Using Shotblasting Treatment to Improve Asphalt Pavement Friction at the NCAT Test Track

2021 ◽  
Author(s):  
Md. Tanvir Ahmed Sarkar ◽  
Fan Gu ◽  
Michael Heitzman ◽  
Buzz Powell
Keyword(s):  
Asphalt Pavement ◽  
Test Track ◽  
Pavement Friction

Effect of aggregate properties on asphalt pavement friction based on random forest analysis

2021 ◽  
Vol 292 ◽  
pp. 123467
Author(s):  
You Zhan ◽  
Joshua Qiang Li ◽  
Cheng Liu ◽  
Kelvin C.P. Wang ◽  
Dominique M. Pittenger ◽  
...  
Keyword(s):  
Random Forest ◽  
Asphalt Pavement ◽  
Random Forest Analysis ◽  
Aggregate Properties ◽  
Pavement Friction

scholarly journals Asphalt Pavement Friction Coefficient Prediction Method Based on Genetic-Algorithm-Improved Neural Network(GAI-NN) Model

2021 ◽  
Author(s):  
Zhaoyun Sun ◽  
Xueli Hao ◽  
Wei Li ◽  
Ju Huyan ◽  
Hongchao Sun
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Friction Coefficient ◽  
Point Cloud ◽  
Spline Interpolation ◽  
Asphalt Pavement ◽  
3D Point Cloud ◽  
Cloud Data ◽  
Pavement Surface ◽  
Pavement Friction

To overcome the limitations of pavement skid resistance prediction using the friction coefficient, a Genetic-Algorithm-Improved Neural Network (GAI-NN) was developed in this study. First, three-dimensional (3D) point-cloud data of an asphalt pavement surface were obtained using a smart sensor (Gocator 3110). The friction coefficient of the pavement was then obtained using a pendulum friction tester. The 3D point-cloud dataset was then analyzed to recover missing data and perform denoising. In particular, these data were filled using cubic-spline interpolation. Parameters for texture characterization were defined, and methods for computing the parameters were developed. Finally, the GAI-NN model was developed via modification of the weights and thresholds. The test results indicated that using pavement surface texture 3D data, the GAI-NN was capable of predicting the pavement friction coefficient with sufficient accuracy, with an error of 12.1%.

scholarly journals Rutting Performance of Semi-Rigid Base Pavement in RIOHTrack and Laboratory Evaluation

2021 ◽  
Vol 7 ◽  
Author(s):  
Sheng Li ◽  
Mengmeng Fan ◽  
Lukai Xu ◽  
Wendi Tian ◽  
Huanan Yu ◽  
...  
Keyword(s):  
Dynamic Modulus ◽  
Asphalt Pavement ◽  
Asphalt Mixtures ◽  
Rigid Base ◽  
Test Results ◽  
Full Scale Test ◽  
Rutting Resistance ◽  
Test Track ◽  
Dynamic Modulus Test ◽  
Scale Test

Through a simple performance dynamic modulus test (SPT), standard rutting test, Hamburg rutting test, French rutting test and asphalt pavement analyzer rutting test, the rutting resistance of asphalt mixtures in the middle and lower courses of three semi-rigid base asphalt pavement of Beijing full-scale test track road in China was evaluated. The test results show that the rutting resistance of asphalt mixtures of the middle and lower courses can be greatly improved by using low-grade asphalt, especially 30# asphalt. The rutting resistance of SBS modified asphalt mixtures is also better. The SPT dynamic modulus test can indirectly characterize the rutting performance of the asphalt mixture. The rutting test results of a laser road detection vehicle and 3 m ruler show that the asphalt grade has a significant impact on the rutting performance of semi-rigid base asphalt pavement. Compared with 70# asphalt used in the middle and lower courses, the rutting resistance of the pavement structure can be improved by more than 20%. The result also show that the APA rutting test results can closely characterize the full-scale test track results, which is an optimal test method for evaluating the rutting performance of semi-rigid base asphalt pavement. The research results can provide a theoretical basis and reference for the rational design and rutting evaluation of semi-rigid base asphalt pavement.

scholarly journals Deterioration trends of asphalt pavement friction and roughness from medium-term surveys on major Italian roads

2017 ◽  
Vol 10 (5) ◽  
pp. 421-433 ◽  
Author(s):  
Alberti Susanna ◽  
Maurizio Crispino ◽  
Filippo Giustozzi ◽  
Emanuele Toraldo
Keyword(s):  
Asphalt Pavement ◽  
Medium Term ◽  
Pavement Friction

Further Evaluation of Limiting Strain Criteria for Perpetual Asphalt Pavement Design

2017 ◽  
Vol 2640 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Alfredo J. Castro ◽  
Nam Tran ◽  
Mary Robbins ◽  
David H. Timm ◽  
Chris Wagner
Keyword(s):  
Asphalt Concrete ◽  
Asphalt Pavement ◽  
Fatigue Cracking ◽  
Pavement Design ◽  
Threshold Values ◽  
Bottom Up ◽  
Test Track ◽  
Climatic Regions ◽  
Concrete Layer ◽  
Perpetual Pavement

Perpetual asphalt pavements have been designed with single threshold values for the horizontal strains at the bottom of the asphalt concrete layer and for vertical strains on top of the subgrade to prevent the occurrence of bottom-up fatigue cracking and subgrade rutting. Several thresholds have been utilized for design based on laboratory and field test results. Limiting strain distributions were recently proposed for perpetual pavement design instead of single threshold values for controlling the horizontal and vertical strains. These design criteria were developed with data collected from test sections at the National Center for Asphalt Technology pavement test track. The objective of this study was to conduct additional analyses of eight perpetual pavement sections located in different climatic regions, to support the proposed limiting strain criteria. These sections were simulated in the PerRoad perpetual pavement design software to determine the horizontal strains at the bottom of the asphalt concrete layer and the vertical strains on top of the subgrade. The strains were then analyzed to evaluate the proposed limiting strain criteria. Based on the simulations, the limiting horizontal strain distribution above the 60th percentile can effectively differentiate the calculated strain distributions of the eight perpetual pavement sections from those of the test sections that failed due to bottom-up fatigue cracking on the test track. In addition, the calculated vertical strains on top of the subgrade at the 50th percentile were lower than the proposed 200-microstrain limit. These results provide additional support for utilizing the proposed strain criteria in perpetual asphalt pavement design.

scholarly journals Research on the Prediction Model of the Friction Coefficient of Asphalt Pavement Based on Tire-Pavement Coupling

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Miao Yu ◽  
Xinquan Xu ◽  
Chuanhai Wu ◽  
Shanqiang Li ◽  
Mingxia Li ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Prediction Model ◽  
Dynamic Testing ◽  
Asphalt Pavement ◽  
Influence Factors ◽  
Testing System ◽  
Tire Pressure ◽  
Coupling System ◽  
Static Contact ◽  
Pavement Friction

The correlations between pavement texture and tire pressure with the actual tire-road contact area were first investigated according to the tire-road static contact characteristics; on this basis, the influence mechanisms of speed and pavement texture on the pavement friction coefficient were systematically explored from the angle of tire-road coupling system dynamics via the self-developed dynamic testing system of tire-pavement friction. By integrating the above influence factors, the BP neural network method was applied to the regression of the prediction model for the asphalt pavement friction coefficient. Through the comparison between the model measured value and estimated value, their correlation coefficient R2 reached 0.73, indicating that this model is of satisfactory prediction accuracy and applicable to the antiskid design of asphalt pavement.

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