Sensitivity Analysis Of Aashto's 2002 Flexible And Rigid Pavement Design Methods

Transcription

1 University of Central Florida Electronic Theses and Dissertations Masters Thesis (Open Access) Sensitivity Analysis Of Aashto's 2002 Flexible And Rigid Pavement Design Methods 2006 Sanjay Shahji University of Central Florida Find similar works at: University of Central Florida Libraries Part of the Civil Engineering Commons STARS Citation Shahji, Sanjay, "Sensitivity Analysis Of Aashto's 2002 Flexible And Rigid Pavement Design Methods" (2006). Electronic Theses and Dissertations This Masters Thesis (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of STARS. For more information, please contact

2 SENSITIVITY ANALYSIS OF AASHTO S 2002 FLEXIBLE AND RIGID PAVEMENT DESIGN METHODS by SANJAY SHAHJI B.E. Mumbai University, 2002 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Civil & Environmental Engineering in the College of Engineering and Computer Science at the University of Central Florida Orlando, Florida Spring Term 2006

3 2006 Sanjay Shahji ii

4 ABSTRACT Over the years pavement design has been based on empirical equations developed from the American Association of State Highway Transportation Officials (AASHTO) road tests. The various editions of the AASHTO pavement design guide have served well for several decades; nevertheless many serious limitations existed for their continued use as the nation s primary pavement design procedure. For example, the traffic loads and truck sizes have increased over the years, the AASHTO design equations were derived based on the climatic conditions present at the Road Tests site, and the issue of aging materials was not addressed in the design. To overcome these limitations AASHTO finally proposed the AASHTO 2002 design guide which is based on mechanistic empirical approach and serves to address the shortcomings and limitations of the earlier empirical design equations developed from the Road Tests. In this report, sensitivity analyses were conducted of the new AASHTO 2002 method for both flexible and rigid pavements, to understand its performance with respect to the various design parameters. Several important design parameters were selected and were varied one at a time and their effect on the pavement distresses was found. The sensitivity analysis included different amount of traffic loads, base materials, base material thicknesses, surface/slab layer thicknesses and subgrade materials. Some of the illogical results obtained from the sensitivity analyses were also addressed.. iii

5 . ACKNOWLEDGMENTS The writer wishes to express his sincere appreciation and gratitude to his major advisor, Dr. Shiou-San Kuo, for his guidance and assistance during investigation and preparation of this research report and for his constant inspiration throughout the graduate program. Special thanks to the other members of the writer s guidance committee Dr. Manoj Chopra and Dr. Hesham Mahgoub. iv

6 TABLE OF CONTENTS LIST OF FIGURES...viii LIST OF TABLES...xiii CHAPTER ONE: INTRODUCTION Problem Statement Thesis Organisation Objective... 3 CHAPTER TWO: LITERATURE REVIEW Introduction AASHTO Design Equations Original AASHTO Design Equations for flexible pavements Original AASHTO Design Equations for Rigid pavements Need for Mechanistic- Empirical Design Mechanistic Empirical Design Models Models for flexible pavement distresses Permanent Deformation in Asphalt mixtures Permanent Deformation in Unbound Materials Permanent Déformation of Total Pavement Structure Fatigue Cracking in Asphalt Mixtures Models for Rigid Pavement Distresses JPCP Cracking Model JPCP Faulting Model CRCP Punchout Model v

7 CHAPTER THREE: AASHTO 2002 DESIGN METHODOLOGY Introduction Pavement Design Components Design Inputs Processing of inputs over design analysis period Pavement Response Model Incremental Distress and Damage accumulation Distress Prediction International Roughness Index (IRI) Bottom-up Fatigue cracking or Alligator cracking Surface-down fatigue cracking or Longitudinal Cracking Thermal Cracking Permanent Deformation Joint Faulting for JPCP Transverse Slab Cracking in JPCP Punchouts in CRCP Design Reliability: CHAPTER FOUR: RESULTS OF SENSITIVITY ANALYSIS Flexible Pavement Sensitivity Analysis Rigid Pavement Sensitivity Analysis Jointed Plain Concrete Pavement (JPCP) Continuous Reinforced Concrete Pavement (CRCP) CHAPTER FIVE: COMPARISON OF METHODS vi

8 CHAPTER SIX: SUMMARY OF RESULT AND CONCLUSION Flexible Pavements Tabulated Results Conclusions on Flexible Pavement Rigid Pavements Tabulated Results (Jointed Plain Concrete Pavement) Conclusions on Jointed Plain Concrete Pavement (JPCP) Tabulated Results (Continuous Reinforced Concrete Pavement) Conclusions on Continuous Reinforced Concrete Pavement (CRCP) APPENDIX: AASHTO 2002 SOFTWARE OUTPUT FOR FLEXIBLE PAVEMENT EXAMPLE LIST OF REFERENCES vii

9 LIST OF FIGURES Figure 1: Terminal IRI vs AADTT Figure 2: AC surface down cracking vs AADTT Figure 3: AC bottom up cracking vs AADTT Figure 4: AC Thermal Fracture vs AADTT Figure 5: Permanent Deformation (AC only) vs AADTT Figure 6: Permanent Deformation (Total Pavement) vs AADTT Figure 7: Permanent Deformation in different pavement layers over the design life Figure 8: Terminal IRI vs AC Layer Thickness Figure 9: AC Surface down cracking vs AC Layer Thickness Figure 10: AC bottom up cracking vs AC layer thickness Figure 11: AC thermal fracture vs Asphalt Layer thickness Figure 12: Permanent Deformation (AC only) vs Asphalt Layer Thickness Figure 13: Permanent Deformation (Total Pavement) vs AC layer thickness Figure 14: Terminal IRI vs Base layer thickness Figure 15: AC surface down cracking vs Base layer thickness Figure 16: AC bottom up cracking vs Base layer thickness Figure 17: AC thermal fracture vs Base layer thickness Figure 18: Permanent Deformation (AC only) vs Base layer thickness Figure 19: Permanent deformation (total) pavement vs Base Layer thickness Figure 20: Terminal IRI vs Base layer modulus Figure 21: AC surface down cracking vs Base layer modulus viii

10 Figure 22:AC bottom up cracking vs Base layer modulus Figure 23: AC thermal fracture vs Base layer modulus Figure 24: Permanent Deformation (AC only) vs Base layer modulus Figure 25: Permanent deformation (Total Pavement) vs Base layer modulus Figure 26: Terminal IRI vs Subbase thickness Figure 27: AC surface down cracking vs Subbase layer thickness Figure 28:AC bottom up cracking vs Subbase layer thickness Figure 29:AC thermal fracture vs Subbase layer thickness Figure 30: Permanent deformation (AC only) vs Subbase layer thickness Figure 31: Permanent deformation (Total Pavement) vs Subbase layer thickness Figure 32: Terminal IRI vs Subbase layer modulus Figure 33: AC surface down cracking vs Subbase layer modulus Figure 34: AC bottom up cracking vs Subbase layer modulus Figure 35: AC thermal fracture vs Subbase layer thickness Figure 36: Permanent deformation (AC only) vs Subbase layer Modulus Figure 37: Permanent deformation (Total Pavement) vs Subbase layer thickness Figure 38: Terminal IRI vs Subgrade modulus Figure 39: AC surface down cracking vs Subgrade Modulus Figure 40: AC bottom up cracking vs Subgrade modulus Figure 41: AC thermal fracture vs Subgrade modulus Figure 42: Permanent deformation (AC only) vs Subgrade modulus Figure 43: Permanent deformation vs Subgrade modulus Figure 44: Sensitivity of Total pavement rutting to Asphalt layer thickeness ix

11 Figure 45: Sensitivity of Total Pavement Rutting with Base thickness Figure 46: Sensitivity of total pavement rutting with the subbase thickness Figure 47: Sensitivity of Terminal IRI with AC layer thickness Figure 48: Sensitivity of Surface down cracking with Asphalt layer thickness Figure 49: Sensitivity of Bottom up cracking vs Asphalt thickness Figure 50: Sensitivity of AC layer rutting with AC layer thickness Figure 51: Sensitivity of Terminal IRI with base layer thickness Figure 52: Sensitivity of Bottom up cracking with base layer thickness Figure 53: Sensitivity of AC rut with base layer thickness Figure 54: Terminal IRI vs AC layer thickness ( for Subgrade Modulus of 5k psi and 10k psi). 96 Figure 55: AC surface down cracking vs AC layer thickness ( for subgrade modulus of 5k and 10k psi) Figure 56: AC bottom up cracking vs AC layer thickness ( for subgrade modulus of 5k and 10k psi) Figure 57: Permanent deformation (AC only) vs AC layer thickness ( for subgrade modululs of 5k and 10k psi) Figure 58: Perm. Deformation (Total Pavement) vs AC layer thickness ( for subgrade modulus of 5k and 10k psi) Figure 59: Sensitivity of Terminal IRI with AADTT Figure 60: Sensitivity of Transverse Cracking with AADTT Figure 61: Sensitivity of Mean Joint Faulting with AADTT Figure 62: Sensitivity of Terminal IRI with Slab thickness Figure 63: Sensitivity of Transverse Cracking with Slab Thickness x

12 Figure 64: Sensitivity of Mean Joint Faulting with Slab Thickness Figure 65: Sensitivity of Terminal IRI with Joint Spacing Figure 66: Sensitivity of Transverse Cracking with Joint Spacing Figure 67: Sensitivity of Mean Joint Faulting with Joint Spacing Figure 68: Sensitivity of Terminal IRI with Dowel Bar Spacing Figure 69: Sensitivity of Transverse Cracking with Dowel Bar Spacing Figure 70: Sensitivity of Mean Joint Faulting with Dowel Bar Spacing Figure 71: Sensitivity of Terminal IRI with Dowel Bar Diameter Figure 72: Sensitivity of Transverse Cracking with Dowel Bar Diameter Figure 73: Sensitivity of Mean Joint Faulting with Dowel Bar Diameter Figure 74: Sensitivity of Terminal IRI with layer 2 (Cement Stabilized base) thickness Figure 75: Sensitivity of Transverse Cracking with Layer 2 (Cement Stabilized) thickness Figure 76: Sensitivity of Mean Joint Faulting with Layer 2 (Cement Stabilized) thickness Figure 77: Sensitivity of Terminal IRI with Layer 3 (Crushed Stone Subbase) thickness Figure 78: Sensitivity of Transverse Cracking with Layer 3 (subbase layer) thickness Figure 79: Sensitivity of Mean Joint Faulting with Layer 3 (Crushed Stone) thickness Figure 80: Sensitivity of Terminal IRI with Subgrade Modulus Figure 81: Sensitivity of Transverse Cracking with Subgrade Modulus Figure 82: Sensitivity of Mean Joint Faulting with Subgrade Figure 83: Effect of Tied/Untied PCC shoulder on Terminal IRI Figure 84: Effect of Tied/Untied PCC shoulder on Transverse Cracking Figure 85: Effect of Tied/Untied PCC shoulder on Mean Joint Faulting Figure 86: Sensitivity of Terminal IRI with Base Modulus xi

13 Figure 87: Sensitivity of Transverse Cracking with Base layer modulus Figure 88: Sensitivity of Mean Joint Faulting with Base layer modulus Figure 89: Sensitivity of Terminal IRI with AADTT Figure 90: Sensitivity of Punchouts with AADTT Figure 91: Sensitivity of Terminal IRI with Slab Thickness Figure 92: Sensitivity of Punchouts with Slab Thickness Figure 93: Sensitivity of Terminal IRI with Base Layer Thickness Figure 94: Sensitivity of Punchouts with Base layer thickness Figure 95: Sensitivity of Terminal IRI with Compacted Subgrade layer thickness Figure 96: Sensitivity of Punchouts with Compacted Subgrade Thickness Figure 97: Sensitivity of Terminal IRI with Percent Steel Figure 98: Sensitivity of Punchouts with Percent Steel Figure 99: Sensitivity of Terminal IRI with Steel Depth Figure 100: Sensitivity of Punchouts with Steel Depth Figure 101: Sensitivity of Terminal IRI with Uncompacted Subgrade Modulus Figure 102: Sensitivity of CRCP Punchouts with Subgrade Modulus Figure 103: Flexible Pavement Design Example xii

14 LIST OF TABLES Table 1 Truck Traffic Classification 1 based on LTPP traffic data Table 2: The average axle spacing for tandem, tridem and quad axles Table 3: List of the parameters used in the sensitivity analyses of Flexible pavement Table 4: List of parameters used for sensitivity analyses of JPCP pavement Table 5: List of parameters used in the sensitivity analyses of CRCP pavement Table 6: Percent Change in Pavement Distresses for changes in AADTT Table 7: Percent Change in Pavement Distresses for changes in AC layer thickness Table 8: Percent Change in Pavement Distresses for changes in Base Layer thickness Table 9: Percent Change in Pavement Distress for changes in Base Layer Modulus Table 10: Percent Change in Pavement Distress for change in Subbase Layer Thickness Table 11: Percent Change in Pavement Distress for change in Subbase Layer Modulus Table 12: Percent Change in Pavement Distress for change in Subgrade Modulus Table 13: Sensitivity Analysis of Pavement Distresses Versus Pavement Design Parameters Table 14: Percentage change in JPCP pavement distresses for change in AADTT Table 15: Percent change in JPCP pavement distresses for change in Slab thickness Table 16: Percent change in JPCP pavement distresses for change in Joint Spacing Table 17: Percentage change in JPCP pavement distresses for change in Dowel bar diameter. 163 Table 18: Percent Change in JPCP pavement distresses for change in Dowel Bar Spacing Table 19: Percentage change in JPCP pavement distresses for change in Layer 2 thickness. 163 Table 20: Percentage change in JPCP pavement distresses for change in Layer 3 thickness. 163 Table 21: Percent Change in JPCP pavement distresses for change in layer 4 Modulus xiii

15 Table 22: Percentage change in JPCP pavement distresses for Tied/Untied PCC Shoulder Table 23: Percentage change in JPCP pavement distresses for change in Base Modulus Table 24: Sensitivity of pavement distresses with change in JPCP pavement design parameters Table 25: Percentage change in CRCP pavement distresses for change in AADTT Table 26: Percentage change in CRCP pavement distresses for change in Slab Thickness Table 27: Percentage change in CRCP pavement distresses for change in Base Layer Thickness Table 28: Percentage change in CRCP pavement distresses for change in Compacted Subgrade Table 29: Percentage change in CRCP pavement distresses for change in Percent Steel Table 30: Percentage change in CRCP pavement distresses for change in Steel Depth Table 31: Percentage change in CRCP pavement distresses for change in Uncompacted Subgrade Modulus Table 32: Sensitivity of pavement distresses with changes in CRCP pavement design parameters xiv

16 CHAPTER ONE: INTRODUCTION 1.1 Problem Statement Earliest years pavement design solely depended on rule-of-thumb procedures based on past experiences. The same thickness was designed for a section of highway even though widely different soils were encountered. From 1920 s to 1940 s engineers made efforts to evaluate the structural properties of soil and correlations were established relating the pavement performance with the subgrade types. In the early 1950 s gear loads imposed by heavy aircrafts and the increased truck traffic necessitated a more rational approach towards the design of pavements. This resulted in the construction of several test roads for the purpose of evaluating the effect of load and materials on pavement design. The Bureau of Public Roads and AASHO as well as many state highway departments have been responsible for several test roads constructed in the United States. These road tests yielded pavement design formulas for the Interstate Highway System that were based on observations of the performance of pavement test sections. With the availability of computers, high speed and memory it was possible to do complex calculations and operations in quick time. This resulted in the development of computer programs and applications for the design of pavements in a more mechanistic way. But theory alone had not proven sufficient to design pavements realistically and there was still a need to rely on observed performance. Therefore, efforts were made to design the pavements in a mechanistic empirical way to realistically predict pavement responses. The AASHTO Joint force on Pavements in cooperation with National Cooperative Highway Research Program (NCHRP) and Federal Highway Authority (FHWA) sponsored the Workshop on Pavement Design in March 1

17 1996 at Irvine California. At the workshop many of the top pavement engineers were charged with identifying the means for developing an AASHTO mechanistic empirical pavement design procedure by Based on the conclusions developed at the March 1996 meeting the Development of the 2002 guide for Design of New and Rehabilitated Pavement Structures was awarded to ERES Consultants Division of Applied Research and Associates Inc. in February This resulted in the development of the new AASHTO 2002 design guide that utilizes existing mechanistic-based models and databases reflecting current state of the art pavement design procedures. A mechanistic- empirical design approach relates an input such as a wheel load to an output or pavement response, such as a stress or strain. The responses are used to predict distress based on laboratory test and field performance data. This was the first pavement design procedure that incorporated both the impact of climate and aging on materials properties in an iterative and comprehensive manner throughout the entire design life. However, prior to the use of this guide in practice it is necessary to investigate and evaluate the pavement response models incorporated in the design guide. This is required so that design guide yields realistic pavement responses for the design inputs. 1.2 Thesis Organization The thesis is organized into six chapters. Chapter 2 includes the literature review related to the various pavement response models for the new AASHTO 2002 design guide. It also includes the design equations used in the earlier AASHTO design guides. 2

18 Chapter 3 includes a very brief summary of the new AASHTO design methodology. It discusses in general the steps involved in the mechanistic empirical design approach for both flexible and rigid pavement designs. Chapter 4 presents the sensitivity analysis of AASHTO 2002 design guide for both flexible and rigid pavements. It includes various design parameters including traffic loads, thicknesses and moduli of pavement components. Chapter 5 presents a design example solved using earlier AASHTO design methods and new AASHTO 2002 design guide, and Chapter 6 presents the results and the conclusions of this research study. 1.3 Objective The report aims at understanding the new AASHTO 2002 pavement design guide by conducting a sensitivity analysis of its mechanistic-empirical design approach for both flexible and rigid pavements. In order to achieve this objective, major pavement distresses were selected and their sensitivity with respect to the design parameters for both flexible and rigid pavement design methods was found. This was done to understand the pavement response models to changes in various design parameters including traffic, layer properties etc. and to check if the pavement response models yielded realistic responses to changes in the design inputs. 3

19 CHAPTER TWO: LITERATURE REVIEW Literature review was conducted through information search using electronic databases and documented publications. This chapter clearly distinguishes the theories and approaches between the old various ( ) design guides and the new 2002 design method. 2.1 Introduction Over the past years, empiricism had played a significant role in the design of road pavements. The thickness of road pavements was based purely on experience. The same thickness was used for pavement design along a highway despite encountering different types of soils along the length of the highway. As experience was gained over a period of years in pavement design, various methods were adopted by different agencies for determining the thickness of pavement under different conditions. From 1958 to 1960 American Association of State Highway Officials (AASHO) sponsored the full-scale road test in Ottawa, Illinois, which yielded pavement design formulas for the Interstate highway system that were based on observations of the performance of pavement test sections. Tests were conducted to determine the effects of a wide range of design factors. Test sections were subjected to thousands of load repetitions before being taken out of the test; surviving test sections received more than a million load applications. The most significant road test finding was that pavement damage was related to the accumulation of axle repetitions of all types, even if ultimate strength of the pavement was not exceeded by any one axle load. In other words, even though the load of an axle passing the pavement was less than the ultimate strength of the pavement, damage to the pavement will still occur on account of the 4

20 repetition of axle load of all types through the pavement. Furthermore the road tests demonstrated that the damage caused by heavier loads is exponentially greater than damage caused by lighter loads. One of the key products of the road test was the concept of load equivalency, which accounts for the effects of the axle loads on pavements in terms of an equivalent single axle load (ESAL). Under this concept the damage imposed by any vehicle is based on its axle weights compared with a standard 18,000 lb axle load. The ESAL values for other axles express their relative effect on pavement wear. If the number and types of vehicles using the pavement can be predicted, then engineers can design the pavement for anticipated number of 18 kips equivalent single axle loads (18 kips ESAL). Virtually, all heavy-duty pavements built in the United States since the mid-1960s have been designed using the principles and formulas developed from the Road Test. The adoption of 20 year design life as the standard for the Interstate system enabled the state highway agencies to design the Interstate Highway Pavements to the same service criteria. On the basis of the information available at that time 20 years was considered a reasonable length of service for such a major highway network and was about as far into the future as designers wished to project traffic growth or extrapolate the road test findings. However, many pavements did not endure 20 years design life and had to undergo some rehabilitation. 2.2 AASHTO Design Equations The empirical design equations developed from the AASHO road tests are discussed in the following sections (Reference: Pavement Analysis and Design, Yuang H Huang (1)): 5

21 2.2.1 Original AASHTO Design Equations for flexible pavements given by The basic equations developed form the AASHO road test for flexible pavements are G t ( ( ) log ( ρ ) ) (2.1) β log W t log ρ β ( ) log SN ( L 1 + L 2 ) ( SN + 1) L 2 ( ) ( ) + ( ) 4.79 log L 1 + L log L 2 (2.2) (2.3) where, G t = logarithm of the ratio of loss in serviceability at time t to the potential loss taken at a point when the terminal serviceability p t is 1.5, or G t = log [(4.2- p t )/ ( )], noting that 4.2 is the initial serviceability for flexible pavements. β = a function of design and load variables that influences the shape of p versus W t curve. ρ = a function of design and load variables that denotes the expected number of load applications to a p t equal to 1.5, while ρ = W t when p t = 1.5. W t = axle load application at the end of time t. p t = serviceability at the end of service time t. L 1 = load on one single axle or a set of tandem axles, in kip. L 2 = axle load, 1 for single axle and 2 for tandem axle. SN = structural number of pavement system, which is computed as; SN = a 1 D 1 + a 2 D 2 + a 3 D 3 6

22 in which a 1, a 2 and a 3 are layer coefficients for the surface, base and subbase, respectively; and D 1, D 2 and D 3 are the thicknesses of the surface, base, and subbase respectively. The procedure is greatly simplified if an equivalent 18 kip (80-kN) single-axle load is used. By setting L 1 = 18 and L 2 = 1 the following equation is obtained as: ( ) 9.36 log SN + 1 log W t18 ( ) log p t ( SN + 1) 5.19 (2.4) in which W t18 is the number of 18-kip single axle load application to time t and p t is the terminal serviceability index. The above equation is applicable only to flexible pavements in the AASHO road test with an effective subgrade modulus of 3000 psi. For other subgrade and environmental conditions, the equation (2.4) is modified to ( ) 9.36 log SN + 1 log W t p t log ( ) log( M 1094 R ) ( SN + 1) 5.19 (2.5) in which M R is the effective roadbed soil resilient modulus. To take local precipitation and drainage conditions into account, the equation of structural number was modified to SN = a 1 D 1 + a 2 D 2 m 2 + a 3 D 3 m 3 (2.6) in which m 2 is the drainage coefficient of base course and m 3 is the drainage coefficient of subbase course. The modified equation is the performance equation which gives the allowable number of 18-kip single-axle load applications W t18 to cause the reduction of PSI to p t. If the predicted number of applications W 18 is equal to W t18 the reliability of design is only 50% because all 7

23 variables in the equation are based on mean values. To achieve a higher level of reliability, W 18 must be smaller than W t18 by a normal deviate Z R as: Z R log W 18 ( ) log( W t18 ) S o (2.7) in which, Z R is the normal deviate for a given reliability R, and S o is the standard deviation. Combining these two equations and replacing (4.2 - p t ) by ΔPSI, equation (2.5) yields log( W t18 ) Z R S o log( SN + 1) ΔPSI log log( M R ) 8.07 ( SN + 1) (2.8) This is the final equation used for flexible pavement design or analysis Original AASHTO Design Equations for Rigid pavements by The basic equations developed from the AASHO road test for rigid pavements are given G t ( ( ) log ( ρ ) ) (2.9) β log W t log ρ β ( ) log D ( L 1 + L 2 ) 5.2 ( D + 1) L 2 ( ) ( ) + ( ) 4.62 log L 1 + L log L 2 (2.10) (2.11) G t = log[(4.5- p t )/( )], where 4.5 is the initial serviceability and 1.5 is terminal serviceability for rigid pavement at the AASHO Road Test, and p t is the serviceability at time t. D = slab thickness in inches. 8

24 Using an equivalent 18 kip single axle load with L 1 = 18 and L 2 = 1 and combining Equations (2.9) through (2.11) it yields, ( ) 7.35 log D + 1 log W t18 ( ) log p t ( D + 1) 8.46 (2.12) In order to account for conditions other than those that existed in the road test, the above equation was modified using experience and theory. The modified equation is given as: log( W t18 ) Z R S o where, ΔPSI log log( D + 1) p t ( D + 1) S c = Modulus of rupture of concrete E c = Modulus of elasticity of concrete k = Modulus of subgrade reaction J = load transfer coefficient C d = drainage coefficient This is the final design equation for rigid pavements. ( ) log ( ) S c C d D J D E c k 0.25 (2.13) 9

25 2.3 Need for Mechanistic- Empirical Design Pavement design methods were constantly updated by the AASHTO through research findings; thus, the most recent AASHTO 2002 design guide was developed based on mechanistic - empirical design approach. The system of highways designed using the earlier AASHTO Design Guide has matured. Some have exceeded 20 years life and other may have been rehabilitated and reconstructed before reaching the design life. Although those pavements performed well, the experience with the interstate pavements has revealed some serious limitations to the design methods, such as shortcoming in the quality of basic design inputs to the design process, problems with the materials and construction control, and an inability to predict how well alternative rehabilitation schemes. The needs for and the benefits of a mechanistically based pavement design procedure were clearly recognized and the AASHTO Joint Task Force on pavements, in cooperation with NCHRP and FHWA, sponsored the workshop on pavement design in March 1996 at Irvine, California. The workshop participants included many top pavement design engineers from United States who were charged with identifying the means for developing an AASHTO mechanistic-empirical design procedure by Based on the conclusions developed at the March 1996 meeting, NCHRP Project 1-37A, Development of the 2002 Guide for the Design of New and Rehabilitated Pavement Structures was awarded to ERES Consultants, division of Applied Research Associates, Inc. in February The project called for the development of a guide that utilized existing mechanistic based models and databases reflecting current state-of- 10

26 the-art design pavement design procedures. This guide addressed all new and rehabilitation design issues and provided an equitable design basis for all pavement types Mechanistic Empirical Design Models This was the first pavement design procedure that incorporated both the impact of climate and aging of materials properties in an iterative and comprehensive manner throughout the entire design life. Most of the existing models have limited usage with equivalent or worst case material properties being used as inputs. When varying material properties and climatic conditions are applied using an incremental damage approach over the design period, some of the models give erroneous results. As a result significant resources are required to modify and adapt these models to work within the incremental damage approach. In addition, the hourly, monthly and annual variations in traffic loadings are superimposed on changes to materials and climate to more realistically reflect the ways in which pavements exist in-service. The performance models (Reference: ERES Design Guide (2)) that have been incorporated in the AASHTO 2002 design guide are: 11

27 2.4.1 Models for flexible pavement distresses Permanent Deformation in Asphalt mixtures The constitutive relationship in this Guide to predict rutting in the asphalt mixtures is based upon a field calibrated statistical analysis using laboratory repeated load permanent deformation tests. This selected laboratory model is: where, ε p a 1 T a 2 N a 3 ε r (2.14) ε = Accumulated plastic strain at N repetitions of load (in/in) p ε = Resilient strain of the asphalt material as a function of mix properties, temperature and time r rate of loading (in/in) N = Number of load repetitions T = Temperature (deg F) a = Non-linear regression coefficients i While statistical relationships evaluated from laboratory repeated load tests on asphalt mixtures were found to be reasonable; field calibration factors, β, were necessary to ascertain the final ri field distress model. The final asphalt rutting equation implemented in the Design Guide is thus of the form: ε p β r1 a 1 ε r T a 2 β r2 N a 3 β r3 (2.15) 12

28 This is a relatively simple equation to use in the implementation process. The final lab expression that was initially selected for the field calibration / validation process was: ε p T N ε r (2.16) Where, the sample size, N = 3476 observations and R 2 = S = 0.321, where S e = Standard error of estimate e S /S = 0.597, where S y = Standard deviation of the y scores e y This model shown in equation (2.16) was based on extensive research work conducted by Ayers (3), Leahy (4) and Kaloush (5) (NCHRP 9-19: Superpave Models ). The national field calibrated model used in the Design Guide was determined by numerical optimization and other modes of comparison to result in national calibration factors of: β = r1 β = 0.9 r2 β = 1.2 r3 This results in the final model as: ε p k T N ε r (2.17) A depth parameter k 1 in Equation (2.17) is introduced to provide as accurate a rut depth prediction model as possible from the following equations: ( ) depth k 1 C 1 + C 2 depth 2 C h ac h ac (2.18) (2.19) 13

29 2 C h ac h ac (2.20) where, k = function of total asphalt layers thickness (h, in) and depth (in) to computational point, to 1 ac correct for the confining pressure at different depths. Equation (2.17) is calibrated from the sample size of 387 observations with R 2 = S = in where, S e = Standard error of estimate e S /S = 0.574, where S y = Standard deviation of y scores e y The rutting model for new pavement systems has been partially calibrated based on 88 LTPP new sections located in 28 states. Time-series data were available for many of the sections, making the total number of 387 field rutting observations Permanent Deformation in Unbound Materials The initial model framework used to predict the permanent deformation in unbound material layers was that proposed by Tseng and Lytton (6). The basic relationship is: ε ο δ a ( N) β 1 ε r e ρ N β ε v h (2.21) where, δ = Permanent deformation for the layer/sublayer (in). a N = Number of traffic repetitions. ε, β, and ρ = Material properties. o 14

30 ε = Resilient strain imposed in laboratory test to obtain the above listed material properties, ε, β, r o and ρ (in/in). ε = Average vertical resilient strain in the layer/sublayer as obtained from the primary response v model (in /in) h = Thickness of the layer/sublayer (in). β = calibration factor for the unbound granular and subgrade materials 1 During the development process and field calibration studies, numerous modifications were necessary to determine a final reasonable calibrated relationship. Changes leading to the elimination of the stress term in the model, major simplifications to the β and ρ equations and an eventual combination of all unbound granular and subgrade materials into one model were accomplished. The modified models developed are: log( β) W c (2.22) log ε ο ε r ( )β b 1 a 1 E r e ρ + 2 ρ 10 9 e β b 9 a 9 E r (2.23) C o ln b 1 a 1 E r b 9 a 9 E r (2.24) β ρ 10 9 C o 1 β (2.25) 15

31 W c E r GWT (2.26) where, W = Water content (%). c E = Resilient modulus of the layer/sublayer (psi). r GWT = Ground water table depth (ft). a 1 = 0.15 b 1 = 0.0 a 9 = 20.0 b 9 = 0.0 The final calibrated model for the unbound granular base is given by: ε ο δ a ( N) β GB ε.r e β ρ N ε v h (2.27) with the national calibration factor of β = being determined, where the sample size N = GB 387 observations, R 2 = S = in where, S e = Standard error of estimate e S /S = where, S y = Standard deviation of y scores e y The final calibrated model for all subgrade soils is as follows: 16

32 ε ο δ a ( N) β SG ε.r e ρ N β ε v h (2.28) with the national calibration factor of β SG = 1.35 being determined. R 2 = N = 387 observations Se = in where, S e = Standard error of estimate Se/Sy = where, S y = Standard deviation of the y scores Both rutting models were calibrated based on 88 Long Term Pavement Performance (LTPP) new sections located in 28 states. Time-series data were available for many of the sections, making the total number of 387 field rutting observations. In addition, comparative studies involving general comparisons of unbound rutting levels for AASHTO Design Guide (current) pavement structures also, provided valuable insight into the final selection Permanent Deformation of Total Pavement Structure The total rutting in the pavement structure is equal to the summation of the individual layer permanent deformation for each season and to estimate the permanent deformation of each individual sublayer, the system verifies the type of layer, applies the model corresponding to the material type of the sublayer and computes the plastic strain accumulated at the end of each subseason. The overall permanent deformation for a given subseason is the sum of the permanent deformation for each individual layer and is mathematically expressed as: 17

33 RD nsublayers i 1 i ε p h i = (2.29) where, RD = Pavement Permanent Deformation nsublayers = Number of sublayers ε p i = Total plastic strain in sublayer i h i = Thickness of sublayer i The Equation (2.29) for total rutting can also be expressed as: RD Total RD AC + RD GB + RD SG (2.30) RD AC, RD GB and RD SG can be found from equations (2.17), (2.27) and (2.28) as discussed earlier Fatigue Cracking in Asphalt Mixtures The most commonly used model form to predict the number of load repetitions to fatigue cracking is a function of the tensile strain and mix stiffness (modulus). Most of relationships available have a common basic structure and are function of the stiffness of the mix and the tensile strain. The commonly used mathematical relationship used for fatigue characterization is given by: 1 N f Ck 1 ε t k 2 k 3 1 E β f1 k 1 ( ε t ) β f2 k 2 k 3 ( E) β f3 (2.31) 18

34 where, N = number of repetitions to fatigue cracking. f ε = tensile strain at the critical location. t E = stiffness of the material. k, k, k = laboratory regression coefficients β, β, β = calibration parameters. f1 f2 f3 C = laboratory to field adjustment factor. The national field calibrated model used in the Design Guide was determined by numerical optimization and other modes of comparison to result in national calibration factors of: β = k 1 * β f1 f1 β = 1.0 f1 β = 1.2 f2 β = 1.5 f3 This results in the following final model as: N f k 1 C 1 ε t E (2.32) Equation (2.32) has the parameter k being introduced to provide a correction for different asphalt layer thickness (h ac ) effects given by a. For the bottom-up cracking : k b. For the top-down cracking ( 1 e h ac) + (2.33) 19

35 k ( 1 e h ac) + (2.34) where, h = Total thickness of the asphalt layers, in. ac The final transfer function to calculate the fatigue cracking from the fatigue damage is expressed as: a. For bottom-up cracking (% of total lane area) : where, (2.35) FC bottom = bottom-up fatigue cracking, percent lane area D = bottom-up fatigue damage C 1 = 1.0 C 1 = -2 * C 2 C 2 = 1.0 C 2 = * (1 + h ac ) Here, N = 461 observations S e = 6.2 percent Se/Sy = b. For top-down cracking (feet/mile); 20

36 (2.36) where, FC top = top-down fatigue cracking, (ft/mile) D = top-down fatigue damage, (ft/mile) Here, N = 414 observations S = e Se/Sy = The fatigue-cracking model for the asphalt concrete mixtures has been calibrated based on 82 LTPP sections located in 24 States Models for Rigid Pavement Distresses JPCP Cracking Model The percentage of slabs with transverse cracks in a given traffic lane is used as a measure of transverse cracking and is predicted using the following model for both bottom up and top down crackings: CRK FD 1.68 (2.37) where, CRK = predicted amount of top down or bottom-up cracking (fraction) 21

37 FD = Calculated fatigue Damage Model Statistics are: R 2 = 0.68 N = 521 observations SEE = 5.4 percent The total amount of cracking is determined as follows: ( ) 100 TCRACK CRK Top_down + CRK Bottom_up CRK Top_down CRK Bottom_up % (2.38) where, TCRACK = Total Cracking (percent) CRK Bottom_up = Predicted amount of Bottom Up cracking (Fraction) CRK Top_down = Predicted amount of Top Down cracking (Fraction) The JPCP transverse cracking model was calibrated based on performance of 196 field sections located in 24 States JPCP Faulting Model The faulting models for Rigid JPCP pavement is as follows Fault m m p_ ΔFault i i = 1 (2.39) ( ) 2 ΔFault i C 34 FAULTMAX i 1 Fault i 1 DE i FAULTMAX i FAULTMAX 0 + C 7 DE j log 1 + C EROD i = 1 m ( ) C 6 (2.40) (2.41) 22

38 FAULTMAX 0 ( ) log C 12 δ curling log 1 + C EROD P 200 WetDays p s C 6 (2.42) where, Fault m = mean joint faulting at the end of the month, in ΔFault i = incremental change (monthly) in mean transverse joint faulting during month i, in. FAULTMAX i = Maximum Mean Transverse Joint Faulting for month i, in FAULTMAX O = initial maximum mean transverse joint faulting, in EROD = Base/Subbase erodibility factor DE i = differential deformation energy accumulated during month i δ curling = maximum mean monthly slab corner upward deflection PCC due to temperature curling and moisture warping Ps = overburden on subgrade, lb. P 200 = percent subgrade material passing #200 sieve WetDays = average annual number of wet days (greater than 0.1 in of rainfall) C 1 through C 8 and C 12 and C 34 are national calibration constants: C 12 C 1 + C 2 FR 0.25 C 34 C 3 + C 4 FR 0.25 C C C C C C C

39 FR = base freezing index defined as percentage of time the top base temperature is below freezing (32 o F) temperature. Model Statistics are: R 2 = 0.71 SEE = inches N = 564 observations The JPCP transverse joint faulting model is a result of the calibration based on performance of 248 field sections located in 22 States and is applicable for both doweled and undoweled JPCP CRCP Punchout Model CRCP punchout are predicted using a calibrated model, which predicts punchouts as a function of accumulated fatigue damage due to top-down stresses in transverse direction. The nationally calibrated model is as follows: PO A 1 + α FD β (2.43) where, PO = total predicted number of punchouts per mile FD = accumulated fatigue damage at the end of the y th year A, α, β = calibration constants (105.26, 4.0, respectively) Model Statistics: R 2 = 0.67 SEE = 4.73 punchouts per mile N =

40 The CRCP punchout model was calibrated based on performance of 74 field sections from 23 states. The greatest challenge was to calibrate the mechanistic-based conceptual models with nationally available field performance data. This had never been successfully accomplished before nationally. After the theoretical distress models were formulated they were compared and calibrated against the observed data. The results were then evaluated which lead to improvements to the model, which in turn required another time consuming calibration. This process was repeated many times to achieve each of the final acceptable mechanistic based distress prediction models. After model calibration was completed, design reliability was incorporated into the design procedure by considering the residual between the observed and predicted distress. The complex models and the design concepts were finally incorporated into a user friendly software package. The software package includes climatic database containing an hourly climatic data from over 800 locations in North America, which allows the user to easily select a given station or to generate virtual weather stations. Another very important feature of the design procedure and software is that improvements can be made over time in a piecewise manner to any of the component models and incorporated into the procedure for recalibration. Ranges and default values of design inputs can be set by local agencies. According to the results of sensitivity analysis of the AASHTO 2002 design guide conducted by Masad (7), the base modulus and thickness have significant influence on the international roughness index and the longitudinal cracking. However, the base material properties have almost no influence on the permanent deformation of the pavement. 25

41 The AASHTO 2002 design guide software is relatively complex and required a longer time to run. On an average the run time for a 4 - layered flexible pavement system it took about twenty five (25) minutes and for a rigid pavement system it took about seven (7) minutes. These run times resulted with a computer configuration of Intel(R) Pentium (R) M processor 1.50 GHz with 1.0 GB RAM. 26

42 CHAPTER THREE: AASHTO 2002 DESIGN METHODOLOGY 3.1 Introduction The AASHTO 2002 Design Guide is based on mechanistic empirical approach to pavement design. The design procedure in this guide contributes a major improvement from the existing empirical design procedure. The procedures in this guide has the capability to both structurally and climatically model the pavement structure using mechanistic principles and requires a much more comprehensive input data for analysis. These procedures have been calibrated using design inputs and performance data largely from the national LTPP database which includes sections located throughout significant parts of North America. The mechanistic empirical design requires an iterative hands-on approach by the designer. The designer must first establish a performance criterion, then select a trial design, and finally analyze the design in detail to see if it meets the established performance criteria. If the trial design does not meet the performance criteria, the design is then modified and reanalyzed until the design does satisfy all criteria. The designs that meet the applicable criteria are considered feasible from structural and functional viewpoint. The major steps in the design process according to this design guide can be summarized as follows: 1. Assemble a trial design for specific site conditions define pavement layer material properties, traffic loads, climate, pavement type and design and construction features. 2. Establish criteria for acceptable pavement performance at the end of the design period. (i.e. acceptable levels of rutting, fatigue cracking, thermal cracking, faulting, punchouts, IRI etc.) 27

43 3. Select the desired level of reliability for each of the performance indicators. 4. Process input to obtain monthly values of traffic inputs and seasonal variations of material and climatic inputs needed in the design evaluations for the entire design period. 5. Compute structural responses (stresses and strains) using multilayer elastic theory or finite element based pavement response models for each axle type and load and for each damage calculation increment throughout the design period. 6. Calculate the accumulated distress and/or damage at the end of the each analysis period for the entire design period. 7. Predict key distresses at the end of the analysis period throughout the design life using the calibrated mechanistic empirical performance models provided in the guide. 8. Predict smoothness (IRI) as a function of initial IRI, distresses that accumulate over time, and site factors at the end of each time increment. 9. Evaluate the expected performance of the trial design at the given reliability level. 10. If the trial design does not meet the performance criteria, modify the design and repeat steps 4 through 9 above until the design does meet the criteria. 3.2 Pavement Design Components Design Inputs The ASHTO 2002 design procedure has the capability to consider a wide range of structural sections. The designer must provide inputs for the project site conditions including subgrade properties, traffic and climatic data as well as several design inputs related to 28

44 constructions such as the initial smoothness (IRI), estimated month of construction, and estimated month that the pavement will be opened to the traffic. For the convenience of the designer the design inputs are divided into three different levels of data quality. Level 1 refers to the site and/or material specific inputs obtained through direct testing or measurements. Level 2 - refers to the use of correlations to establish and determine the required inputs. Level 3 - refers to the use of national or regional default values to define the input. Most of the design inputs considered in sensitivity analysis done in this report are level 3 inputs. The input level for a particular parameter is decided based on the criticality of the project, sensitivity of the pavement performance to the given input, the information available at the time of the design and also the resources and the time available to the designer to obtain the input. Sensitivity analysis can be used to determine which parameter should be determined more precisely for a given project Processing of inputs over design analysis period Seasonal values of traffic, material and climatic inputs are needed for each analysis increment in the design evaluations. These are obtained by processing the raw design inputs which is automated in the design guide software and the processed inputs are then directly fed in to the structural response calculation modules that compute critical pavement responses on a period by period basis over the entire design period. 29