establish AQC-performance relationships and set specification limits Establishing AQCs/performance relationships is a critical step in developing the preservation PRS framework and establishing the suitability of guidelines for the PRS. This task establishes relationships between the AQCs and pavement performance for a specific preservation treatment, (i.e., a chip seal). In developing these relationships, certain ranges of a particular performance measure are correlated to the threshold value of the selected AQC by analyzing performance- related trends in historical data obtained from existing projects, establishing relationships between AQCs and performance measures, or applying engineering judgment and statistical analyses. 4. Determine limits for AQC and quality measures Once the relationships between candidate AQCs and performance measures are established for chip seal treatments, and the methods for measuring the AQCs are identified, the limits or thresholds of the AQCs for acceptable levels of performance can be determined. Each of the AQCs for chip seal treatments only requires either an upper or lower limit. A quality measure PWL can be used after the treatment application. AQL and RQL limits are subjective decisions based on the party setting specification limits. Although there are typical ranges (e.g., 90 to 95 AQL and 60 RQL), these can vary based on the pay adjustment level. However, AQL and RQL should reflect appropriate pay disincentives or corrective action. 5. Specify AQC measurement methods The successful adoption of a PRS requires the use of an objective test method for measuring performance-related parameters. Methods that provide quantitative results are preferred. The process of specifying test methods will consider the effect on user delays, the duration of collect- ing and processing data, and the use of NDT techniques. Two problems could be encountered in the selection of a test method: (1) the use of less- proven methods that may be deemed undesirable by a contractor unfamiliar with the associated calibration and analysis procedures and (2) the subjectivity of manual measurement methods in comparison to automated data collection methods. These potential problems should be con- sidered as part of the overall performance-based strategy, and the methods employed must be agreed upon by both the agency and contractor. The requirements of such a test method are discussed in this section. 6. Establish a sampling and measurement plan The PRS provided herein should be supplemented by a sampling plan that balances efficiency with contractor and agency risks. For example, an overly extensive sampling plan may result in

54 performance-related Specifications for pavement preservation treatments less risk to the parties involved, but may accrue higher project and user costs. Therefore, the plan should be tailored to the type of parameter being tested, the resources available to the agency, and the goal of the project delivery approach unique to each project. However, certain statistical sampling concepts, such as sample size, lot size, and sampling frequency, are recurrent, regardless of project needs. The sampling and testing frequency depends on specific project goals and needs and can be specified locally. For example, a chip seal constructed on a high-traffic-volume arterial roadway may require more frequent testing than a chip seal constructed on a low-volume roadway. 7. Select and evaluate quality measurement methods Using the quality measure PWL, evaluate the PWL of each lot, based on the previously speci- fied AQCs and their limits. The PWL of the entire lot from a project can then be related to improvement in the quality to justify pay adjustments. 8. Develop pay adjustment factors for incentives and disincentives and assess risk (if desired) Pay adjustment factors are often part of acceptance plans and PRS guidelines. However, pay reduction factors derived from reduction of service life concepts is not appropriate for perfor- mance measures such as aggregate loss, which is the most critical distress for chip seal treatments (Lee 2007). For instance, most aggregate loss occurs within the first days or weeks in service, and aggregate loss early in the life of the seal does not necessarily lead to a reduction in the service life of the seal (Im 2013). Therefore, pavement maintenance practitioners with state highway agencies can often provide recommendations for pay adjustment factors as a starting point; these recommendations can be evaluated prior to implementation. Joint Resealing 1. Selection of a preservation treatment Sealant materials on concrete pavement joints or cracks are applied to reduce moisture infil- tration and prevent intrusion of incompressible fines. Performance measures associated with joint seals include cracking, pumping, faulting, and spalling. 2. Select candidate material and construction characteristics The material properties of sealants influence cohesion and adhesion failures at a joint and joint seal performance effectiveness over time. Joint seal effectiveness is a measure of how much percent- age of the sealant can prevent the infiltration of water and fines. Therefore, the percent effective joints based on overall joint seal effectiveness (%Leff-total) for a pavement section can be used as an AQC (Smith et al. 1999, FHWA 2003, Darter et al. 1985, Biel and Lee 1997, Evans et al. 1999). 3. Establish AQC-performance relationships and set specification limits A relationship between change in percent joint seal effectiveness (%Leff-total) and SLE due to faulting can be considered for developing the PRS guidelines (Evans et al. 1999). A lower limit of 50% overall joint seal effectiveness is selected. A joint is considered effective if at least 75% of a joint is sealed. FHWA recommends a minimum allowable value of 50% of effective joints (over- all joint effectiveness) in a pavement section before requiring joint resealing (Evans et al. 1999). 4. Determine limits for AQC and quality measures A quality measure, DPWL, can be selected, while AQL and RQL selection is based on pay equa- tion, SLE, and risk assessment. Frequently, PWL is used as a quality measure in pavement con- struction practice. However, for preservation treatments, DPWL (PWL after treatment minus PWL before treatment) can be used to reflect a change in pavement quality due to a treatment.

Guidelines for Implementing prS 55 A lower AQC (%Leff-total in this case) limit needs to be established for before-and-after treatment PWL calculations. AQL and RQL limits are subjective decisions and typical ranges (e.g., 90 to 95 AQL and 60 RQL) can vary based on the corresponding pay adjustments, SLE, and risk analysis. However, AQL and RQL should award appropriate pay (i.e., 100% pay at AQL, justified dis- incentive between RQL and AQL, and corrective action below RQL). 5. Specify AQC measurement methods The FHWA Manual of Practice (Evans et al. 1999) for repair of joint reseals in PCC pavements may be used as a guide; it provides well-established means for measuring and evaluating joint effectiveness. 6. Establish a sampling and measurement plan Evaluation of joint seals requires visual inspection along a project length in different wheel- paths. The following steps are required for developing the sampling and measurement plan: • Identify the party (agency, contractor, or consultant) performing acceptance testing. • Select an acceptance sampling plan type (a variable acceptance plan and stratified sampling method are ideal to award pay adjustments for varying levels of quality). • Develop verification sampling and testing procedures. The decision to use split or indepen- dent sampling techniques is related to the goals of the agency and on the AQC measurement methods. In practice, the agency’s verification test methods are used solely for verification, and the acceptance methods proposed by the contractor must be compared to the results of agency verification testing. • Select a verification sampling frequency. The verification sampling frequency should be approximately 10% of the acceptance sampling rate of the contractor. In practice, the fre- quency of verification sampling is selected based on economic, rather than statistical reasons. • Determine the lot and sample size. The risks associated with incorrectly accepting or rejecting the lot quality are related to the sample size, which depends on the treatment type and AQC. All the data obtained for joint seal effectiveness is based on visual inspection of all the joints in a lot and can be used in estimating PWL. Typically, the joint spacing of 15 ft is used for JPCP, which means that there will be about 36 joints in a 0.1-mile pavement segment. A minimum of five data points should be used to calculate PWL (i.e., a lot should be divided into a mini- mum of five sublots and one %Leff-total value from each sublot, which means about seven joints per sublot). A lot size of 0.1 mile could provide a minimum of five average %Leff-total values for calculating PWL. 7. Select and evaluate quality measurement methods Using a quality measure such as PWL, evaluate the PWL of each lot based on the specified AQC limits. The PWL of the entire lot from a project can then be related to improvement in pavement performance (SLE) to justify pay adjustments. 8. Develop pay adjustment factors for incentives and disincentives and assess risk Predict pavement performance as a function of levels of quality. Convert the expected perfor- mance (i.e., SLE) into a pay adjustment. Adjust AQL and RQL and pay relationships to minimize risk and ensure appropriate pay. The following steps can be used: • Relate DPWL (determined in Step 7) to the SLE distribution (determined in Step 3). • Determine the pay adjustment factor based on LCC analysis. • Develop an EP curve that relates the pay factors to SLE due to the treatment (and awards full pay at AQL).

56 performance-related Specifications for pavement preservation treatments • Develop an operating characteristic (OC) curve that provides the probability of awarding a pay factor greater than 1 at AQL close to 50%. Diamond Grinding 1. Selection of a preservation treatment Diamond grinding is typically used for rigid pavements as a preservation treatment. It involves removal of a thin layer of PCC using stacked diamond-tipped cutting blades. Performance measures associated with diamond grinding include cracking, surface roughness, and faulting. 2. Select candidate material and construction characteristics Diamond grinding is performed to improve pavement smoothness by eliminating the surface undulations. IRI captures variation in vertical surface elevations along the pavement length. Hence IRI can be selected as an AQC. The effectiveness of diamond grinding can be assessed by evaluating the IRI before and after the treatment. 3. Establish AQC-performance relationships and set specification limits The relationship between a change in IRI and SLE can be established by using the Pavement- ME performance prediction models. A successful grinding treatment will reduce surface rough- ness, as indicated by reduced IRI after treatment. A smoother pavement surface results in less vehicle body and axle bounce, reducing dynamic load-related damage. It can be hypothesized that a reduced dynamic load should result in increased pavement SLE. The mechanistic-empirical approach can be used to (1) measure before-and-after treatment surface profiles, (2) estimate dynamic load index (DLI) from profiles based on Figure 5-1, (3) estimate relative damage based on DLI or IRI before and after the treatment; for example, the relative damage based on DLI can be calculated by using Equation 4-2 and Table 5-1, and (4) calculate the life extension based on the change in relative damage using Equations 4-3 and 4-4. 4. Determine limits for AQC and quality measures A quality measure, DPWL, can be selected while AQL and RQL selection is based on pay equa- tion, SLE, and risks. Commonly, PWL is used as a quality measure in pavement construction practice. However, for preservation treatments, DPWL (PWL after treatment minus PWL before treatment) can be used to reflect a change in pavement quality due to a treatment. An upper AQC (IRI in this case) limit needs to be established for before-and-after treatment PWL calcula- tions. AQL and RQL limits are subjective decisions and typical ranges for AQL (e.g., 90 to 95) and RQL (e.g., 60) can vary as a function of the corresponding pay adjustment, SLE, and risks. However, AQL and RQL should assess appropriate pay (i.e., 100% pay at AQL, justified dis- incentive between RQL and AQL, and corrective action below RQL). 5. Specify AQC measurement methods A standard for measuring and evaluating surface roughness in terms of IRI (AASHTO PP37-04) is available and recommended for measuring the longitudinal profile and calculating IRI (AASHTO 2010). 6. Establish a sampling and measurement plan Evaluation of longitudinal profile requires a pass of conventional profile-measuring devices along a project length in different wheel paths. The following process may be used for establish- ing the sampling and measurement plan:

Guidelines for Implementing prS 57 • Identify the party performing acceptance testing. • Select an acceptance sampling plan type. A variable acceptance plan and stratified sampling method are ideal to award pay adjustments for varying levels of quality. • Develop verification sampling and testing procedures. The decision to use split or indepen- dent sampling techniques is related to the goals of the agency and on the AQC measurement methods. In practice, the agency’s verification test methods are used solely for verification, and the acceptance methods proposed by the contractor must be compared to the results of agency verification testing. • Select a verification sampling frequency. The verification sampling frequency should be approximately 10% of the acceptance sampling rate of the contractor. In practice, the fre- quency of verification sampling is selected based on economic, rather than statistical, reasons. • Determine a lot and sample size. The risks associated with incorrectly accepting or rejecting lot quality are related to the sample size, which depends on the treatment type and AQC. All the data obtained from the continuous IRI data collection for a lot can be used in estimating PWL, and a minimum of five data points should be used to calculate PWL (i.e., a lot should be divided into a minimum of five sublots and one IRI value from each sublot). A lot size of 0.1 mile could provide a minimum of five average IRI values for calculating PWL. 7. Select and evaluate quality measurement methods Using PWL as a quality measure, evaluate the PWL of each lot based on the specified AQC limits. The PWL of the entire lot from a project can then be related to improvement in pavement performance (SLE) to justify pay adjustments. 8. Develop pay adjustment factors for incentives and disincentives and assess risk Predict pavement performance as a function of levels of quality. Convert the expected perfor- mance (i.e., SLE) into a pay adjustment. Adjust AQL and RQL and pay relationships to minimize risk and ensure appropriate pay. The following steps can be used: • Relate DPWL (determined in Step 7) to SLE distribution (determined in Step 3). • Determine the pay adjustment factor based on LCC analysis. • Develop an EP curve that relates the pay factors to SLE due to treatment and awards full payment at AQL. • Develop an operating characteristic (OC) curve that provides the probability of awarding a pay factor greater than 1 at AQL close to 50%. Dowel-Bar Retrofit 1. Selection of a preservation treatment Dowel-bar retrofit (DBR) typically is used for rigid pavements as a preservation treatment for load-transfer restoration across a rigid pavement discontinuity. Performance measures associ- ated with DBR include joint faulting, pumping, and corner breaks. 2. Select candidate material and construction characteristics While material characteristics such as mortar properties are relevant to the effectiveness of the DBR, the ability to restore load transfer is critical to a successful application and effectiveness of the treatment. Load-transfer efficiency (LTE) across a discontinuity is representative of the material and construction characteristics (e.g., strength properties of mortar and alignment of dowel bars) and can be used as an AQC. Faulting can be the primary performance measure, given that it is the direct result of the pumping distress mechanisms that can occur when load transfer is poor.

58 performance-related Specifications for pavement preservation treatments 3. Establish AQC-performance relationships and set specification limits The faulting model developed for the Pavement-ME can be used to establish a relationship between changes in LTE due to DBR and predicted faulting performance. The differential energy (DE) is a key component of the Pavement-ME faulting model. LTE and corresponding DE at a joint can be calculated by using deflection measurements. The measured DE can be used as inputs to the Pavement-ME faulting model to predict faulting to compare with measured fault- ing. If necessary and data representative of local conditions is available, calibrate the faulting model and develop a relationship between DE and LTE. Establish a relationship between DLTE and SLE to justify pay adjustment relationships. A 10-year study on DBRs showed that pavements with retrofitted dowel bars retained an aver- age joint load transfer between 70 and 90% (Pierce et al. 2003). A one-sided lower specification limit of 70% LTE can be selected, but this can vary per agency choice. 4. Determine limits for AQC and quality measures A quality measure, DPWL, can be selected while AQL and RQL selection is based on pay equa- tion, SLE, and risk assessment. PWL is often used as a quality measure in pavement construc- tion practice. However, for preservation treatments, a modified version of PWL can be used to reflect a change in pavement quality due to a treatment, i.e., DPWL (PWL after treatment minus PWL before treatment). Such a quality measure is more appropriate for pavement preservation practice, given that the goal is to extend the life of the existing pavement. However, a lower AQC (LTE in this case) limit needs to be established for before-and-after treatment PWL calculations. AQL and RQL limits are subjective decisions based on the party setting the specification limits. Although there are typical ranges for AQL (e.g., 90 to 95) and RQL (e.g., 60), these values can vary based on the corresponding pay adjustments, SLE, and risk analysis. However, AQL and RQL should reflect appropriate pay (i.e., 100% pay at AQL, a justified disincentive between RQL and AQL, and corrective action below RQL). 5. Specify AQC measurement methods A well-established standard (ASTM D4695-03) is available and can be used for measuring and evaluating surface deflections (ASTM 2015). 6. Establish a sampling and measurement plan The LTE is measured across a discontinuity using falling weight deflectometer (FWD) deflec- tion data along a project length in different wheel paths. The following process may be used for establishing the sampling and measurement plan. • Identify the party performing acceptance testing. • Select an acceptance sampling plan type (a variable acceptance plan and stratified sampling method are ideal for awarding pay adjustments for varying levels of quality). • Develop verification sampling and testing procedures. The decision to use split or indepen- dent sampling techniques is related to the goals of the agency and on the AQC measurement methods. In practice, the agency’s verification test methods are used solely for verification, and the acceptance methods proposed by the contractor must be compared to the results of agency verification testing. • Select a verification sampling frequency. The verification sampling frequency should be approx- imately 10% of the acceptance sampling rate of the contractor. In practice, the frequency of verification sampling is selected based on economic, rather than statistical, reasons. • Determine a lot and sample size. The risks associated with incorrectly accepting or rejecting lot quality are related to the sample size, which depends on the treatment type and AQC. Since the data collection method for DBR effectiveness is based on deflection testing, all the joints in

Guidelines for Implementing prS 59 a lot can be used for estimating PWL. Typically, joint spacing of 15 ft is used for JPCP, which means there will be about 36 joints in a 0.1-mile pavement segment. Therefore, it is recom- mended that a lot size should be 0.1 mile such that LTE values from all the joints are used to calculate PWL. A minimum of five LTE values should be used for calculating the PWL of a lot. 7. Select and evaluate quality measurement methods Using a quality measure such as PWL, evaluate the PWL of each lot based on the specified AQC limits. The PWL of the entire set of samples from the project can then be related to improvement in pavement performance (i.e., SLE) to justify pay adjustments. 8. Develop pay adjustment factors for incentives and disincentives and assess risk Predict pavement performance as a function of quality levels in terms of DPWL. Convert the expected performance (i.e., SLE) into a pay adjustment. Adjust AQL and RQL and pay relation- ships to minimize risks and ensure appropriate pay. The following steps can be used: • Relate DPWL (determined in Step 7) to SLE distribution (determined in Step 3). • Determine the pay adjustment factor based on LCC analysis. • Develop an EP curve that relates the pay factors to SLE due to the treatment (and awards full pay at AQL). • Develop an operating characteristic (OC) curve that provides the probability of awarding a pay factor greater than 1 at an AQL close to 50%.