The integration of nanomaterials in asphalt modification has emerged as a promising approach to enhance the performance of asphalt pavements, particularly under high-temperature conditions. Nanomaterials, due to their unique properties such as high surface area, exceptional mechanical strength, and thermal stability, offer significant improvements in the rheological properties, durability, and resistance to deformation of asphalt binders. This research reviewed the application of various nanomaterials, including nano silica, nano alumina, nano titanium, nano zinc, and carbon nanotubes in asphalt modification. The incorporation of these nanomaterials into asphalt mixtures has shown potential to increase the stiffness and high-tempera

Hard-grade asphalt binders like AC20-30 typically exhibit excessive stiffness, reduced penetration, and compromised workability, necessitating modification before use in paving applications. This study evaluates the efficacy of regular polyalphaolefin (PAO), a synthetic olefin-based lubricant, as a performance-enhancing modifying agent for such binders. AC20-30 was blended with PAO at dosages ranging from 2 wt.% to 10 wt.%, and the modified binders were characterized via penetration, ductility, softening point, and rotational viscosity measurements, alongside advanced rheological and chemical-morphological analyses. Incorporating PAO in AC20-30 asphalt progressively reduced the binder stiffness and enhanced its flexibility, with all modifie

This research aims to prepare exercises of varying resistances and muscular work exchange for 200m freestyle swimmers, in addition to these exercises’ effects on physical adequacy and the time needed to complete this distance. The experimental method is the basis for the design of the experimental group and the control group of a 100% intentionally chosen sample from a community of  elite-youth swimmers of 200m freestyle swimming for the sport season of 2020-2021 at the Police Sports Club. The sample consists of 15 swimmers that were divided, randomly, into two groups; 7 of them in the experimental group while 8 were in the control group. Physical adequacy was calculated with the use of swimmers’ mechanical energy measurements

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 durability of asphalt concrete is highly dependent on the geometry and mineralogy of coarse aggregates, yet their combined influence on mechanical and moisture resistance properties is still not fully understood. This study evaluates the effects of coarse aggregate geometry, specifically flat and elongated particle ratios and angularity, as well as mineral composition (quartz versus calcite), on asphalt mixture durability. The durability of mixtures was evaluated through Marshall properties as well as moisture susceptibility indicators, including the tensile strength ratio (TSR) and index of retained strength (IRS). Statistical analyses (ANOVA and t-tests) were also conducted to confirm the significance of the observed effects.

Enhancing asphalt binder performance against anticipated distresses is a critical focus in pavement engineering. This study investigates the synergistic influence of nano titanium dioxide (NT) and nano zinc oxide (NZ) on asphalt binder performance. Nine NT:NZ combinations (1:1 to 3:3) were prepared with 1–3% by binder weight, in addition to a reference binder (RB). The performance test program included; conventional tests (penetration, softening point, viscosity, and ductility), Dynamic Shear Rheometer (DSR) for performance grading, Multiple Stress Creep Recovery (MSCR) for rutting evaluation, and Linear Amplitude Sweep (LAS) for fatigue resistance. Furthermore, Statistical analysis (ANOVA) was performed to determine the significa

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca