Cracking and Roughness of Asphalt Pavements Constructed Using Cement-Treated Base Materials

Transcription

1 Brigham Young University BYU ScholarsArchive All Theses and Dissertations Cracking and Roughness of Asphalt Pavements Constructed Using Cement-Treated Base Materials Jonathan Russell Hanson Brigham Young University - Provo Follow this and additional works at: Part of the Civil and Environmental Engineering Commons BYU ScholarsArchive Citation Hanson, Jonathan Russell, "Cracking and Roughness of Asphalt Pavements Constructed Using Cement-Treated Base Materials" (2006). All Theses and Dissertations This Thesis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in All Theses and Dissertations by an authorized administrator of BYU ScholarsArchive. For more information, please contact scholarsarchive@byu.edu, ellen_amatangelo@byu.edu.

2 CRACKING AND ROUGHNESS OF ASPHALT PAVEMENTS CONSTRUCTED USING CEMENT-TREATED BASE MATERIALS by Jon Russell Hanson A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of Master of Science Department of Civil and Environmental Engineering Brigham Young University April 2006

3 BRIGHAM YOUNG UNIVERSITY GRADUATE COMMITTEE APPROVAL of a thesis submitted by Jon Russell Hanson This thesis has been read by each member of the following graduate committee and by majority vote has been found to be satisfactory. Date W. Spencer Guthrie, Chair Date Steven E. Benzley Date Mitsuru Saito

4 BRIGHAM YOUNG UNIVERSITY As chair of the candidate s graduate committee, I have read the thesis of Jon Russell Hanson in its final form and have found that (1) its format, citations, and bibliographical style are consistent and acceptable and fulfill university and department style requirements; (2) its illustrative materials including figures, tables, and charts are in place; and (3) the final manuscript is satisfactory to the graduate committee and is ready for submission to the university library. Date W. Spencer Guthrie Chair, Graduate Committee Accepted for the Department A. Woodruff Miller Department Chair Accepted for the College Alan R. Parkinson Dean, Ira A. Fulton College of Engineering and Technology

5 ABSTRACT CRACKING AND ROUGHNESS OF ASPHALT PAVEMENTS CONSTRUCTED USING CEMENT-TREATED BASE MATERIALS Jon Russell Hanson Department of Civil and Environmental Engineering Master of Science While cement treatment is a proven method for improving the strength and durability of soils and aggregates, cement hydration causes shrinkage strains in the cement-treated base (CTB) that can lead to reflection cracking in asphalt surfaces. Cracking may then cause increased pavement roughness and lead to poor ride quality. The overall purpose of this research was to utilize data collected through the Long-Term Pavement Performance (LTPP) program to investigate the use and classification of CTB layers and evaluate the relative impact of cement content on the development of roughness and cracking in asphalt concrete (AC) pavements constructed using CTB layers. The data included 52 LTPP test sites, which represented 13 different states and one Canadian province, with cement contents ranging from 3.0 to 9.5 percent by weight of dry aggregate. Statistical procedures were utilized to identify the factors that were most correlated to the observed pavement performance and to develop prediction equations that transportation agencies can use to estimate the amount of roughness for a given

6 pavement at a given age and the amount of distress associated with a particular crack severity level for a given pavement. The data collected for this study suggest that wide ranges of cement contents are used to stabilize soils within individual American Association of State Highway and Transportation Officials soil classifications. The data also suggest that CTBs comprising flexible pavement structures are constructed mainly on rural facilities. A backwardselection model development technique was used to develop sets of prediction equations for roughness and cracking. Age, AC thickness, CTB thickness, and cement content were determined to be significant predictors of International Roughness Index, while age, air freezing index, AC thickness, CTB thickness, cement content, and traffic loads in thousands of equivalent single-axle loads were determined to be significant predictors of low-severity, medium-severity, and high-severity block, fatigue, longitudinal (wheel-path and non-wheel-path), and transverse cracking in AC pavements constructed using CTB layers. Investigation of the relationships between CTB modulus and the development of roughness and cracking is recommended for further study.

7 ACKNOWLEDGMENTS I wish to give my most sincere thanks to Dr. Spencer Guthrie for his guidance, unwavering example, and friendship. I would also like to thank Dr. David Luhr of the Portland Cement Association and Dr. Dennis Eggett of the Brigham Young University (BYU) Center for Collaborative Research and Statistical Consulting for their assistance and interest in this research. Appreciation is given to the Utah Department of Transportation for funding this project. In addition, I am very grateful to the following BYU students who have lent me a helping hand throughout the course of this research: Russell Lay, Rebecca Crane, Ashley Brown, Steven Frost, Ellen Linford, Aimee Birdsall, and Jeffrey Lewis. Above all, I wish to thank my wife for her support and encouragement.

8 TABLE OF CONTENTS LIST OF TABLES...ix LIST OF FIGURES...x CHAPTER 1 INTRODUCTION Problem Statement Scope Outline of Report...3 CHAPTER 2 LONG-TERM PAVEMENT PERFORMANCE DATA Performance of Cement-Treated Base Materials Long-Term Pavement Performance Program Pavement Test Sections Summary...15 CHAPTER 3 ROUGHNESS Roughness of Cement-Treated Base Layers Procedures Results Summary...26 CHAPTER 4 CRACKING Cracking of Cement-Treated Base Layers Procedures Results Summary...37 CHAPTER 5 CONCLUSION Summary Findings Recommendations...41 vii

9 REFERENCES...43 APPENDIX A...47 APPENDIX B...61 viii

10 LIST OF TABLES Table 2.1 Table 2.2 Table 3.1 Table 3.2 Construction Date, Functional Classification, and Freezing Index...9 Layer Thicknesses and Material Type...11 Pavement Roughness Threshold Values...18 Significance of Predictor Variables and Roughness Prediction Equation...24 Table 4.1 Significance of Predictor Variables and Cracking Prediction Equations..37 ix

11 LIST OF FIGURES Figure 2.1 Figure 2.2 Reflection Cracking from Cement-Treated Base...6 Distribution of Cement Content by Functional Classification...13 Figure 2.3 Distribution of Cement Content by Soil Classification...14 Figure 2.4 Distribution of Cement Content by Cement-Treated Base Type...15 Figure 3.1 Correlation Between International Roughness Index and Age for 3 Percent Cement...20 Figure 3.2 Correlation Between International Roughness Index and Age for 4 Percent Cement...21 Figure 3.3 Figure 3.4 Figure 3.5 Correlation Between International Roughness Index and Age for 5 Percent Cement...21 Correlation Between International Roughness Index and Age for 6 Percent Cement...22 Correlation Between International Roughness Index and Age for 7 Percent Cement...22 Figure 3.6 Correlation Between International Roughness Index and Age for 8 Percent Cement...23 Figure 3.7 Correlation Between International Roughness Index and Age for 9 Percent Cement...23 Figure 3.8 Roughness Development for Each Cement Content Category...25 Figure 3.9 Distribution of Cement Content by Roughness Category...26 Figure 4.1 Effect of Cement Content on Fatigue and Block Cracking...35 Figure 4.2 Effect of Cement Content on Wheel-Path and Non-Wheel-Path Longitudinal Cracking...36 x

12 CHAPTER 1 INTRODUCTION 1.1 PROBLEM STATEMENT In the United States, the amount of high-quality materials for building pavement base layers is diminishing. The Portland Cement Association (PCA) states (1, p. 2): A century of modern growth and urbanization in America has depleted once plentiful aggregate supplies. Frequently, aggregates either come from distant quarries at great expense or from local sources offering only marginal quality. Continuing to exhaust these valuable resources to rebuild existing roads only propagates and accelerates the problem. Therefore, the pavement industry seeks ways of improving lower quality materials that are more readily available for use in roadway construction. Cement treatment has become an accepted method for increasing the strength and durability of marginal-quality soils and aggregates. The cement binds the aggregates together, generating greater material strength and rigidity and increasing resistance to moisture damage and frost action. The amount of cement that is blended with the aggregate base material cannot be excessive, however, because cement hydration causes shrinkage stresses in the cementtreated base (CTB) that can lead to cracking of the layer. Cracking creates avenues for water ingress into the base layer, causes accelerated pavement damage by increasing erosion and susceptibility to deterioration under freeze-thaw cycling, and decreases the strength and stiffness of the affected layers. Therefore, increased cracking can cause increased pavement roughness and lead to poor ride quality. Recognizing the need to minimize damage due to CTB shrinkage, other researchers have previously investigated the mechanism and extent of shrinkage cracking in CTBs and methods of minimizing damage due to CTB shrinkage (2, 3, 4, 5, 6, 7). 1

13 The objectives of this research were to investigate the use and classification of CTB layers and evaluate the relative impact of cement content on roughness development and cracking in asphalt pavements constructed using CTB layers. Because several parameters influence the performance of a CTB, including cement content, aggregate type, layer thickness, traffic loads, environmental conditions, and pavement age, statistical procedures were utilized to identify those factors most correlated to pavement performance. 1.2 SCOPE Data collected through the Long-Term Pavement Performance (LTPP) program were used as the basis for this study. The data were downloaded from primarily the Inventory, Monitoring, and Testing modules of DataPave, the on-line LTPP database. The scope of the research was limited to asphalt concrete (AC) pavements with CTB layers; use of these filter criteria led to the identification of 52 LTPP test sites from 13 different states and one site located in Canada. Specifically, these pavement sections were located in Arkansas, California, Delaware, Georgia, Maryland, Mississippi, Missouri, North Carolina, North Dakota, Oregon, Texas, Virginia, Wyoming, and Alberta, Canada, and included cement contents ranging from 3.0 to 9.5 percent by weight of dry aggregate. Extensive inventory data were compiled for each site, including construction date, functional classification of the facility, average air freezing index, AC layer thickness, CTB layer thickness, cement content, base type, and American Association of State Highway and Transportation Officials (AASHTO) soil classification. In addition, monitored data such as International Roughness Index (IRI), pavement distress, and traffic loads in terms of thousands of equivalent single-axle loads (KESALs) were collected. Analyses included only those data collected during the period defined as construction number one for each site. In the LTPP program, the construction number is incremented upon the initiation of maintenance or rehabilitation action. Because the effects of pavement maintenance and rehabilitation on pavement performance were outside the scope of this work, data associated with construction numbers greater than one were not considered. Also, unconfined compressive strength was not analyzed because only a limited number of sites included CTB strength data. 2

14 1.3 OUTLINE OF REPORT This report contains five chapters. Chapter 1 presents the objectives and scope of the research. Chapter 2 provides a brief history of CTB usage, summarizes previous research related to this study, and introduces the data set analyzed in this report. Chapter 3 presents an analysis of the roughness data, provides a roughness prediction equation, explores the effect of cement content on the rate at which roughness increases over time, and documents roughness levels at which transportation agencies decide to initiate maintenance or rehabilitation to improve pavement condition. Chapter 4 provides evaluations of cracking extent and severity for asphalt pavement constructed using CTBs, and, finally, Chapter 5 presents a summary of the research findings. 3

15 4

16 CHAPTER 2 LONG-TERM PAVEMENT PERFORMANCE DATA 2.1 PERFORMANCE OF CEMENT-TREATED BASE MATERIALS Experimental soil stabilization was performed in the United States as early as 1908 when J. H. Aimes patented a cement treatment process for soils used in the construction of roads. Similarly, in the United Kingdom, H. E. Brooke-Bradley attempted to stabilize the chalky soil at a military camp with cement in Aimes patented a product known as Soilaimes in 1917, and in 1920 he patented Soil-crete (8). Construction practices from the early 1900s are similar to those employed today. After a site had been selected for stabilization, cement was spread over the area, milled in with a plow, and then tamped or compacted with a roller. The amount of cement used generally varied from 5 to 15 percent, depending on the site. Lower cement contents were typically used for sandy gravels, while higher contents were typically used for cohesive soils. In 1942, PCA indicated that 85 percent of all soils that were candidates for cement treatment could be sufficiently stabilized with the addition of 14 percent cement or less (8). With the advent of soil cement stabilization, its use became very popular. In fact, engineers began to specify increasingly higher cement contents in hopes of further increasing the strength and durability of pavement structures. However, the increase in cement content led to significant shrinkage cracking problems. CTB volume reductions were exacerbated by self-dessication due to cement hydration, which initiated the formation of shrinkage cracks in the CTB layer that would reflect through the flexible pavement surface as illustrated in Figure 2.1 (9). Cracking became so prevalent with the increased cement contents that several state departments of transportation (DOTs) banned the use of cement stabilization in their roadways (10). 5

17 However, in the 1960s and 1970s, several researchers published work addressing CTB shrinkage cracking and methods for reducing it (2, 3, 4, 5, 6, 7), and in 1987 the Federal Highway Administration selected numerous pavement sections with CTB layers for inclusion in the LTPP program. Routine monitoring of the pavement sections generated significant amounts of field performance data, which were first made available to the public in 1991 (11). Although LTPP data have been utilized by several authors (12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23), only limited studies have been performed utilizing data collected from asphalt pavements with CTB layers. Indeed, an extensive Figure 2.1 Reflection cracking from cement-treated base (3). 6

18 literature review identified just one publication that specifically utilizes LTPP data to address crack-related degradation of pavement systems constructed using CTBs (24). The author of that document, K. P. George, limited his research specifically to 14 LTPP sites corresponding to eight different states. He developed a model that can be used to predict the amount of shrinkage cracking in a CTB as a function of subgrade restraint forces and shrinkage characteristics and mechanistic properties of the CTB material, but he did not consider any other causative factors such as layer thicknesses or traffic loading. Furthermore, his study only refers to the amount of cracking in a pavement over time and makes no reference to roughness or deterioration through time. In the current research, 52 flexible pavement sections constructed with CTB layers were selected from the LTPP database for evaluation, and statistical analyses of both roughness and cracking were performed. This study may therefore be the most comprehensive investigation of CTB performance conducted to date using LTPP data. The following sections provide a description of the LTPP program and present the characteristics of each of the pavement sections included in the study. 2.2 LONG-TERM PAVEMENT PERFORMANCE PROGRAM The LTPP program was created to investigate parameters that impact pavement performance life. Specific objectives of the LTPP program include the following (25): 1. Evaluate existing design methods. 2. Develop improved design methodologies and strategies for the rehabilitation of existing pavements. 3. Develop improved design equations for new and reconstructed pavements. 4. Determine the effects of loading, environment, material properties and variability, construction quality, and maintenance levels on pavement distress and performance. 5. Determine the effects of specific design features on pavement performance. 6. Establish a national long-term pavement database to support the objectives and future needs of the program. The LTPP program includes more than 2400 pavement test sections located throughout the United States and Canada and boasts the largest pavement performance 7

19 database in the world. LTPP data are currently accessible on-line through a structured, user-friendly software tool called DataPave (26). In DataPave, LTPP data are organized in numerous tables arranged into information modules designed to facilitate efficient data extraction. As stated previously in Chapter 1, all of the data analyzed in this research were downloaded from primarily the Inventory, Monitoring, and Testing modules of the LTPP database. These modules are described in the following paragraphs. The inventory module contains static information for all of the test sections included in the LTPP program. The tables in this module include data regarding the test site location, pavement structure dimensions, and material types. This module was used to find only the sites with cement-stabilized base materials. The INV_STABIL table found in the Inventory module contains information regarding the type and percentage of stabilizing agent utilized in the base layer of each pavement structure (27). The Monitoring module is the largest module in the LTPP database, as it contains extensive pavement performance monitoring data. Relevant to this research, longitudinal profile measurement data collected either manually or by an automated dipstick are found in the MON_PROFILE table, and the MON_DIS table includes distress survey data from manual and film-based surveys (27). Included in the Testing module are test descriptions and protocols together with laboratory and field test results. For example, the TST_LO5B table contains the results of all material testing performed on the base material (27). 2.3 PAVEMENT TEST SECTIONS This research was based entirely on original data collected in the LTPP program. Summaries of LTPP pavement test section information are given in Tables 2.1 and 2.2, which are referenced again in Chapters 3 and 4 addressing roughness and cracking analyses, respectively. Table 2.1 provides the state or province in which the site is located, LTPP site identification number, construction date, functional classification, and air freezing index for each site. Table 2.2 repeats the state or province and identification 8

20 TABLE 2.1 Construction Date, Functional Classification, and Freezing Index State or Province ID Construction Date Functional Classification Freezing Index ( C-days) AB /1/1985 Rural Principal Arterial- Other 1248 AR 2042 * 12/1/1972 Rural Principal Arterial- Other 30 AR /1/1981 Rural Principal Arterial- Other 49 CA 2002 * 12/1/1980 Rural Principal Arterial- Other 76 CA /1/1976 Rural Principal Arterial- Interstate 0 CA /1/1972 Rural Principal Arterial- Other 0 CA /1/1979 Rural Principal Arterial- Other 0 CA 2041 * 7/1/1971 Rural Principal Arterial- Other 0 CA 2051 * 2/1/1981 Urban Principal Arterial - Other Freeways or Expressways 0 CA /1/1973 Rural Principal Arterial- Interstate 0 CA /1/1976 Rural Principal Arterial- Other 1 CA /1/1972 Rural Minor Arterial 1 CA 8149 * 8/1/1971 Rural Principal Arterial- Interstate 0 CA /1/1973 Rural Principal Arterial- Interstate 0 CA /1/1971 Rural Minor Arterial 0 CA /1/1970 Rural Principal Arterial- Other 0 DE 1450 * 6/1/1976 Rural Principal Arterial- Other 99 GA /1/1986 Rural Principal Arterial- Other 2 GA /1/1986 Rural Principal Arterial- Other 3 GA 4096 * 6/1/1985 Rural Minor Collector 6 MD 1632 * 10/1/1986 Rural Principal Arterial- Other 81 MD /1/1986 Rural Principal Arterial- Interstate 132 MO /1/1965 Rural Minor Arterial 146 MO /1/1965 Rural Principal Arterial- Other 147 MS 2807 * 12/1/1982 Rural Principal Arterial- Other 65 MS 3081 * 10/1/1984 Rural Principal Arterial- Other 34 MS /1/1978 Rural Principal Arterial- Other 66 MS /1/1978 Rural Principal Arterial- Other 64 MS 3087 * 10/1/1982 Rural Principal Arterial- Other 67 MS /1/1982 Rural Principal Arterial- Other 61 MS /1/1973 Rural Principal Arterial- Other 56 NC 1645 * 10/1/1986 Rural Principal Arterial- Other 11 NC /1/1983 Rural Principal Arterial- Other 50 ND /1/1978 Rural Principal Arterial- Other 1436 OR 2002 * 6/1/1971 Rural Principal Arterial- Other 22 TX 2108 * 8/1/1985 Rural Principal Arterial- Other 2 TX 2176 * 7/1/1970 Rural Major Collector 146 TX 3669 * 5/1/1983 Rural Minor Arterial 8 9

21 State or Province ID Construction Date TABLE 2.1 (Continued) Functional Classification Freezing Index ( C-days) TX 3679 * 6/1/1988 Rural Minor Arterial 8 TX 3689 * 4/1/1987 Rural Principal Arterial- Other 9 VA /1/1981 Rural Principal Arterial- Other 141 VA /1/1979 Rural Principal Arterial- Other 141 VA 2004 * 12/1/1981 Urban Principal Arterial - Other Freeways or Expressways 60 WY /1/1978 Rural Principal Arterial- Interstate 411 WY 2017 * 8/1/1982 Rural Minor Arterial 572 WY /1/1983 Rural Principal Arterial- Other 577 WY 2019 * 7/1/1985 Rural Minor Arterial 619 WY 2020 * 7/1/1985 Rural Principal Arterial- Interstate 610 WY /1/1985 Rural Minor Arterial 772 WY /1/1986 Rural Minor Arterial 600 WY 7773 * 1/1/1987 Rural Minor Arterial 552 While all sites shown in the table were included in roughness analyses, only the sites marked with an asterisk (*) were included in cracking analyses. number and then reports AC thickness, CTB thickness, cement content, base type, and AASHTO soil classification for each of the LTPP sections analyzed in this study. These data were utilized to determine the facility types for which cement treatment is most commonly used, evaluate the importance of AASHTO soil classifications on cement content selections, and examine the relationship between cement content and CTB type. Figures 2.2, 2.3, and 2.4 show cement content distribution by functional classification, soil classification, and base type, respectively. To the extent that the LTPP sites evaluated in this study can be considered representative of all AC pavements constructed using CTBs, Figure 2.2 indicates that CTBs comprising flexible pavement 10

22 TABLE 2.2 Layer Thicknesses and Material Type State AC CTB Cement AASHTO or ID Thickness Thickness Content Base Type Soil Province (cm) (cm) (%) Classification AB Cement Treated Soil A-3 AR 2042 * Cement Aggregate Mixture A-2-4 AR Cement Aggregate Mixture A-2-4 CA 2002 * Cement Aggregate Mixture A-1a CA Cement Aggregate Mixture A-3 CA Lean Concrete A-1a CA Lean Concrete A-1a CA 2041 * Cement Aggregate Mixture A-1a CA 2051 * Cement Aggregate Mixture A-1a CA Cement Aggregate Mixture A-1a CA Cement Aggregate Mixture A-3 CA Lean Concrete A-1a CA 8149 * Cement Aggregate Mixture A-1a CA Cement Aggregate Mixture A-3 CA Cement Aggregate Mixture A-1a CA Cement Aggregate Mixture A-1-b DE 1450 * Soil Cement A-2-4 GA Soil Cement A-2-4 GA Soil Cement A-2-4 GA 4096 * Soil Cement A-3 MD 1632 * Lean Concrete A-3 MD Cement Aggregate Mixture N/A MO Soil Cement A-6 MO Soil Cement A-6 MS 2807 * Soil Cement A-2-4 MS 3081 * Soil Cement A-2-4 MS Soil Cement A-2-4 MS Soil Cement A-2-4 MS 3087 * Soil Cement A-2-4 MS Soil Cement A-2-4 MS Soil Cement A-2-4 NC 1645 * Soil Cement A-3 NC Cement Aggregate Mixture A-1a ND Lean Concrete N/A OR 2002 * Cement Aggregate Mixture A-3 TX Cement Aggregate Mixture A-2-4 TX 2108 * Cement Aggregate Mixture A-2-4 TX 2176 * Cement Aggregate Mixture A-2-6 TX 3669 * Cement Aggregate Mixture A

23 TABLE 2.2 (Continued) State AC CTB Cement AASHTO or ID Thickness Thickness Content Base Type Soil Province (cm) (cm) (%) Classification TX 3679 * Cement Aggregate Mixture A-1a TX 3689 * Cement Aggregate Mixture A-2-4 VA Cement Aggregate Mixture A-1a VA Cement Aggregate Mixture A-1-b VA 2004 * Lean Concrete A-1a WY Cement Aggregate Mixture A-1a WY 2017 * Cement Aggregate Mixture A-1a WY Cement Aggregate Mixture A-1-b WY 2019 * Cement Aggregate Mixture A-1-b WY 2020 * Cement Aggregate Mixture A-1a WY Cement Aggregate Mixture A-1a WY Cement Aggregate Mixture A-1-b WY 7773 * Cement Aggregate Mixture A-1a While all sites shown in the table were included in roughness analyses, only the sites marked with an asterisk (*) were included in cracking analyses. structures are constructed mainly on rural facilities; only 6 percent of the sites included in the study are classified as urban. This observation may simply reflect original LTPP site selection criteria, but it may also suggest that dusting or other construction issues associated with CTB placement discourage engineers from specifying the use of cement stabilization in urban environments. Approximately 58 percent of the sites are in the Rural Principle Arterial-Other category. Although PCA offers guidelines regarding the amount of cement that should be used to stabilize materials based on AASHTO soil classification (28), Figure 2.3 suggests that a broad range in cement content is utilized in each of the listed soil classes; pavement engineers are apparently applying other criteria when selecting cement contents for CTBs. Figure 2.3 also shows that, among the sites evaluated in this research, the soil 12

24 Cement Content (%) Rural Major Collector Rural Minor Arterial Rural Minor Collector Rural Principal Arterial- Interstate Rural Principal Arterial- Other Urban Other Principal Arterial Urban Principal Arterial - Other Freeways or Expressways Functional Classification Sites Included in Roughness and Cracking Analyses Sites Included Only in Roughness Analyses FIGURE 2.2 Distribution of cement content by functional classification. classification types most commonly stabilized with cement are A-1-a and A-2-4, which represent 35 and 31 percent of the total number of sites, respectively. Figure 2.4 displays the cement contents characteristic of each of the four CTB types specified in the LTPP program. The CTB layers for 60 percent of the sites are 13

25 considered to be cement-aggregate mixtures, while only 2 percent are considered to be cement-treated soil. However, according to PCA, cement-aggregate mixtures and cement-treated soils are subcategories within soil cement. Furthermore, CTBs considered to be lean concrete should have the greatest cement contents among these categories according to definitions published by PCA, but the other three CTB types representing LTPP data analyzed in this research include much higher cement contents than lean concrete. These observations suggest that inconsistent or inadequate definitions may not permit clear distinctions between these CTB types Cement Content (%) A-1-a A-1-b A-2-4 A-2-6 A-3 A-6 N/A AASHTO Soil Classification Sites Included in Roughness and Cracking Analyses Sites Included Only in Roughness Analyses FIGURE 2.3 Distribution of cement content by soil classification. 14

26 Cement Content (%) Cement- Aggregate Mixture Lean Concrete Base Type Soil Cement Cement-Treated Soil Sites Included in Roughness and Cracking Analyses Sites Included Only in Roughness Analyses FIGURE 2.4 Distribution of cement content by cement-treated base type. 2.4 SUMMARY Cement stabilization has been used as early as 1908 for improving the strength and durability of soils and aggregates utilized in roadway construction. Although stabilizing a base layer with cement has proven effective on numerous projects, addition of excessive amounts of cement has been shown to cause shrinkage cracking that eventually 15

27 propagates through the flexible pavement surface and causes poor pavement performance. In 1987, the Federal Highway Administration selected numerous pavement sections with CTB layers for inclusion in the LTPP program, which was created to investigate parameters that impact pavement performance life. While many researchers have utilized LTPP data in their studies, only one publication was identified in this research that specifically employs LTPP data to address crack-related degradation of pavement systems constructed using CTBs; that study included 14 LTPP sites in eight states. The current research extends the previous work by analyzing performance data for 52 LTPP sites representing 13 states and one Canadian province. The pavement sections included in the data set are constructed mainly on rural facilities with CTB layers stabilized with cement contents ranging from 3.0 to 9.5 percent. 16

28 CHAPTER 3 ROUGHNESS 3.1 ROUGHNESS OF CEMENT-TREATED BASE LAYERS Roughness is regarded as the most important measure of pavement performance next to safety, as ride quality directly impacts the comfort of the traveling public. Although pavement roughness often reflects the quantity and severity of distresses manifest on the pavement surface, such as cracking, rutting, and patching, the development of roughness is fundamentally influenced by the strength, durability, and thickness of the pavement layers and the environmental conditions and traffic loads to which the pavement is subjected. Because traffic loading and environmental conditions such as freeze-thaw cycling can cause cumulative damage through time, age is another important factor affecting pavement roughness. Mechanistic approaches to predicting structural rutting and fatigue cracking in asphalt pavements are based on calculations of vertical compressive strains on the top of the subgrade and horizontal tensile strains at the bottom of the AC layer, respectively (29). The spatial distributions of traffic-induced stresses and strains within a pavement structure depend greatly upon the stiffness of the constituent materials and the layer thicknesses. Stiffer, thicker base layers can distribute loads over greater areas than more flexible, thinner layers, resulting in reduced strains that reduce rutting and improve fatigue life (30). Furthermore, with specific regard to asphalt pavements constructed with cement-stabilized base layers, greater AC thicknesses will prolong the time required for shrinkage cracks in the CTB to propagate to the pavement surface, while thicker CTB layers may limit the degree to which faulting occurs across shrinkage cracks. In pavements constructed in frost-affected areas, increased AC and CTB layer thicknesses can also reduce the penetration of frost into underlying layers and thereby minimize the occurrence of frost heave and thaw weakening, which are both potential causes of 17

29 pavement roughness in cold regions. For these reasons, evaluation of roughness development in asphalt pavements constructed using CTB layers warrants consideration of factors such as air freezing index, AC layer thickness, CTB layer thickness, cement content, and traffic loads. The universal measure of roughness is IRI, which has been defined as follows (29, p. 399): The IRI summarizes the longitudinal surface profile in the wheelpath and is computed from surface elevation data collected by either a topographic survey or a mechanical profilometer. It is defined by the average rectified slope (ARS), which is a ratio of the accumulated suspension motion to the distance traveled obtained from a mathematical model of a standard quarter car traversing a measured profile at a speed of 50 mph. IRI is measured in meters per kilometer, with higher IRI values corresponding to rougher pavements. Table 3.1 relates specific IRI values to roughness condition categories on interstate facilities (31). As previously stated, the overall purpose of this part of the research was to investigate the relative impact of cement content on roughness development in asphalt pavements constructed using CTB layers. Because several parameters influence the performance of a CTB, including cement content, aggregate type, layer thickness, traffic loads, environmental conditions, and pavement age, statistical procedures were utilized to identify those factors that were most correlated to the observed pavement performance. The following sections describe the procedures utilized in the roughness evaluation of the selected LTPP program sites, present the results, and summarize the research findings. TABLE 3.1 Pavement Roughness Threshold Values (31) Condition Term IRI (m/km) Very Good <0.95 Good Fair Mediocre Poor >

30 3.2 PROCEDURES The IRI data provided in DataPave included five roughness measurements in each of the left and right wheel paths of the LTPP test lane, which was 152 m in length, for a given pavement section on a given date. In this research, these values were averaged together to obtain just one average IRI value for each date. Because of the large amount of IRI data available, the results were categorized by cement content for presentation and analysis. Seven categories were thus created, with each one representing a different cement content between 3.0 and 9.0 percent, where cement content is defined as the mass of cement specified as a percentage of the dry weight of the aggregate. The actual cement content for each site was rounded down to the nearest whole number for categorization. The age of each pavement test section at the time of each roughness evaluation was determined to facilitate comparison of different pavement structures at the same age. The age, in years, was determined by subtracting the construction date from the roughness measurement date. The ages of the pavement sections at the time of IRI measurement ranged from 0 to 35 years for the sites included in this research. Cumulative KESALs from the time of construction to the time of each roughness evaluation were also computed for each site. After the data were collected and categorized, plots depicting the relationship between pavement age and IRI were prepared for each cement content category, and the backward-selection process was used to identify the most significant variables influencing IRI values for development of a best-fit IRI prediction equation. In the backward-selection process, a full model is initially fit, and then the least significant term, where significance is assessed using the adjusted sum of squares, is eliminated from the model. A new model is then fit without the eliminated variable. This process is repeated until all terms in the model have p-values less than 0.15 (32). After the best-fit model was developed, IRI values were predicted for pavement ages of 5, 10, 15, 20, 25, and 30 years using average values of the other prediction variables. Finally, the data were examined to determine typical roughness levels at which transportation agencies decide to initiate maintenance or rehabilitation to improve pavement condition. 19

31 3.3 RESULTS Summaries of pavement test section information are given in Tables 2.1 and 2.2. A summary of the roughness surveys from the LTPP database is given in Appendix A. The average AC and CTB layer thicknesses are 11.8 cm and 20.1 cm, respectively, while the average cement content and air freezing index for the sites are 5.8 percent and 142 Cdays, respectively. Figures 3.1 to 3.7 depict relationships between IRI and pavement age for cement content categories ranging from 3.0 to 9.0 percent, respectively. Although age appears to be a significant factor in the development of roughness in most of the graphs, the importance of other factors was investigated using a backwardselection model development technique that produced an IRI prediction equation based on data from all of the sites. Potential prediction parameters included age, air freezing index, AC thickness, CTB thickness, cement content, and cumulative KESALs International Roughness Index (m/km) CA-8201 MD-2805 CA-8149 CA-8202 NC-2824 VA Age (yr) FIGURE 3.1 Correlation between international roughness index and age for 3 percent cement. 20

32 3.5 International Roughness Index (m/km) CA-2647 VA-1417 VA-2004 CA-7452 CA-2038 CA-2040 CA-2041 NC-1645 WY-2018 WY Age (yr) FIGURE 3.2 Correlation between international roughness index and age for 4 percent cement. 4.0 International Roughness Index (m/km) AR-2042 CA-2004 CA-2051 CA-8151 MS-3090 OR-2002 TX-2176 CA-2053 MS Age (yr) FIGURE 3.3 Correlation between international roughness index and age for 5 percent cement. 21

33 International Roughness Index (m/km) Age (yr) CA-2002 GA-4092 GA-4093 GA-4096 MD-1632 MS-2807 MS-3089 ND-2001 TX-1049 TX-3669 WY-2015 WY-7772 WY-2019 WY-2037 FIGURE 3.4 Correlation between international roughness index and age for 6 percent cement. 2.5 International Roughness Index (m/km) DE-1450 TX-2108 TX-3689 MS-3081 MO-5403 MO Age (yr) FIGURE 3.5 Correlation between international roughness index and age for 7 percent cement. 22

34 3.0 International Roughness Index (m/km) TX-3679 WY-2020 MS-3083 MS-3085 AB Age (yr) FIGURE 3.6 Correlation between international roughness index and age for 8 percent cement International Roughness Index (m/km) WY-2017 AR Age (yr) FIGURE 3.7 Correlation between international roughness index and age for 9 percent cement. 23

35 However, only age, AC thickness, CTB thickness, and cement content proved to be significant predictor variables as shown in Equation 3.1: IRI = t a b c (3.1) where IRI = International Roughness Index, m/km t = age, yr a = AC thickness, cm b = CTB thickness, cm c = cement content, % The p-values associated with this equation are shown in Table 3.2, in which the symbol - represents predictor variables that were removed from the model due to high p-values. Equation 3.1 allows a user to estimate the amount of roughness exhibited by an AC pavement comprised of a CTB layer stabilized with between 3.0 and 9.5 percent cement, AC thickness between 2.8 cm and 26.9 cm, and CTB thickness between 11.7 cm and 41.7 cm at any point in its service life. For this equation, a user would expect to find positive correlations between pavement age and IRI and cement content and IRI and negative correlations between AC thickness and IRI and CTB thickness and IRI. While the first three correlations are correctly represented in Equation 1, the regression analysis suggests that a positive relationship exists between CTB thickness and IRI, meaning that thicker CTB layers are associated with greater roughness. Perhaps the CTB layer thickness is behaving to some degree as a surrogate for traffic volume, for example, which would be expected to be negatively correlated with IRI but is apparently not a significant predictor variable. TABLE 3.2 Significance of Predictor Variables and Roughness Prediction Equation p -Values Age Freezing Index AC Thickness CTB Thickness Cement Content Cumulative KESALs R 2 <

36 To compare the effects of cement content on the rate of roughness development, IRI values were computed for 5, 10, 15, 20, 25, and 30 years of age using the average AC thickness and CTB thickness values of 19.8 cm and 12.0 cm, respectively. The results were plotted as depicted in Figure 3.8, which clearly shows that increasing roughness is associated with increasing time and increasing cement content. The IRI values increase between 32.7 and 37.1 percent over a 30-year period, depending on the cement content, while cement contents of 4, 5, 6, 7, 8, and 9 percent yield average increases in roughness over time of 2.4, 4.7, 7.1, 9.4, 11.8, and 14.2 percent, respectively, compared to the roughness associated with 3.0 percent cement. Finally, Figure 3.9 illustrates the roughness levels of the pavement test sections at the conclusion of the first LTPP construction period, or just before the transportation agencies responsible for the sections decided to initiate maintenance or rehabilitation to improve pavement condition. Only 36 of the 52 sites included in this study had reached International Roughness Index (m/km) Time (yr) 3 % Cement 4 % Cement 5 % Cement 6 % Cement 7 % Cement 8 % Cement 9 % Cement FIGURE 3.8 Roughness development for each cement content category. 25

37 Cement Content (%) Very Good Good Fair Mediocre Poor Roughness Category FIGURE 3.9 Distribution of cement content by roughness category. the second construction period at the time this research was completed. Although the final IRI values of these pavement sections vary between all of the roughness categories, only 3 percent of the sites are classified as poor; nearly 64 percent of the sites are classified as good or very good. These data suggest that transportation agencies typically initiate maintenance or rehabilitation action before pavements decline into a poor classification. 3.4 SUMMARY The purpose of the roughness analyses was to evaluate the relative impact of cement content on roughness development in asphalt pavements constructed using CTB layers. Data collected through the LTPP program were used as the basis for this study, which 26

38 included 52 sites representing 13 different states and one site in Canada. The cement contents among these sites ranged from 3.0 to 9.5 percent. Factors including age, air freezing index, AC layer thickness, CTB layer thickness, cement content, and KESALs were considered in the research. A roughness equation developed in this research for flexible pavements constructed using CTBs indicates that only age, AC layer thickness, CTB layer thickness, and cement content are significant predictor variables. The equation may be utilized to estimate the amount of roughness exhibited by an AC pavement comprised of a CTB layer stabilized with between 3.0 and 9.5 percent cement at any point in its service life. Based on calculations using average values of AC thickness and CTB thickness, IRI increases between 32.7 and 37.1 percent over a 30-year period, depending on the cement content. As cement content increases from 3.0 to 9.0 percent, IRI increases 14.2 percent, on average, over a given time period. Transportation agencies typically initiate pavement maintenance or rehabilitation before pavements deteriorate to a poor roughness classification. Because increasing cement contents are correlated to increasing pavement roughness over time, the use of reduced cement contents may be appropriate in pavement design. 27

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40 CHAPTER 4 CRACKING 4.1 CRACKING OF CEMENT-TREATED BASE LAYERS Cracking is the primary distress type exhibited by flexible pavements constructed with CTBs and can directly influence the development of pavement roughness. Although the thickness of the pavement layers and the environmental conditions and traffic loads to which the pavement is subjected can impact the extent and severity of cracking, the stiffness of the CTB layer itself is probably the most important predictor of cracking. A stiffer layer develops greater tensile stresses at its interface with the underlying layer, leading to increased bottom-up cracking compared to more flexible layers. Furthermore, stiffer layers are usually associated with higher cement contents, which lead to greater shrinkage cracking due to self-desiccation of the layer as the cement hydrates. Four types of cracking were evaluated in this research, including block cracking, fatigue cracking, longitudinal cracking (wheel-path and non-wheel-path), and transverse cracking. Block cracking is typically characterized by the formation of rectangular blocks with sizes ranging from 0.1 m 2 to 9.3 m 2 and is the most common form of pavement distress associated with CTBs (29). Fatigue cracking of an asphalt pavement surface is usually manifest as a series of interconnected cracks resulting from repeated flexure of the AC layer; this form of distress usually occurs in wheel paths, where loads are cyclic in nature, and is often referred to as alligator cracking (29). Cracks that develop parallel to the direction of traffic on a pavement structure are known as longitudinal cracks. While longitudinal cracks frequently occur in wheel paths as a result of heavy traffic loading, they do commonly occur along AC construction joints and in other non-wheel-path locations. Cracks that develop perpendicular to the direction of traffic on a pavement structure and extend across the center line are known as transverse cracks. Transverse cracks in AC layers overlying CTBs often reflect the shrinkage 29

41 cracking pattern within the CTB layer (3), but they can also result from excessive thermal stresses caused by rapid cooling of the AC; in the latter case, they are usually referred to as thermal cracks. As previously stated, the overall purpose of this part of the research was to investigate the relative impact of cement content on cracking in asphalt pavements constructed using CTB layers. Because several parameters influence the performance of a CTB, including cement content, aggregate type, layer thickness, traffic loads, environmental conditions, and pavement age, statistical procedures were utilized to identify those factors that were most correlated to the observed pavement performance. The following sections describe the procedures utilized in the cracking evaluation of the selected LTPP program sites, present the results, and summarize the research findings. 4.2 PROCEDURES Due to inadequacies in the data downloaded from the LTPP database, the research addressing cracking of flexible pavements constructed with CTB layers was limited to 24 LTPP test sites from 11 different states. The cement contents utilized at these sites ranged from 3.5 to 9.0 percent. The pavement sections were located in Arkansas, California, Delaware, Georgia, Maryland, Mississippi, North Carolina, Oregon, Texas, Virginia, and Wyoming. Tables 2.1 and 2.2 indicate the subset of the original data that was used for this chapter. Data were downloaded from the LTPP database for each of the four distress types previously introduced. High, moderate, and low severity distress measurements for each of the LTPP test sections, which were one lane wide and 152 m in length, were then organized in tables corresponding to the date of the measurement. High severity cracking corresponds to mean crack widths greater than 19 mm but may also include cracks less than 19 mm if the cracks are adjacent to moderate or high severity random cracking (26). Cracks with widths between 6 mm and 19 mm or under 6 mm but adjacent to low severity random cracking are considered to be of moderate severity (26). Low severity cracking corresponds to well-sealed cracks of unknown width or cracks with mean widths of 6 mm or less (26). Longitudinal and transverse crack types were reported as crack lengths, while block and fatigue crack types were recorded as crack areas. Typically, 30

42 cracking measurements were taken in late spring, summer, or fall and repeated in approximately 3-year intervals. The age of each pavement section at the time that each distress survey was conducted was determined to facilitate comparison of different pavement sections at the same age. The age, in years, was determined by subtracting the construction date from the distress survey date. The age of the pavement sections at the time of the distress surveys ranged from 0 to 35 years. The total number of KESALs was also calculated for each pavement section by summing all of the KESALs for each section starting from the day of construction and ending on the month that the particular distress survey was performed. After all of the data were organized, the backward-selection process was used to identify the most significant variables influencing cracking values and to develop best-fit distress prediction equations. In the backward-selection process, a full model is initially fit, and then the least significant term, where significance is assessed using the adjusted sum of squares, is eliminated from the model. A new model is then fit without the eliminated variable. This process is repeated until all terms in the model have a p-value less than 0.15 (32). The model that was developed consisted of several possible predictor variables, including age, AC thickness, CTB thickness, cement content, traffic loading in KESALs, and air freezing index. The response variables included in this research consisted of high, medium, and low severity cracking associated with block, fatigue, longitudinal (wheel-path and non-wheel-path), and transverse cracking distress types. Rates of pavement surface deterioration due to cracking could not be explicitly investigated in this research because some distress types commonly convert to other types as the extent and severity of cracking increases. For example, longitudinal cracking found in wheel paths eventually becomes fatigue cracking with time. 4.3 RESULTS Summaries of pavement test section information are given in Tables 2.1 and 2.2. The average AC and CTB layer thicknesses are 12.9 cm and 19.9 cm, respectively, and the average cement content for the sites is 5.8 percent. The average air freezing index is 134 C-days for the sites. A summary of the distress surveys from the LTPP database is 31