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Publication Number: FHWA-HRT-04-079
Date: July 2006

Seasonal Variations in The Moduli of Unbound Pavement Layers

Chapter 1: Introduction and Research Objectives

INTRODUCTION

Among the more important considerations in pavement design is the fact that the in situ moduli of the pavement layers vary on a seasonal basis, due to variations in the environmental conditions within the pavement structure. For the sections under study in the Seasonal Monitoring Program[ 1 ] of the Long-Term Pavement Performance (LTPP) program, the observed amplitude of seasonal variations in backcalculated moduli for unbound pavement layers, exclusive of frost effects and expressed as a percentage of the minimum observed modulus, ranges from 1 percent to more than 300 percent.

Seasonal variations in pavement layer moduli are important because the deflections, stresses, and strains induced in the pavement by traffic loads, and the resultant incremental damage imparted to the pavement, vary with the moduli of the pavement layers. Unlike most structures, pavements are designed with a finite life expectancy, with design lives greater than 25 to 35 years being the exception, not the rule. The key to cost-effective management of a network of pavements lies in the ability to predict the condition of each pavement at any selected time, and when each will fail (i.e., performance) with a reasonable degree of accuracy and precision. This cannot be achieved without considering the seasonal variations in the pavement layer moduli, and resultant variations in incremental damage.

The work discussed here applied data collected through the Seasonal Monitoring Program of the LTPP program to study the issue of seasonal variations in unbound pavement layers, exclusive of frost effects. Within the Seasonal Monitoring Program, data characterizing both the structural changes in the pavement and the key factors believed to cause those changes are collected monthly. Selected site-specific weather data are collected continuously. The test sections at which these data are collected are geographically dispersed and thus represent a broad array of temperature and moisture conditions prevalent in the United States. Details of test sections and the data used in this investigation are provided in Chapter 3.

RESEARCH OBJECTIVES

The overall goal of this research was to advance the state of the art relative to the estimation of seasonal variations in backcalculated pavement layer moduli for unbound pavement materials under nonfrozen conditions. Four specific objectives, elaborated in the next section, support that goal:

  1. Characterizing the extent of variation in backcalculated pavement layer moduli obtained for the LTPP Seasonal Monitoring test sections.
  2. Evaluating the moisture prediction capabilities of the Enhanced Integrated Climatic Model (EICM).
  3. Developing models to predict backcalculated pavement layer moduli as a function of moisture, stress state, and other pertinent variables.
  4. Demonstrating how the results associated with objectives 1–3 may be applied to estimate backcalculated pavement layer moduli for unbound pavement materials.

RESEARCH APPROACH

This study applied data collected via the Seasonal Monitoring Program of the LTPP program to build upon the foundation embodied in the EICM for the prediction of backcalculated pavement layer moduli for unbound pavement layers under nonfrozen conditions. The overall research approach was comprised of four major tasks:

  1. Assembly, manipulation and assessment of data from the LTPP Seasonal Monitoring Program. This task is the foundation for all subsequent work. In addition to yielding the data sets used in the subsequent analysis, the data assessment element of this task provided more broadly based information on the extent of seasonal variations in pavement layer moduli than has heretofore been available. This information is of value in its own right, and provides a basis for evaluating the outcome of work toward objectives 3 and 4. Task 1 and its outcomes are discussed in detail in Chapter 3.
  2. Evaluation of the moisture-predictive capabilities of the EICM. In this task, LTPP Seasonal Monitoring Program data were applied to evaluate the accuracy of pavement moisture predictions obtained using the EICM. This work was originally undertaken to establish the accuracy of moisture predictions obtained using Version 2.0 of the EICM, and subsequently evolved to include evaluation of Versions 2.1 and 2.6 of the EICM, as well. A detailed discussion of task 2 is in Chapter 4.
  3. Development of models to predict backcalculated layer moduli for unbound materials. This task sought to provide the "missing link" between the moisture predictions obtained with the EICM and the desired end result—estimates of layer moduli on a seasonal basis. A detailed discussion of task 3 is in Chapter 5.
  4. Trial application of the regression models developed in task 3 to demonstrate their use in estimating seasonal variations in unbound pavement layers. In this task, a procedure for applying the outcome of task 3 was proposed and applied to predict pavement layer moduli for several test sections representing varying climatic conditions. The procedures and results obtained in task 4 trial applications are in Chapter 6.

Overall conclusion and recommendations drawn from this study are presented in Chapter 7.

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The Federal Highway Administration (FHWA) is a part of the U.S. Department of Transportation and is headquartered in Washington, D.C., with field offices across the United States. is a major agency of the U.S. Department of Transportation (DOT).
The Federal Highway Administration (FHWA) is a part of the U.S. Department of Transportation and is headquartered in Washington, D.C., with field offices across the United States. is a major agency of the U.S. Department of Transportation (DOT). Provide leadership and technology for the delivery of long life pavements that meet our customers needs and are safe, cost effective, and can be effectively maintained. Federal Highway Administration's (FHWA) R&T Web site portal, which provides access to or information about the Agency’s R&T program, projects, partnerships, publications, and results.
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