Landfill and incineration are the most common and widely used methods to dispose of solid wastes; both of these techniques are considered the main sources of pollution in the world due to the harmful toxic emissions that are considered an environmental problem. Because of the large areas used by landfills, they are not always considered an economical method. With the increase in the production of solid materials, solid wastes increase the pressure on incinerators and landfills, making the environmental pollution hazard more serious. Instead, these waste materials can be used in some other applications. One of the most important of these applications is asphalt pavements, which are the most used types of pavements in the

The filler in the asphalt mixture is essential since it plays a significant role in toughening and stiffening the asphalt. Changes in filler type can lead the asphalt mixtures to perform satisfactorily during their design life or degrade rapidly when traffic and environmental effects are considered. This study aims to assess the impact of filler types such as limestone dust (LS) and hydrated lime (HL) on Marshall characteristics and moisture damage in asphalt mixtures. Three different percentages of HL were employed in this study to partially replace the LS mineral filler: 1.5, 2.0, and 2.5% by aggregate weight. Furthermore, a control mixture was created with 7% LS by overall aggregate weight for the wearing course layer. The Marsha

Material obtained from the demolition of concrete structures and milling of flexible pavements has the highest potential for recyclability. This study aimed to evaluate the performance of hot mix asphalt with the concurrent use of recycled asphalt pavement (RAP) and recycled concrete aggregate (RCA). Contents of RAP and RCA were varied from 0% to 50% by fixing the total recycling materials percentage to 50%. Penetration grade 40/50 virgin binder and waste engine oil (WEO) as rejuvenator were used in the present study. A series of tests, such as Scanning electron microscopy (SEM), Marshall stability, indirect tensile strength test, IDEAL CT, uniaxial compression test, and resilient modulus test, were carried out to assess the performance of

The performance of flexible pavements is significantly impacted by the permanent deformation (rutting) of asphalt pavements. Rutting shortens the pavement's useful service life and poses significant risks to those using the highway since it alters vehicle handling characteristics.. The aim of this research is to evaluate the permanent deformation of asphalt mixtures under different conditions,to achieve this aim 108 cylindrical specimens has been prepared and tested under repeated loading in uniaxial compression mode. Five factors were considered in this research, these factors represent the effect of environmental condition and traffic loading as well as mixture properties, they include testing temperature, loading condition (stress level

This paper predicts the resilient modulus (Mr) for warm mix asphalt (WMA) mixtures prepared using aspha-min. Various predictor variables were analyzed, including asphalt cement types, asphalt contents, nominal maximum aggregate sizes (NMAS), filler content, test temperatures, and loading times. Univariate and multivariate analyses were conducted to examine the behavior of each predictor variable individually and collectively. Through univariate analysis, it was observed that Mr exhibited an inverse trend with asphalt cement grade, NMAS, test temperature, and load duration. Although Mr increased slightly with higher filler and asphalt content, the magnitude of this increase was minimal. Multivariate analysis revealed that the rate of change

The performance of asphalt pavements is crucial due to heavy traffic loads from civil and industrial developments. Various additives and modifiers are used in flexible roads to improve their resistance to deterioration caused by climatic changes. From this context, modifying the asphalt binder with polymers is popular in asphalt pavement construction. The present research investigates the effect of Polyethylene (PE) polymers in powder form on the characteristics of asphalt mixtures since these polymers are composed of hydrocarbons. It is similar to asphalt binders, making them very effective in enhancing the performance of neat asphalt produced from the oil refinery. To confirm this, two types of PE, High-Density PE (HDPE) and Low-Density P

Moisture induced damage in asphaltic pavement might be considered as a serious defect that contributed to growth other distresses such as permanent deformation and fatigue cracking. This paper work aimed through an experimental effort to assess the behaviour of asphaltic mixtures that fabricated by incorporating several dosages of carbon fiber in regard to the resistance potential of harmful effect of moisture in pavement. Laboratory tests were performed on specimens containing fiber with different lengths and contents. These tests are: Marshall Test, the indirect tensile test and the index of retained strength. The optimum asphalt contents were determined based on the Marshall method. The preparation of asphaltic mixtures involved

One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to stu

Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R