Evaluation of AASHTO Rigid Pavement Design Model Using Long-Term Pavement Performance Data Base

1996 ◽  
Vol 1525 (1) ◽  
pp. 57-71
Author(s):  
M.I. Darter ◽  
E. Owusu-Antwi ◽  
R. Ahmad
Keyword(s):  
Performance Data ◽  
Pavement Design ◽  
Pavement Performance ◽  
Slab Thickness ◽  
Road Test ◽  
Rigid Pavement ◽  
The Road ◽  
Overall Evaluation ◽  
Axle Loads

The AASHTO design guide's rigid pavement equation that is used for thickness design was originally developed in 1960 at the conclusion of the road test. This equation predicts the number of axle loads for a given slab thickness and loss in serviceability. During the last 30 years, the original equation has been extended to include several additional design factors and has been used by many highway agencies for rigid pavement design. Due to the limited inference space of the original road test equation and the subjective nature of the subsequent extensions, there is considerable interest in determining the adequacy of the equation. The availability of the nationwide long-term pavement performance data has finally made an overall evaluation possible. The evaluation included determining the adequacy of predicting the number of heavy axle loads required to cause a given loss of serviceability. The results indicate that the original 1960 equation generally overpredicts the number of 80-kN (18-kip) equivalent single axle loads for a given loss of serviceability. However, extensions to the original model improve predictions considerably. These results were determined at the 50-percentile (mean) level. At a higher level of reliability such as 95 percent, the 1986 AASHTO model provides a conservative design for a majority of the pavement sections. However, several deficiencies that need to be improved still remain.

Early Evaluation of Long-Term Pavement Performance Specific Pavement Studies-2, Colorado

2000 ◽  
Vol 1699 (1) ◽  
pp. 160-171 ◽  
Author(s):  
Nadarajah Suthahar ◽  
Ahmad Ardani ◽  
Dennis A. Morian
Keyword(s):  
State Standard ◽  
Performance Comparison ◽  
Pavement Performance ◽  
Ride Quality ◽  
Slab Thickness ◽  
Rigid Pavement ◽  
Early Evaluation ◽  
Standard Section ◽  
Aggregate Base

The Long-Term Pavement Performance (LTPP) Program included the construction of rigid pavement sections for evaluation. These test sections, designated Specific Pavement Studies (SPS)-2, were constructed on the basis of an experiment matrix that includes pavement slab thickness [202 mm (8 in.) and 280 mm (11 in.)], base type (permeable asphalt-treated base, lean concrete base, and dense-graded aggregate base), widened lane of 4.27 m (14 ft) and state standard lane of 3.66 m (12 ft), and drainage (with and without pavement edge drains). In addition, a standard Colorado Department of Transportation design section was constructed to provide a performance comparison. The performance of these test sections after 4 years of service is discussed. The results are based on deflection, profile, and distress data collected by the LTPP Program. Virtually no distress and no change in ride quality are evident in these pavement test sections at this time. However, the evaluation of deflection data provides an early indication of anticipated variation in test section performance. Currently, no difference can be identified between the deflection magnitude of the widened-lane section and the state standard section with tied concrete shoulders. However, both these sections exhibit lower deflections at this time than those sections with untied shoulders. High deflections of 202-mm sections indicate that perhaps these sections do not provide adequate structural strength for this roadway.

Use of Long-Term Pavement Performance Data to Develop Traffic Defaults in Support of Mechanistic-Empirical Pavement Design Procedures

2003 ◽  
Vol 1855 (1) ◽  
pp. 176-182 ◽  
Author(s):  
Weng On Tam ◽  
Harold Von Quintus
Keyword(s):  
Pavement Design ◽  
Vehicle Classification ◽  
Pavement Performance ◽  
Traffic Data ◽  
Design Procedures ◽  
Load Spectra ◽  
State Highway ◽  
Pavement Structures ◽  
Empirical Design

Traffic data are a key element for the design and analysis of pavement structures. Automatic vehicle-classification and weigh-in-motion (WIM) data are collected by most state highway agencies for various purposes that include pavement design. Equivalent single-axle loads have had widespread use for pavement design. However, procedures being developed under NCHRP require the use of axle-load spectra. The Long-Term Pavement Performance database contains a wealth of traffic data and was selected to develop traffic defaults in support of NCHRP 1-37A as well as other mechanistic-empirical design procedures. Automated vehicle-classification data were used to develop defaults that account for the distribution of truck volumes by class. Analyses also were conducted to determine direction and lane-distribution factors. WIM data were used to develop defaults to account for the axle-weight distributions and number of axles per vehicle for each truck type. The results of these analyses led to the establishment of traffic defaults for use in mechanistic-empirical design procedures.

Use of Long Term Pavement Performance-Seasonal Monitoring Program Data to Develop and Validate a Generalized Regression Model to Predict the In-Situ Resilient Modulus of Subgrade Soils for Pavement Design and Evaluation

2020 ◽  
Vol 2674 (5) ◽  
pp. 673-684
Author(s):  
Mohamed Elshaer ◽  
Christopher DeCarlo ◽  
Wade Lein ◽  
Harshdutta Pandya ◽  
Ayman Ali ◽  
...  
Keyword(s):  
Prediction Model ◽  
Resilient Modulus ◽  
Monitoring Program ◽  
Pavement Design ◽  
Pavement Performance ◽  
Regression Approach ◽  
Seasonal Monitoring ◽  
Generalized Regression

Resilient modulus (Mr) is a critical input for pavement design as it is the main property used to evaluate the contribution of subgrade to the overall pavement structure. Considering this, practitioners need simple and accurate ways to determine the Mr of in-situ subgrade without the need for expensive and time-consuming testing. The objective of this study is to develop a generalized regression prediction model for in-situ Mr of subgrades, compare it with established prediction models, and assess the model’s predictions on pavement performance using the Mechanistic-Empirical Pavement Design Guide (Pavement ME). The prediction model was built using field data from 30 pavement sections studied in the Long Term Pavement Performance (LTPP) Seasonal Monitoring Program where backcalculated modulus from falling weight deflectometer testing, in-situ moisture contents, and subgrade material properties were considered in the model. Based on the results, it was found that liquid limit, plasticity index, WPI (the product of percent passing #200 and plasticity index), percent coarse sand, percent fine sand, percent silt, percent clay, moisture content, and their respective interactions were significant predictors of in-situ Mr values. The findings showed that the generalized regression approach was able to predict Mr more accurately than predictions from the Witczak model. To assess the application of the predictive model on pavement performance, three LTPP sections located in New York, South Dakota, and Texas were analyzed to predict the rutting performance based on Mr values obtained from the developed generalized prediction model and those obtained from the current Pavement ME model and then compared with rut depths measured in the field. The findings showed that, for coarse-grained subgrades that have a low degree of plasticity, the generalized regression model predicted rutting performance similar to the embedded Pavement ME model. For fine-grained subgrades, the developed model tends to predict lower rut depths which were closer to the field measured rut depths. Overall, the generalized regression approach was successfully applied to create a simple, practical, cost-effective and accurate Mr prediction model that can be used to estimate the stiffness of subgrades when designing and evaluating pavements.

Impact of Changing Traffic Characteristics and Environmental Conditions on Flexible Pavements

2000 ◽  
Vol 1730 (1) ◽  
pp. 125-131 ◽  
Author(s):  
Zhanmin Zhang ◽  
Joseph P. Leidy ◽  
Izydor Kawa ◽  
W. Ronald Hudson
Keyword(s):  
Environmental Conditions ◽  
Trade Agreement ◽  
Design Methods ◽  
Pavement Design ◽  
Road Test ◽  
The North ◽  
Traffic Characteristics ◽  
Axle Loads ◽  
The Impact ◽  
Aasho Road Test

Although the trend for the next generation of pavement design methods is shifting to mechanistic design, the use of design methods based on the AASHO road test results is still the current design practice in Texas and some other states. Critical to these design methods are the AASHTO load equivalency factors (LEFs), which are used to convert the mixed traffic axle loads into standard 18-kip (80.1-kN) equivalent single-axle loads. Several studies have been conducted on the subject of load equivalency for pavement design and analysis. However, there remain uncertainties related to various issues of load equivalency. Over the years, the composition and characteristics of traffic using Texas highways have been changing. The North American Free Trade Agreement has accelerated such changes in that more trucks, primarily moving among mid-western states, Texas, and Mexico, are traveling on Texas highways. In addition, the original AASHO road test was conducted at a site with environmental conditions significantly different from the environmental conditions in Texas. It is therefore critical to understand fully the impact of such changing traffic characteristics and environmental conditions on pavements in Texas. Presented is the methodology used to analyze the impact of these factors on the AASHTO LEFs.

Structural number prediction for flexible pavements using the long term pavement performance data

2018 ◽  
Vol 21 (7) ◽  
pp. 841-855 ◽  
Author(s):  
Hossam S. Abd El-Raof ◽  
Ragaa T. Abd El-Hakim ◽  
Sherif M. El-Badawy ◽  
Hafez A. Afify
Keyword(s):  
Flexible Pavements ◽  
Performance Data ◽  
Pavement Performance
Sign in / Sign up

Export Citation Format

Share Document