Sustainable pavements are pavements that meet the requirements of present generation without influencing the capability of the future generation to meet their needs. One of the problems of the warm mix asphalt is that it has low resistance to moisture damage; therefore, the aim of this research paper is to study the possibility of producing more durable warm mixes against the moisture damage with the use of recycled concrete aggregate (RCA) which has not been studied before. Six replacement rates (0, 20, 40, 60, 80, and 100%) for the coarse version aggregate (VA) with RCA were studied. The Marshall mix design method was used to determine the optimum asphalt cement content for each replacement rate. Thereafter, specimens with the optimum asphalt cement content were prepared and tested in the indirect tension test to evaluate their moisture susceptibility. The results revealed that the mixes with higher percentage of RCA possess higher optimum asphalt content. Moreover, an improvement of 13 and 28% in Marshall stability and tensile strength ratio (TSR), respectively, was obtained in case that the VA was entirely replaced by the RCA.
The performance grading system (superpave) has provided means to incorporate binder characteristics with
pavement failure types. It’s a comprehensive system that relates climate, traffic conditions and aging with
critical pavement distress. The objective of this paper is to develop an improved asphalt binder grading
system for Iraq based on the principal of superpave. The country was divided into different zones according
to the highest and lowest temperature ranges and traffic loading. The Performance graded binder proposed
for each zone was compared with some States of USA that have same hot weather of Iraq by using Long
Term Pavement Performance (LTPP v3.1) software. Iraqi asphalt samples were tested using the Supe
Reinforcing asphalt concrete with polyester fibers considered as an active remedy to alleviate the harmful impact of fatigue deterioration. This study covers the investigation of utilizing two shapes of fibers size, 6.35 mm by 3.00 mm and 12.70 mm by 3.00 mm with mutual concentrations equal to 0.25 %, 0.50 % and 0.75 % by weight of mixture. Composition of asphalt mixture consists of different optimum (40-50) asphalt cement content, 12.50 mm nominal aggregate maximum size with limestone dust as a filler. Following the traditional asphalt cement and aggregate tests, three essential test were carried out on mixtures, namely: Marshall test (105 cylindrical specimens), indirect tensile strength test (21 cylindrical specimens)
... Show MoreThe incorporation of recycled concrete aggregate (RCA) into asphalt concrete supports circular economy goals by reducing reliance on virgin materials and minimizing construction waste. However, RCA’s inherent limitations, such as high porosity, microcracking, and poor interfacial bonding, compromise the structural integrity and durability of asphalt mixtures. This study introduces sugarcane molasses (SCM), a naturally derived, carbohydrate-rich byproduct of sugarcane refining, as a novel and eco-friendly surface treatment for RCA aimed at enhancing its compatibility with asphalt binders. SCM was applied at 5-6% by weight of RCA replacing coarse aggregate at varying levels (0-100%) to assess its effect on asphalt mixture performance. A com
... Show MoreThe performance and durability of asphalt pavements are strongly influenced by the rheological properties of asphalt binders, particularly under severe climatic and traffic conditions. This study investigates the synergistic effects of incorporating multi-walled carbon nanotubes (CNTs) at dosages ranging from 0.25% to 1% into AC 40-50 asphalt binders modified with 4% Styrene–Butadiene–Styrene (SBS). A comprehensive experimental program involving physical, rheological, and chemical characterization tests was conducted, including penetration, softening point, viscosity, storage stability, a Dynamic Shear Rheometer (DSR), Multiple Stress Creep Recovery (MSCR), Linear Amplitude Sweep (LAS), Fourier Transform Infrared Spectroscopy (F
... Show MoreRutting 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
... Show MoreTourism is a human phenomenon and economic and social activity. It represents an effective forces in the life of the individuals and state alike. As any other economic and human activity has appositive and negative results.
So there is a necessary to planning and activate this sector to get the most possible advantage.
Tourism has special importance out of its effect on the structure and performance of national economy. It can be regarded a dynamic activity with mutual effect include all the economic activities within and out the state. Tourism is affected and affect the production con summing , joineries , communication , ports ,hotel , restaurants ,internal and
... Show MoreThis quasi-experimental study investigated generative AI (GenAI) tools—Copilot for chemistry and GitHub Copilot for mathematics—on academic achievement and sustainable professional development among 160 undergraduates (40 experimental/control per department) at the University of Baghdad’s Ibn Al-Haitham College of Education for Pure Sciences (2024–2025). Non-random assignment controlled for covariates. Pre/post validated tests (α ≥ .85; 15 MCQ + 5 essay items) measured outcomes. ANOVA revealed significant gains for experimental groups (p < .001, η2 = .41, Cohen’s d = 0.72 [95% CI: 0.45–0.98]). Chemistry excelled in affective domains; mathematics in cognitive/skills. Findings affirm GenAI’s domain-specific efficacy, prov
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