100% recycled hot mix asphalt lab samples were modified with five generic and one proprietary rejuvenators at 12% dose and tested for binder and mixture properties. Waste Vegetable Oil, Waste Vegetable Grease, Organic Oil, Distilled Tall Oil, and Aromatic Extract reduced the Superpave performance grade (PG) from 94–12 of extracted binder to PG 64-22 while waste engine oil required higher dose. All products ensured excellent rutting resistance while providing longer fatigue life when compared to virgin mixtures and most lowered critical cracking temperature. Rejuvenated samples required more compaction energy compared to virgin and some oils reduced moisture resistance slightly.

Influence of Six Rejuvenators on the Performance Properties of Reclaimed Asphalt Pavement (RAP) Binder and 100% Recycled Asphalt Mixtures

iv FOREWORD The performance of the public service has improved rapidly since the advent of multipartysm in 2003. The change in the fortunes of the public service is the result of a number of factors, among them, the gradual but sustained improvement in the terms of service of public employees across the board, but more significantly, the introduction of a clearly defined and easy to implement performance management system. As a medium for impelling implementation of public policies, projects and programs, the performance contracting system has impelled sustained growth in the performance of all categories of public institutions with only occasional extraneous disruption. The first such disruption was the consequence of the 2007/2008 post election skirmishes, which saw growth in Real GDP falling from 7.1 per cent to 1.7 per cent. This was however, to rise rapidly to 2.8 per cent and 5.6 per cent in the following two years, underscoring the tremendous rebound energy and capacity, engendered by the performance contracting system. The second disruption was driven by external and other factors outside the control of the public service. These included rising inflation, exchange rate depreciation, unusually low rainfall levels leading to drought in some parts of the country, and the rising cost of energy.

Evaluation of performance.

Properly specified pavement deterioration models are an important input for the efficient management of pavements, the allocation of cost responsibilities to various vehicle classes for their use of the highway system, and the design of pavement structures. However, most empirical deterioration progression models developed to date have had limited success. This paper is concerned with the development of an empirical rutting progression model using experimental data. The data used in this paper comprise an unbalanced panel data set with more than 14,000 observations taken from the AASHO Road Test. The salient features of the model specification are (1) the model eschews conventional (predefined) axle load equivalencies and structural numbers in favor of relationships determined entirely by the data itself; (2) a thawing index variable has been incorporated to capture the effects of the environmental factors in the AASHO Road Test; and (3) the model predicts incremental changes in rut depth, which is particularly advantageous in a pavement management context. The specified model is nonlinear in the variables and the parameters and is estimated using both fixed-effects and random-effects specifications to account for unobserved heterogeneity. The estimation results show that the model replicates the pavement behavior well, that the inclusion of an environmental variable is important to avoid biases in other parameters, and that the size of the unobserved heterogeneity nonlinear specification leads to significant differences between parameter estimates among the two wheel paths rutting models.

Development of a Pavement Rutting Model from Experimental Data

Use of recycling agents in asphalt mixtures with high recycled materials contents in the United States: A literature review

Traditional rejuvenators normally have a great deal of heavy fuel oils to supply the light oil component of asphalt binders, which decreases throughout a long-term aging process However, h

Effectiveness of Vegetable Oils as Rejuvenators for Aged Asphalt Binders

Segregation determination in the asphalt pavement is an issue causing many disputes between agencies and contractors. The visual inspection method has commonly been used to determine pavement texture and in-place core density test used for verification. Furthermore, laser-based devices, such as the Florida Texture Meter (FTM) and the Circular Track Meter (CTM), have recently been developed to evaluate the asphalt mixture texture. In this study, an innovative digital image processing approach is used to determine pavement segregation. In this procedure, the standard deviation of the grayscale image frequency histogram is used to determine segregated regions. Linear Discriminate Analysis (LDA) is then implemented on the obtained standard deviations from image processing to classify pavements into the segregated and nonsegregated areas. The visual inspection method is utilized to verify this method. The results have demonstrated that this new method is a robust tool to determine segregated areas in newly paved FC9.5 pavement types.

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Asphalt Mixture Segregation Detection: Digital Image Processing Approach

In recognition of the potential of mechanistic-empirical (M-E) methods in analyzing pavements and predicting their performance, pavement engineers around the country have been advocating the movement toward M-E design methods. In fact, the next AASHTO Guide for Design of Pavement Structures is planned to be mechanistically based. Since many of the performance models used in the M-E methods are laboratory-derived, it is important to validate these models using data from in-service pavements. The Long-Term Pavement Performance (LTPP) program data provide the means to evaluate and improve these models. The fatigue and rutting performances of LTPP flexible pavements were predicted using some well-known M-E models, given the loading and environmental conditions of these pavements. The predicted performances were then compared with actual fatigue cracking and rutting observed in these pavements. Although more data are required to arrive at a more conclusive evaluation, fatigue cracking models appeared to be con...

Evaluation of Mechanistic-Empirical Performance Prediction Models for Flexible Pavements

In light of the data collected under the Seasonal Monitoring Program of the Long-Term Pavement Performance Program, the relationship between climatic factors and pavement structural properties is investigated. Using deflection data collected at a seasonal site over the course of 1 year, layer elastic moduli are backcalculated. The correlations between pavement structural properties (represented by layer elastic moduli) and climatic factors (represented by pavement temperature and moisture conditions) are studied using a series of statistical analyses. Bivariate analysis is used to evaluate linear association between pairs of variables. Principal components analysis is used to identify principal constructs of the system. Multiple regression is used to calibrate linear models. Numerical optimization is used to calibrate nonlinear models that correlate backcalculated layer moduli to pavement temperature. The latter models are then used to derive a temperature correction algorithm of backcalculated asphalt co...

Statistical Analyses of Temperature and Moisture Effects on Pavement Structural Properties Based on Seasonal Monitoring Data

Performance of hot in-place recycled Superpave mixtures in Florida

Raveling is one of the critical modes of failure in open graded asphalt mixtures. The Florida Department of Transportation (FDOT) Districts 4 and 6, located in southeastern Florida, have experienced a large amount of premature raveling with Open Graded Friction Course mixes (OGFC) compared to the other districts in Florida. To investigate the reason of raveling occurrence, the research team devised a data collection tool for smartphones and developed software to measure the raveling area and its location and severity in video images using smartphone GPS capability. The data used in this study were extracted from different FDOT database systems, such as the Laboratory Information Management System (LIMS) and the Electronic Data Management System (EDMS), as well as from the National Oceanic and Atmospheric Administration (NOAA). Ten projects were surveyed by the research team, and numerical raveling statistics were developed and compared with qualitative raveling ratings provided by FDOT. Good correlation was found between the two methods. The comparison was used to establish thresholds of good performance. Such thresholds can be used to develop performance specifications or warranty benchmarks. The relative effects of mix design, construction, and environmental factors were also studied. A project level of analysis was conducted. Several hypotheses were evaluated to determine the cause of premature raveling. Data analysis results indicate significant correlations between raveling and ambient temperature, mix temperature, mix spread rate, and gradation. In light of this study, recommendations were made to enhance the longevity of the OGFC mixtures.

Hesham Ali

Papers

Asphalt Mixture Segregation Detection: Digital Image Processing Approach

Evaluation of Mechanistic-Empirical Performance Prediction Models for Flexible Pavements

Statistical Analyses of Temperature and Moisture Effects on Pavement Structural Properties Based on Seasonal Monitoring Data

Performance of hot in-place recycled Superpave mixtures in Florida

Investigation of pavement raveling performance using smartphone