Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
The inventory of pavement infrastructure is the basic build- ing block of an APMS. Because pavements deteriorate with time, the inventory includes past and current condition of pavements and anticipates future condition. This chapter pro- vides a brief description of the main features of pavement inventory and procedures used for the assessment of pavement condition. Evaluation procedures are described for pave- ment surface distresses, roughness, friction, and pavement deflection testing. With the exception of a few small airports, all airports surveyed carry out periodic pavement condition surveys of runways using the Pavement Condition Index (PCI), with an average survey frequency of 3.4 years. PAVEMENT INVENTORY The documentation of pavement inventory is a prerequisite for a systematic pavement condition evaluation and the selec- tion of M&R treatments on the network level. On the project level, pavement inventory data are essential for the design of M&R treatments. The inventory includes the size and main characteristics of pavement assets and their condition. Prefer- ably, pavement inventory is viewed and organized as part of an airport asset inventory. The U.S.DOT developed the Data Integration Primer (2001), which explains principles and options for developing integrated asset management databases. There is also the ASTM Standard E177-96, Standard Guide for Prioritization of Data Needs for Pavement Management (ASTM 2002). A pavement inventory divides the airport pavement net- work into homogeneous pavement sections with the same pavement structure and a similar pavement condition through- out. A pavement section is the basic building block for pave- ment inventory. It is also a basic unit for pavement preserva- tion decision making. An M&R project can be carried out on a single pavement section. In other words, a section is estab- lished as a ârepair unitââa portion of the network that can be managed and repaired independently from other sections (Tighe and Covalt 2008). The pavement network is typically divided into four lev- els according to specifications given in ASTM Standard D 5340 (2003) or in FAA Advisory Circular on Guidelines and Procedures for Maintenance of Airport Pavements (2007): 1. Networkârepresents the entire pavement infrastruc- ture managed by the airport authority. 12 2. Branchâa part of the network that serves a specific purpose. Typical branches are runways, taxiways, aprons or ramps, and airside pavements; for example, each airport runway is considered to be a branch. 3. Sectionâa part of a branch that has a uniform pave- ment structure (and construction and maintenance history), traffic loads, and pavement condition. It is the basic repair unit. 4. Sample unitsâa part of a section created to carry out pavement condition surveys based on the ASTM standard. The maximum size of the sampling unit for AC and PCC pavements is specified in the standard. Data storage and retrieval is facilitated by APMS software such as MicroPAVER (2003). As a minimum, the pavement inventory data for each section includes the following: ⢠Section identificationâfunctional class (branch) and dimensions of the pavement section. ⢠Location of the sectionâfor example, within the branch, keel, or outer wings. ⢠Pavement structureâdate of the original construction and the description of pavement structure. The descrip- tion includes thickness and basic material properties of all layers, both the original layers and the subsequent changes. ⢠Subgrade and drainage characteristicsâsubgrade type and the presence of subdrains and edge drains. ⢠Maintenance historyâtypes and dates of subsequent pavement M&R treatments, including the age of a current pavement surface. ⢠Pavement condition dataâincludes past and current data. ⢠Traffic dataânumber of aircraft operations and type of aircraft. Pavement inventory data are stored in an APMS database, such as MicroPAVER, that has the capability to graphically display archived data. PAVEMENT EVALUATION PRINCIPLES APMS pavement evaluation includes field measurements of the current state of pavement characteristics and recording them for future use. It encompasses the evaluation of pavement surface distresses, roughness, friction, and pavement strength. The main principles of airport pavement evaluation include: CHAPTER THREE PAVEMENT INVENTORY AND EVALUATION
13 ⢠Objectivity and consistencyâObjective and consis- tent pavement evaluation produces true trends and pro- vides reliable data for pavement investment decisions. Objectivity and consistency of repeated evaluations enables airport owners to see how the pavement condi- tions change over the years. They also enable funding agencies to compare pavement conditions of different airports within and outside their jurisdiction. ⢠Timelines and relevancyâPavement evaluations sup- port planning and budgeting cycles and provide data for timely implementation of pavement preservation treat- ments, particularly preventive maintenance treatments. ⢠Long-term monitoringâHistorical pavement perfor- mance data from repeated evaluations are vital for the development of pavement performance models used to estimate when M&R treatments will be needed. Long- term monitoring data also enables evaluation of past performance of pavement preservation treatments. ⢠Cost-effectivenessâCollection of pavement evaluation data in the field can be expensive. The type, amount, and the frequency of data collection are affected by cost- effectiveness considerations. ⢠Frequency of evaluationâPublic Law 103-305 (1994) states that if an airport is conducting a PCI assessment as part of pavement management activities, a 3-year inspec- tion cycle is sufficient. However, the 3-year cycle may be too long for selecting and implementing preventive main- tenance treatments in a timely manner. ⢠Network- and project-level evaluationâThere is a difference between pavement evaluation data at net- work and project levels. Network-level management entails periodic surveys of pavement surface distresses and pavement friction on sample units. Project-level pavement management typically involves detailed eval- uation of pavement surface conditions over the entire project area and the evaluation of pavement load capac- ity through nondestructive testing (e.g., deflection, cone penetrometer, and ground penetrating radar) and destruc- tive testing (e.g., coring and boring and subsequent material testing). EVALUATION OF PAVEMENT CONDITION The following pavement characteristics are evaluated for in- service airfield pavements ⢠Pavement surface distress ⢠Pavement roughness ⢠Pavement friction ⢠Presence of foreign object debris ⢠Pavement structural strength or capacity. Pavement Surface Distress Surface distresses of airport pavements are typically evalu- ated using the PCI. The PCI evaluation methodology was developed by the U.S. Army Corps of Engineers and is described in FAA Advisory Circular on Guidelines and Pro- cedures for Maintenance of Airport Pavements (2007) and in ASTM Standard D5340 (2003). It is noteworthy that ASTM adopted the PCI as a pavement condition rating standard for airfield pavements. The PCI values can range from 0 to 100 and be interpreted as shown in Table 1. PCI distress data are obtained by a visual survey carried out by trained pavement evaluators who walk on the pave- ment. Alternatively, the evaluation can be done by taking high- quality pavement images and interpreting them using pave- ment evaluators or specialized software. The PCI is based on the evaluation of distress type, severity, and quantity. ⢠Distress typeâThere are 16 pavement surface distress types for AC pavements and 15 for PCC pavements. Considering pavement preservation needs, prominent distresses for AC pavements include longitudinal and transverse cracking, rutting, weathering and raveling, and block cracking. Also included are two distresses specifically related to airport operationsâjet blast and oil spillage. For PCC pavements, prominent distresses include joint seal damage, joint spalling, faulting, corner break, and linear cracking. PCI Rating Description Applicable Pavement Preservation Treatments 86â100 Goodâonly minor distresses Routine maintenance only 71â85 Satisfactoryâlow and medium distresses Preventive maintenance 56â70 Fair, some distresses are severe Corrective maintenance and rehabilitation 41â55 Poorâseverity of some of the distresses can cause operational problems Rehabilitation or reconstruction 26â40 Very poorâsevere distresses cause operational problems. Rehabilitation and reconstruction 11â25 Seriousâmany severe distresses cause operational restrictions Immediate repairs and reconstruction 0â10 Failedâpavement deterioration prevents safe aircraft operations Reconstruction TABLE 1 PAVEMENT CONDITION INDEX FOR AIRPORT PAVEMENTS
⢠Severity of pavement surface distressâThere are four severity levels defined for most of the pavement distress typesânone, low, medium, and high. The severity rating is facilitated by a systematic description of the severity levels and by photographs illustrating the differences between the levels. ⢠Quantity of pavement distressâQuantities are mea- sured in feet or in square feet of the affected area. Evaluation Methodology The distress assessment is done only on selected sample units. The results for sample units are averaged and the average result is reported for the entire section. The sample units are of a uniform size and selected by statistical sampling. The number of sampling units is chosen to achieve the desired accuracy and reliability. The major advantages of the PCI procedure are its wide use, objectivity, and acceptance. A PCI rating provides a good indication of the functional serviceability of the pavement and basic information about its structural integrity. A PCI rating alone can be used to estimate M&R needs for planning pur- poses. The advantages as well as potential misconceptions and pitfalls of using the PCI procedure for airfield pavements have been described by Broten and De Sombre (2001). As described in Table 2, 78% of all airports surveyed carry out periodic PCI surveys on the runways, with an aver- age frequency of every 3.4 years. The PCI surveys are done even by airports that do not have a formal PMS, and are sometimes done by state aviation administrations on behalf of the individual airports. Only one airport used an internal method to evaluate pavement surface distresses, and 10% of airports did not carry out any periodic pavement evaluation. Table 2 also notes that 54% of survey respondents use the PCI for taxiways and other facilities, with average frequen- cies of every 3.3 years. Information on the use of other types of pavement characteristics is also described. In addition, several airport agencies reported using digital images to doc- ument pavement surface distresses. Most state aviation agencies, such as those in Ohio, Michi- gan, Washington, Montana, and Oregon, carry out periodic 14 distress surveys for all airports under their jurisdiction using the PCI procedure. For example, all 50 public airports in Michigan are evaluated using the PCI methodology (Michigan Airports Division 2007). For project-level analysis, the evaluation of surface dis- tresses typically uses the same rating as that used for the net- work level. However, the entire section is evaluated instead of only sample units. Roughness The FAA defines profile roughness as surface profile devia- tions over a portion of the runway that may increase fatigue on airplane components, reduce braking action, impair cock- pit operations, and/or cause discomfort to passengers. The interaction between aircraft responses and runway pavement roughness is complex and depends on the type, weight, and speed of aircraft, and on the position of the observer in the aircraft (Woods and Papagiannakis 2009). Traditionally, M&R actions designed to improve pavement smoothness have been based on pilot observations and complaints (Larkin and Hayhoe 2009). For newly constructed airport pavements, procedures for measuring and specifying pavement roughness have been developed and accepted. For in-service pavements, a first step toward defining and implementing pavement roughness criteria is provided by FAA Advisory Circular on Guidelines and Procedures for Measuring Airfield Pavement Roughness (2009). The roughness criteria presented in the current ver- sion of the Circular are intended to address isolated bump events and do not address cyclic or harmonic events that can have a substantial impact on airplane occupants, components, and operations. The FAA also developed an inertial profiling system for measuring runway and taxiway longitudinal elevation profiles and a computer program, Profile Federal Aviation Administra- tion (ProFAA), to analyze the measured profiles. The ProFAA can be used to compute a variety of airport pavement roughness indices from the measured profiles, including the Boeing Bump Index and the International Roughness Index. Runways Taxiways and Other Facilities Pavement Characteristic Usage (%) Average Frequency, years Usage (%) Average Frequency, years PCI 78 3.4 54 3.3 Roughness 12 N/A 4 N/A Friction 22 N/A 8 N/A FWD testing 18 3.7 12 N/A Based on the survey. Notes: FWD = Falling Weight Deflectometer; N/A = Data are not available or are insufficient. TABLE 2 EVALUATION OF PAVEMENT CHARACTERISTICS
15 Based on the survey results, approximately 12% of agen- cies reported using roughness surveys on runways and 4% of agencies on taxiways and other facilities (see Table 2). Pavement Friction Pavement friction is the force that resists the motion between a vehicle tire and a pavement surface. Pavement friction is a significant safety concern for aircraft with greater weight and landing speeds, such as turbojet aircraft, particularly when the pavement is wet. The Guide for Pavement Friction (Hall at al. 2009) provides general technical information on pave- ment friction. FAA Advisory Circular on Measurement, Construction, and Maintenance of Skid-resistant Airport Pavement Sur- faces (2004) provides guidelines for designing skid-resistant airport pavement surfaces and for on-going monitoring and evaluation of pavement friction. The Circular also describes recommended procedures to measure pavement friction and provides specific friction levels required for safe aircraft operations. These friction levels can be used to plan and carry out appropriate M&R actions. For airfield pavements, friction is typically evaluated on runways only. Twenty-two percent of responding agencies reported that they evaluate pavement friction on runways. In addition, 8% of airport agencies reported measuring friction on taxiways (see Table 2). Presence of Foreign Object Debris The presence of foreign object debris is evaluated using the Foreign Object Damage/Debris (FOD) Index. The FOD Index is determined from the PCI calculated by considering only the distresses/severity levels capable of producing FOD (Pavement Engineering Assessment Standards 2004). The FOD index is generally not used at major airports. Structural Evaluation The overall structural strength of airport pavements is evalu- ated using the Aircraft Classification NumberâPavement Clas- sification Number (ACN-PCN) method outlined in the draft FAA Advisory Circular on Standardized Method of Reporting Airport Pavement StrengthâPCN (2009). The PCN captures the relative strength of the pavement structure (considering a standard subgrade) and the ACN provides guidance to airport operators regarding the relative effect of an aircraft on the pavement structure. The PCN evaluation is not routinely used for the planning of pavement M&R treatments and was not included in the survey. According to the survey (see Table 2), 18% of airports, typically large airports, carry out periodic network-level sur- veys using a Falling Weight Deflectometer (FWD) on run- ways and 12% of surveyed airports reported FWD surveys of taxiways and other facilities. The average frequency of the FWD surveys on runways was 3.7 years. Procedures for FWD testing are outlined in FAA Advisory Circular on Use of Nondestructive Testing Devices in the Evaluation of Airport Pavements (2004). For project-level analysis, structural evaluation is discussed in chapter seven. CONDITION ANALYSIS Pavement condition analysis utilizes pavement condition data in pursuit of the following outcomes: ⢠Assessment of the overall condition of the pavement net- work. For example, Figure 7 shows the results of a PCI survey for a small Michigan airport (Michigan Airports Division 2007). The objective assessment of the condi- tion of the asset is also useful in meeting the accounting recommendations of the Governmental Accounting Standards Board (1999). THSOUTH (100) RW1533 (34) THEAST1 (29) RW1836 (100) RW1533 (34) TWA (100) TWB (100) TWA (100) TW927 (36) A01 (34) A02 (70) THW (21) THEAST2 (29) Pavement Condition Index 100 - 86 85 - 71 70 - 56 55 - 41 40 - 26 25 - 11 10 - 0 FIGURE 7 Example of a graphical display of Pavement Condition Index.
⢠Trends in pavement condition. Historical trends in the health of the network provide linkage between pavement preservation investments and the outcomes. For example, Figure 8 shows an improvement in the condition of the runway pavements, but no improvement in the condi- tion of pavements on other facilities. The PCI results in Figure 8 are based on a 3-year evaluation period. ⢠Documentation of system benefits. Systematic analyses of pavement conditions play a vital role in the documen- tation of APMS benefits necessary to secure continued financial support for the program. ⢠Documentation of funding needs. Condition analysis provides basic data for the determination of funding needs, as described in chapter five. ⢠Technical analysis of pavement performance. System- atic pavement condition evaluation can identify: â Major causes of pavement deterioration such as poor drainage and inappropriate pavement materials. â Well or poorly performing initial pavement struc- tures, or the subsequent M&R treatments. â Rates of pavement deterioration for different pavement types, facilities, and M&R treatments. The deteriora- tion rates are used to develop pavement performance models discussed in chapter five. â Pavement sections with inadequate structural capacity. PAVEMENT EVALUATION FOR PREVENTIVE MAINTENANCE Pavement condition surveys that evaluate the type, severity, and extent of pavement surface distresses are also used in preven- tive maintenance programs. However, for selection and appli- cation of preventive maintenance treatments it is also desirable to identify specific pavement conditions and early indicators that trigger the need for preventive maintenance treatments. Preventive maintenance treatments are best applied when they are most cost-effective, typically before distresses progress and more expensive corrective treatments are needed. For example, treatments to route and seal cracks in asphalt con- crete pavements are carried out when the cracks are already 16 well-formed, but before cracks become raveled, have devel- oped into multiple cracks, or before the crack width exceeds about three-eighths of an inch. Most effectively, condition surveys of pavement surface distresses for the selection and timing of preventive maintenance treatments are annually carried out on candidate pavement sections. The first pave- ment preservation treatments are typically carried out when the pavement surface layer is between 3 and 5 years old. The results of the synthesis survey show that the average frequency of PCI surveys on runways was 3.4 years (see Table 2) with the range of from 1 to 10 years. PAVEMENT PERFORMANCE PREDICTION For planning purposes, airport pavement maintenance man- agers estimate future pavement preservation needs. A typical planning period is 5 years; however, some large airports may prepare pavement preservation plans for major runways for up to 15 years. Predicting pavement performance and storing the results in the APMS database assists managers in identi- fying future pavement performance. Use of Pavement Performance Prediction Future pavement performance, or pavement deterioration, is estimated using pavement performance models. The survey revealed that 66% of responding airport agencies use an APMS to predict future pavement deterioration (see Figure 6). Pave- ment performance prediction serves the following: ⢠Estimation of when the pavement will require M&R treatment. The need for performance prediction is illus- trated in Figure 9, which shows pavement performance curves for two pavements. Both pavements have the same present PCI, but pavement B deteriorates, and is expected to deteriorate, faster than pavement A. Conse- quently, pavement B will require an earlier pavement preservation treatment. ⢠Estimation of treatment type. As shown in Figure 9, when pavement condition reaches a minimum accept- able service level it should be rehabilitated. To identify 0 20 40 60 80 100 19 99 20 02 20 05 20 08 Survey year A ve ra ge P CI Runways All other facilities FIGURE 8 Illustration of trends in average PCI for runway pavements and all other pavements. 0 100 Now + 2 Pavement age, years Past performance Remaining Service Life A B Pa ve m en t C on di tio n In de x (P CI ) Now +5 Predicted performance Minimum acceptable service level Now FIGURE 9 Pavement performance prediction.
17 future funding needs, the type of the M&R treatment, and its cost and timing, need to be estimated. ⢠Estimation of the life span of M&R treatments. To select cost-effective treatments, it is necessary to estimate the cost of the treatment and its life span. The subsequent monitoring of the treatment performance provides feed- back on the choices made. ⢠Deterioration rate. The predicted rate of pavement dete- rioration can also be used as one of the factors to select candidate sections for M&R. In Figure 9, pavement B is expected continue to deteriorate at a higher rate than pavement A, and the timing of the M&R treatment for pavement B is now. ⢠Estimation of the remaining service life. Figure 9 also defines the remaining service life of the pavement. When known for all sections of the network, the remaining ser- vice life can be used to characterize the overall condition of the network. It is also useful in planning and program- ming pavement M&R activities (Wade at al. 2007a). ⢠Timing of preventive maintenance treatments. Pavement conditions that exist at the time of the pavement evalu- ation survey may need to be extrapolated to the time when an M&R treatment will be applied. In some cases, the lead time may be 3 or more years. Preventive main- tenance treatments are typically planned only from 2 to 18 months in advance. Pavement Performance Modeling Techniques Pavement performance depends on many local factors such as the type and frequency of traffic loads, environmental expo- sure, subgrade characteristics including drainage, and pave- ment structure. Consequently, pavement performance models are not easily transferable from airport to airport. The selection of performance models depends on available data, agency requirements for estimating future pavement preservation needs, and on the APMS software used. Typical methods used for pavement performance model- ing include: ⢠Expert modeling. Expert modeling can be used when his- torical pavement performance data are not available. Per- formance models, such as a relationship between pave- ment condition and pavement age for different pavement types (e.g., AC or PCC) and airport pavement facilities (e.g., runways and taxiways) are based on the expert opinion of pavement professionals (Zimmerman 2000). ⢠Modeling using families of performance curves. The concept of âfamilyâ modeling is based on the expecta- tion that similar airport pavements exposed to similar traffic will perform in a similar way. For example, all pavement sections on runways that have AC overlays are expected to have the same pattern of pavement dete- rioration. The deterioration pattern is established using a few sections with known performances and applied to all other sections. Family modeling is a default model- ing approach in MicroPAVER (Shahin 2001). ⢠Extrapolation of existing trends. This approach is a variation on family modeling. If the condition of the pavement was evaluated on only one previous occasion, the family pattern is extrapolated taking into account the condition observed in the past. If the condition of the pavement was evaluated in the past on more than one occasion, the extrapolation using a family curve can take into account the past observation points using regression analysis. The extrapolation using one observation point is illus- trated in Figure 10. The observed PCI value in year 10 is above the family prediction curve. Following the trend established by the family prediction curve it is expected that the section will reach the minimum recommended PCI level in year 20, compared with year 18 expected for the pavement family prediction. ⢠Markov probability models. Markov models have been used for pavement performance prediction of highway pavements. However, it appears that they have not been used for airfield pavements (Tighe and Covalt 2008). Artificial neural networks. Artificial neural networks (ANN), or neural networks, are computing procedures or systems that can link a large set of data (e.g., a data set describing the pavement and its exposure to the traffic and environment) to an outcome (e.g., expected life span of the pavement) with- out using traditional statistical analysis. However, pavement performance models, whether they are developed using ANN or conventional modeling techniques, have to be calibrated to local conditions. Although the calibration process can be facilitated using ANN, the calibration of ANN requires spe- cialized computational techniques that are still experimental. The applicable technology of ANN is reviewed in Trans- portation Research Circular E-C012: Use of Artificial Neural Networks in Geomechanical and Pavement Systems (1999). 0 5 10 300 15 20 25 Observed PCI 18 Pavement age, years Pa ve m en t C on di tio n In de x (P CI ) 100 Section-specific prediction80 20 60 40 Pavement âfamilyâ Minimum recommended PCI level prediction FIGURE 10 Pavement performance prediction using a pavement family prediction.