2appendices_PP

4.0 Overview of Distress Based Rigid Pavement Smoothness/Serviceability Models Developed from Previous Research

Several research studies have successfully modeled smoothness or serviceability (which is highly correlated to smoothness) using key pavement distress types for both JPCP and CRCP.^{(1, 4, 12)} The results from some of these studies are discussed in the next few sections.

Distress Variables that Influence JPCP Smoothness

AASHO Serviceability Equation

The first relationship between user-defined serviceability and distress was developed by Carey and Irick.⁽¹⁾

PSR = C + A₁R₁ + B₁D₁ + B₂D₂ (1)

where

C, A₁, B₁, B₂ = regression coefficients

R₁ = function of longitudinal profile

D₁ = function of transverse profile

D₂ = function of surface distress

This model form was used to develop the serviceability equations of the AASHO Road Test for both rigid and flexible pavements. The rigid pavement model was as follows.⁽¹⁾

PSR = 5.41 − 1.78 log (1 + SV) − 0.09 (C + P)^0.5 (2)

where

PSI = present serviceability rating (panel mean rating)

SV = slope variance

C = major cracking in ft per 1000 sq ft area

P = bituminous patching in sq ft per 1000 sq ft area

Slope variance is defined as follows:⁽¹⁾

SV = [ΣY² − (1/n)(ΣY)²] / (n − 1) (3)

where

Y = difference between two elevations 9 in apart

n = number of elevation readings

The accuracy of the model can be judged by the following statistics:

R² = 92 percent, SEE = 0.32 PSR points

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Acknowledgment of Sponsorship

This work was sponsored by the American Association of State Highway and Transportation Officials (AASHTO) in cooperation with the Federal Highway Administration and was conducted in the National Cooperative Highway Research Program which is administered by the Transportation Research Board of the National Research Council.

Disclaimer

This is the final draft as submitted by the research agency. The opinions and conclusions expressed or implied in this report are those of the research agency. They are not necessarily those of the Transportation Research Board, the National Research Council, the Federal Highway Administration, AASHTO, or the individual States participating in the National Cooperative Highway Research program.

Acknowledgements

The research team for NCHRP Project 1-37A: Development of the 2002 Guide for the Design of New and Rehabilitated Pavement Structures consisted of Applied Research Associates, Inc., ERES Consultants Division (ARA-ERES) as the prime contractor with Arizona State University (ASU) as the primary subcontractor.

Research into the subject area covered in this Appendix was conducted at ARA-ERES. The author of this Appendix is Mr. Leslie Titus-Glover. Dr. Darter provided technical and managerial coordination of the rigid pavement design group, monitored progress, set schedules and deadlines, and provided periodic technical review of research results as they became available.

Foreword

The appendix describes models developed to predict rigid pavement smoothness (the performance indicator used to characterize overall pavement condition in the Design Guide). Specifically, the models developed and described are for predicting JPCP and CRCP smoothness and are suitable for new JPCP and CRCP design along with rehabilitation with JPCP or CRCP design.

The information contained in this appendix serves as a supporting reference to PART 3, Chapters 4 and 7 of the Design Guide.

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APPENDIX PP

SMOOTHNESS PREDICTION FOR RIGID PAVEMENTS

1.0 Introduction

Rough roads lead to user discomfort, increased travel times, and higher vehicle operating costs that can lead to millions of dollars in losses to the general economy. Although the structural performance of a pavement is most important to highway designers, the complaints generated by rough roads often contribute to a large part of the rehabilitation decisions that are made by State highway agencies.

Smoothness has been used since the AASHO Road Test as a measure of pavement serviceability and, hence, performance. The present serviceability rating (PSR) concept was adopted as a subjective measure of the ability of a pavement to serve the traveling public. For practical purposes, the present serviceability index (PSI) was developed as an objective means of determining performance from physical measurements on the pavement.⁽¹⁾ Although the physical measurements used in computing PSI included distresses such as cracking and patching, it was the longitudinal profile or smoothness of the pavement that provided the major correlation variable. Several studies since the AASHO Road Test have confirmed smoothness as a strong indicator of the serviceability of a pavement, and many State highway agencies rely on smoothness measurement to estimate serviceability over time.^{(2, 3, 4, 5)}

Road smoothness can be defined as "the variation in surface elevation that induces vibrations in traversing vehicles."⁽⁶⁾ Although there are various methods for measuring the smoothness of pavements, one of the most common indices used today is the International Roughness Index (IRI).⁽⁷⁾ IRI is defined simply as the accumulated suspension vertical motion divided by the distance traveled as obtained from a mathematical model of a simulated quarter-car traversing a measured profile at 80 km/h.

As a mathematical index of the longitudinal surface profile of the road in the wheelpaths, IRI represents the typical vibrations induced in a passenger car by the unevenness of the road. It is basically the sum of vertical deviations of the frame of a mathematically defined vehicle over a given distance, measured as meters per kilometer.

IRI was adopted as a standard measure of smoothness for the following reasons:

• It is time stable and can be reproduced easily from longitudinal profile elevation data, since it is just a computed statistic of the road profile.
• It gives consistently high correlations with the outputs of other roughness measuring devices at different speeds.
• It has been shown to correlate well with user serviceability rating.

Following a World Bank study that recommended IRI as a reliable measure of smoothness, the FHWA adopted IRI as a standard for measuring smoothness.^{(8, 9, 10)} Since 1989, FHWA has been requiring all States to report pavement smoothness in terms of IRI units for paved rural arterials and urban freeways, including Interstates.⁽⁷⁾

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2.0 Definition of Problem

The AASHTO design procedure has used pavement serviceability as its sole performance design criterion for nearly 40 years. This situation has had both positive and negative implications on design adequacy. On the positive side, the serviceability concept has ensured that the Nation's pavements are designed to provide the traveling public with a smooth highway. It is also used as a basis for triggering rehabilitation when serviceability is no longer adequate. This contributes to the satisfaction of the public, as well as minimizing highway vehicle operating costs such as fuel and vehicle maintenance costs.

On the negative side, pavement designs based only on serviceability do not directly address prevention of distresses such as fatigue cracking, rutting, joint faulting, and punchouts. Such distresses eventually lead to a decrease in smoothness, making pavements unable to meet the traveling public's need for good ride quality and often leading to the early failure of the pavement. Thus, many pavements designed and constructed based on serviceability have failed early due to a lack of consideration of specific design features and material properties that would have prevented the early failures.

The 2002 mechanistic-empirical (M-E) design procedures to be developed under this contract will result in M-E models for key distress types for flexible and rigid pavements. While such models will be invaluable, they lack the direct consideration of pavement serviceability, which is the most important indicator of the traveling public's satisfaction with the highway.⁽¹¹⁾ Thus, it is highly desirable to also predict pavement smoothness over time so that all performance criteria can be met for a proposed pavement design.

3.0 Alternative Approaches for Including Rigid Pavement Smoothness in the 2002 Design Procedure

There are basically three approaches for including smoothness as a key performance indicator in the 2002 design procedure:

1. Predict the longitudinal wheelpath profile over time using M-E principles. While some work has been performed, current technology and material properties are not available to predict profile over time or axle load applications using the M-E approach. This would involve the prediction of the longitudinal profile (point by point) in a wheelpath over time. It is obvious that this approach cannot be implemented at this time, but it may be possible in the future.
2. Predict smoothness over time as a function of initial smoothness, design features, and site conditions (subgrade, traffic, and climate). This may be possible using an M-E approach; however, it is not believed to be the best approach.
3. Predict smoothness over time as a function of key distress types that can be predicted by M-E or empirical procedures. There are several available models using this approach, which is described in detail.

Following a comprehensive review of past research and smoothness model development efforts, approach 3 was adopted. The distress and maintenance variables included in the final smoothness prediction model were drawn from a large pool of independent distress variables in the LTPP database. The model development process was as follows:

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1. Conduct a literature review of past research studies to identify distress types that influence smoothness.
2. Assemble databases for JPCP and CRCP model development. The databases must include the distress variables identified in step 1.
3. Evaluate the quality of databases and identify missing/erroneous data items.
4. Develop methods and procedures for estimating important missing data elements and clean data by resolving anomalies.
5. Select the appropriate smoothness model form (should be capable of estimating smoothness loss incrementally).
6. Develop tentative smoothness prediction models for JPCP and CRCP.
7. Perform sensitivity analysis (model verification) on tentative models.
8. Select final smoothness models.

The steps outlined for model development are summarized in the flow chart shown in figure 1. This approach has been used in previous studies and has been improved to provide practical prediction models.

Figure 1. Flow chart for developing distress-based smoothness models.

4.0 Overview of Distress Based Rigid Pavement Smoothness/Serviceability Models Developed from Previous Research

Several research studies have successfully modeled smoothness or serviceability (which is highly correlated to smoothness) using key pavement distress types for both JPCP and CRCP.^{(1, 4, 12)} The results from some of these studies are discussed in the next few sections.

Distress Variables that Influence JPCP Smoothness

AASHO Serviceability Equation

The first relationship between user-defined serviceability and distress was developed by Carey and Irick.⁽¹⁾

PSR = C + A₁R₁ + B₁D₁ + B₂D₂ (1)

where

C, A₁, B₁, B₂ = regression coefficients

R₁ = function of longitudinal profile

D₁ = function of transverse profile

D₂ = function of surface distress

This model form was used to develop the serviceability equations of the AASHO Road Test for both rigid and flexible pavements. The rigid pavement model was as follows.⁽¹⁾

PSR = 5.41 − 1.78 log (1 + SV) − 0.09 (C + P)^0.5 (2)

where

PSI = present serviceability rating (panel mean rating)

SV = slope variance

C = major cracking in ft per 1000 sq ft area

P = bituminous patching in sq ft per 1000 sq ft area

Slope variance is defined as follows:⁽¹⁾

SV = [ΣY² − (1/n)(ΣY)²] / (n − 1) (3)

where

Y = difference between two elevations 9 in apart

n = number of elevation readings

The accuracy of the model can be judged by the following statistics:

R² = 92 percent, SEE = 0.32 PSR points

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