This study explores the role of nanomaterials in the performance of asphalt binders and mixtures. Two commonly available nanomaterials, i.e., nanosilica (NS) and nanoalumina (NA), were used at contents of 0%, 2%, 4%, 6%, and 8% by weight of asphalt binder. A set of experiments was carried out at the binder level to investigate properties such as penetration, softening point, aging-related mass loss, nanomaterial dispersion (storage stability), and workability (rotational viscosity). In addition, the suitability of NS and NS was also assessed through the testing of nanomodified asphalt mixtures, which focused on Marshall properties, the resilient modulus, moisture susceptibility, permanent deformation, and fatigue resistance. The findings in

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Improving the permanent deformation resistance of asphalt pavements is a vital challenge. Nanomaterials have emerged as promising additives due to their ability to enhance the binder stiffness and elasticity. This study evaluated the influence of five nanomaterials, namely Nano-Silica (NS), Nano-Alumina (NA), Nano-Zinc (NZ), Nano-Titanium (NT), and Carbon Nanotubes (CNTs) incorporated into a base asphalt binder at varying dosages, with up to 10% for NS, NA, and NT, and up to 5% for NZ and CNT. Fifteen modified binders were assessed using the Multiple Stress Creep Recovery (MSCR) test to obtain non-recoverable creep compliance (Jnr), while the corresponding hot mix asphalt samples underwent repeated load testing and rut depth predict

Background: Studying and investigating the transverse strength(Ts), impact strength(Is), hardness (Hr) and surface roughness(Ra) of conventional and modified autopolymerizing acrylic resin with different weight percentages of biopolymer kraftlignin, after curing in different water temperatures; 40°C and 80°C. Material and Methods: Standard acrylic specimens were fabricated according to ADA specification No.12 for transverse strength, ISO 179 was used for impact testing, Shore D for hardness and profilometerfor surface roughness. The material lignin first dispersed in the monomer, then the powder PMMA is immediately added. Ligninadded in different weight percentages. Then cured using pressure pot (Ivomet) in two temperatures;40°C a

Increasing material prices coupled with the emission of hazardous gases through the production and construction of Hot Mix Asphalt (HMA) has driven a strong movement toward the adoption of sustainable construction technology. Warm Mix Asphalt (WMA) is considered relatively a new technology, which enables the production and compaction of asphalt concrete mixtures at temperatures 15-40 °C lower than that of traditional hot mix asphalt. The Resilient modulus (Mr) which can be defined as the ratio of axial pulsating stress to the corresponding recoverable strain, is used to evaluate the relative quality of materials as well as to generate input for pavement design or pavement evaluation and analysis. Based on the aforementioned preface, it is

Affinity is a term used to describe the amount of the adhesion bond between asphalt binder and aggregate. Adhesion force may be used as indicator to the amount of energy or work required to breakdown the adhesive bond between asphalt binder and aggregate. In order to study affinity between asphalt binder and aggregate, a modified device is manufacture locally similar to Rolling Bottle Test (RBT) to Predicted the degree of affinity between asphalt binder and aggregate; taking into consideration mineral composition with physical properties of asphalt binder to measure required force to separate asphalt binder from aggregate surface. In this study, suggest new parameters to represent the stripping or affinity phenomena (aff