A mechanistic evaluation of modified asphalt paving mixtures

1994 ◽  
Vol 21 (6) ◽  
pp. 954-965 ◽  
Author(s):  
N. Ali ◽  
Shaher Zahran ◽  
Jim Trogdon ◽  
Art Bergan
Keyword(s):  
Prediction Model ◽  
Pavement Performance ◽  
Pavement Distress ◽  
Modified Asphalt ◽  
Significant Difference ◽  
Actual Field ◽  
Asphalt Paving ◽  
Polymer Modified Asphalt ◽  
Pavement Performance Prediction

The main purpose of this study was to facilitate decisions concerning the effectiveness of modifiers in mitigating pavement distress and improving long-term overall pavement performance in actual field conditions, by utilizing short-term laboratory results and a mathematical prediction model. The modifiers investigated were carbon black, neoprene latex, and polymer modified asphalt (STYRELF). The statistical general linear model (GLM) and the Fisher least significant difference (LSD) were used for the analysis of data. The results of the study indicate that the effect of the modifier on the paving mixture properties was insignificant at low temperatures (down to −17 °C), but significant at high temperatures (up to 60 °C) where the synergistic effect of the modifier on the paving mixture was pronounced. The VESYS IIIA pavement performance prediction model was utilized to assess the effects, if any, of the modifier on the pavement's overall performance. All the modifiers improve, to some degree, the overall pavement performance. Key words: modifiers, asphalt, paving mixtures, pavements, polymer asphalt.

Update of Long-Term Pavement Performance Manual Distress Data Variability: Bias and Precision

1998 ◽  
Vol 1643 (1) ◽  
pp. 71-79 ◽  
Author(s):  
Gonzalo R. Rada ◽  
Chung L. Wu ◽  
Gary E. Elkins ◽  
Rajesh K. Bhandari ◽  
William Y. Bellinger
Keyword(s):  
Data Collection ◽  
Prediction Models ◽  
Survey Methods ◽  
Quality Data ◽  
Pavement Performance ◽  
Pavement Condition ◽  
Pavement Distress ◽  
Black And White ◽  
Pavement Performance Prediction

Pavement distress surveys based upon field interpretation and manual mapping and recording of the distress information on paper forms has been used in the Long-Term Pavement Performance (LTPP) program to collect important pavement condition and distress data. Although this manual method was used in the past as a backup to the 35-mm black and white photographic-based method, recently the use of manual distress survey methods has increased in intensity and coverage. To promote uniformity and consistency of distress data collection, one of the early LTPP efforts was to develop standard definitions, measurement procedures and data collection forms. Various quality control and quality assurance functions have also been implemented to provide for high quality data. However, despite these efforts, manual surveys are still based upon a single rater’s subjective classification of distresses present in the field. Recognizing that rater variability exists, a study was undertaken by FHWA to assess the level of variability between individual distress raters and to address the potential precision and bias. Results from nine LTPP distress rater-accreditation workshops conducted during the period of 1992 to 1996 were used as the source of data. Analyses of those data led to numerous observations and conclusions regarding the bias and precision of LTPP distress data. Because LTPP distress data are to be used in the development of pavement performance prediction models, it is believed that the level of variability found in this study should be reduced to increase its potential usage in the development of such models. A number of recommendations to improve the variability associated with manual distress surveys data are included.

scholarly journals Effect of Different Polymer Modifiers on the Long-Term Rutting and Cracking Resistance of Asphalt Mixtures

Materials ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3359
Author(s):  
Bangwei Wu ◽  
Chufan Luo ◽  
Zhaohui Pei ◽  
Ji Xia ◽  
Chuangchuang Chen ◽  
...  
Keyword(s):  
Asphalt Mixtures ◽  
Bending Test ◽  
Cracking Resistance ◽  
Rutting Resistance ◽  
Modified Asphalt ◽  
Significant Difference ◽  
Polymer Modified Asphalt ◽  
Aging Stage ◽  
Polymer Modifiers

To evaluate the long-term performances of different polymer-modified asphalt mixtures, three modifiers were chosen to modify AC-13 (defined as the asphalt concrete with the aggregate nominal maximum particle size of 13.2 mm); namely, high viscosity modifier (HVM), high modulus modifier (HMM), and anti-rutting agent (ARA). The deformation and cracking resistance of different polymer-modified mixtures were checked at different aging conditions (unaged, short-term aged, and long-term aged for 5, 10, and 15 days respectively). The results of the Hamburg wheel-track test and uniaxial penetration test (UPT) showed that the rutting resistance of all asphalt mixtures changed in a V-shape as the aging progressed. From the unaged stage to the long-term aging stage (5 days), the rutting resistance decreases gradually. While after the long-term aging stage (5 days), the rutting resistance increases gradually. Results from the semicircular bending test (SCB) and the indirect tensile asphalt cracking test (IDEAL-CT) indicated that the cracking resistance of all the mixtures gradually decline with the deepening of the aging degree, indicating that aging weakens the crack resistance of asphalt mixtures. Additionally, test results showed that the rutting resistance of ARA AC-13 (defined as AC-13 containing ARA) is the best, the cracking resistances of ARA AC-13, HMM AC-13 (defined as AC-13 containing HMM) and HVM AC-13 (defined as AC-13 containing HVM) have no significant difference, and different polymer modifiers had different sensitivities to aging due to the polymer content and the type of modifier. The conclusions of this study help to further understand the long-term performance of polymer-modified asphalt mixtures during service life and to help guide the selection of modifiers for mixtures.

Research Progress on Aging of Polymer Modified Asphalt

2011 ◽  
Vol 71-78 ◽  
pp. 5038-5041
Author(s):  
Chang Qing Fang ◽  
Min Zhang ◽  
Jing Bo Hu ◽  
Ying Zhang ◽  
Rui En Yu
Keyword(s):  
Asphalt Pavement ◽  
Present Situation ◽  
Research Progress ◽  
Pavement Performance ◽  
Modified Asphalt ◽  
Aging Mechanism ◽  
Characterization Techniques ◽  
Aging Properties ◽  
Polymer Modified Asphalt ◽  
At Home

Asphalt aging is inevitable to the asphalt pavement performance, which will lead asphalt to hardening gradually and becoming brittle. Therefore, aging progress shortens the life of asphalt, but the study on polymer asphalt improves the phenomenon. The present situation on aging of polymer modified asphalt is summarized and the aging mechanism of modified asphalts is analyzed in the paper. Otherwise, the research progress at home and abroad on the aging properties of modified asphalt is introduced by a series of characterization techniques, which include mechanics technique, rheology technique, FTIR, GPC and so on

scholarly journals A Hybrid Model for Prediction in Asphalt Pavement Performance Based on Support Vector Machine and Grey Relation Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xuancang Wang ◽  
Jing Zhao ◽  
Qiqi Li ◽  
Naren Fang ◽  
Peicheng Wang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Prediction Model ◽  
Performance Prediction ◽  
Asphalt Pavement ◽  
Pavement Performance ◽  
Support Vector ◽  
Grey Relation Analysis ◽  
Relation Analysis ◽  
Pavement Performance Prediction ◽  
Grey Relation

Pavement performance prediction is a crucial issue in big data maintenance. This paper develops a hybrid grey relation analysis (GRA) and support vector machine regression (SVR) technique to predict pavement performance. The prediction model can solve the shortcomings of the traditional model including a single consideration factor, a short prediction period, and easy overfitting. GAR is employed in selecting the main factors affecting the performance of asphalt pavement. The SVR is performed to predict the performance. Finally, the data collected from the weather station installed on Guangyun Expressway were adopted to verify the validity of the GRA-SVR model. Meanwhile, the contrast with the grey model (GM (1, 1)), genetic algorithm optimization BP[[parms resize(1),pos(50,50),size(200,200),bgcol(156)]]081%, −0.823%, 1.270%, and −4.569%, respectively. The study concluded that the nonlinear and multivariate prediction model established by GRA-SVR has higher precision and operability, which can be used in long-period pavement performance prediction.

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.

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