Calibrating the Mechanistic–Empirical Pavement Design Guide Rutting Models using Accelerated Pavement Testing

Author(s):  
Yu Tian ◽  
Jusang Lee ◽  
Tommy Nantung ◽  
John E. Haddock

This paper presents a new method for the local calibration of the rutting models in the Mechanistic–Empirical Pavement Design Guide (MEPDG) for Indiana’s pavements using accelerated pavement testing (APT). The study focused on the verification, calibration, and validation of the rutting models in the MEPDG using both field and APT sections. In this study, a new calibration methodology was developed that uses layer rutting distribution. Also, a procedure was developed to provide the most realistic simulations of APT conditions (climate, traffic, and aging) using virtual weather station data generation, a special traffic configuration, and falling weight deflectometer evaluation. The primary benefits of APT are that it uses test sections with high distress levels and low measurement errors and it provides findings about the contributions of each layer to the total rut depth (i.e., pavement surface rutting). The accuracy of the MEPDG’s rutting prediction models was improved significantly following implementation of the new calibration process. The sum of squared errors (SSE) was reduced by 73% and the standard error of estimates was reduced by 38%. No significant differences were found between the predicted and measured asphalt layer, subgrade, and total rut depths at the 95% confidence level. When compared with the conventional calibration method, which uses the total rut depth without knowing the rut depth of each layer, the proposed method provides more reliable predictions for both asphalt mixture and subgrade rutting, most especially for the latter. The bias and SSE of the predicted subgrade rutting were improved by 46% and 62%, respectively.

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Xinquan Xu ◽  
Yunhong Yu ◽  
Jun Yang ◽  
Chuanhai Wu

In this paper, four antiskidding surface test sections were paved to investigate the long-term skid resistance of the improved dense-graded asphalt concrete in Guangdong Province (GAC) using diabase fine aggregate instead of limestone. Four test sections were tested by the accelerated loading equipment (MLS11, mobile load simulator). The reduction law of the long-term skid resistance of GAC-16 was analyzed based on the accelerated pavement testing results. Prediction models of the GAC-16 skid resistance were also established and verified. The evaluation indexes of the long-term skid resistance of the asphalt pavement were introduced, and the antiskidding durability of different sections was evaluated. Results show that the initial British pendulum number (BPN) and mean texture depth (MTD) of the asphalt pavement cannot completely characterize its long-term skid resistance. With increasing loading cycles, the attenuation law of the BPN and MTD of GAC-16 denotes a fast reduction during the early stage, which gradually stabilizes. The relation between the skid resistance index and accelerated loading cycles was analyzed by nonlinear fitting according to the least-squares-method principle. The attenuation law of the BPN and MTD of GAC-16 with loading cycles was in accordance with the exponential and logarithmic models, respectively. The long-term antiskidding performance of the asphalt pavement could be accurately characterized using a stable BPN, loading cycles while reaching a stable BPN, the initial MTD value, and the MTD reduction rate as the evaluation indexes of the skid resistance of asphalt pavement. Compared with limestone fine aggregate, diabase fine aggregate can improve the long-term skid resistance of the asphalt mixtures.


2019 ◽  
Vol 46 (7) ◽  
pp. 557-566
Author(s):  
Zexin Ma ◽  
Liping Liu ◽  
Yu Yuan ◽  
Lijun Sun

The purpose of this study was to estimate the total fatigue life for in-service asphalt mixture fatigue with in situ accelerated pavement testing (APT) and laboratory four-point bending beam tests. On a selected expressway in Shanghai, China, a series of full-scale APT tests were conducted. During the APT tests, a portable seismic property analyzer was used to monitor the pavement deterioration through modulus reduction. An equivalent factor between the APT loading and equivalent single axle loads (ESALs) was estimated. Additionally, asphalt concrete slabs were cut from the APT test sections and then transferred to the laboratory for four-point bending beam fatigue tests. A new fatigue equation was proposed for the in-service asphalt mixtures. Furthermore, a shift factor between the laboratory fatigue life and field ESAL was recommended. Finally, the field total fatigue life of the in-service asphalt mixture was estimated based on all the work in this study.


Author(s):  
Lucio Salles de Salles ◽  
Lev Khazanovich

The Pavement ME transverse joint faulting model incorporates mechanistic theories that predict development of joint faulting in jointed plain concrete pavements (JPCP). The model is calibrated using the Long-Term Pavement Performance database. However, the Mechanistic-Empirical Pavement Design Guide (MEPDG) encourages transportation agencies, such as state departments of transportation, to perform local calibrations of the faulting model included in Pavement ME. Model calibration is a complicated and effort-intensive process that requires high-quality pavement design and performance data. Pavement management data—which is collected regularly and in large amounts—may present higher variability than is desired for faulting performance model calibration. The MEPDG performance prediction models predict pavement distresses with 50% reliability. JPCP are usually designed for high levels of faulting reliability to reduce likelihood of excessive faulting. For design, improving the faulting reliability model is as important as improving the faulting prediction model. This paper proposes a calibration of the Pavement ME reliability model using pavement management system (PMS) data. It illustrates the proposed approach using PMS data from Pennsylvania Department of Transportation. Results show an increase in accuracy for faulting predictions using the new reliability model with various design characteristics. Moreover, the new reliability model allows design of JPCP considering higher levels of traffic because of the less conservative predictions.


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