This study investigates the influence of five nanomaterials nano-alumina (NA), nano-silica (NS), nano-titanium (NT), nano-zinc oxide (NZ), and carbon nanotubes (CNT)on enhancing the fatigue resistance of asphalt binders. NA, NS, and NT were incorporated at dosages of 2%, 4%, 6%, 8%, and 10%, while NZ and CNT were added at 1%, 2%, 3%, 4%, and 5%. A series of physical, rheological, and performance-based tests were conducted, including penetration, softening point, ductility, and rotational viscosity. Based on the outcomes of the overall desirability evaluation, the first three dosages of each nanomaterial were selected for further testing due to their superior workability and binder flexibility. Subsequent investigations included the high-temperature performance grade, fatigue parameter (G*.sin δ), Linear Amplitude Sweep (LAS), and IDEAL-CT test integrated with Digital Image Correlation (DIC). The results confirmed that nanomaterial modification significantly enhanced asphalt binder performance, though the effectiveness varied with type and dosage. Physical tests demonstrated improved stiffness, softening point, and reduced temperature susceptibility, with slight ductility losses at higher dosages. Rotational viscosity analysis indicated that low-to-moderate contents ensured workability excluding high CNT dosages which exceeded Superpave limits. High-temperature PG improved notably with NS, NZ, and CNT, while NA and NT showed limited gains. Fatigue parameter results (G*.sin δ) identified NA and NT as the most consistent in reducing cracking susceptibility. LAS testing confirmed superior fatigue lives at optimal dosages of 6% NA, 6% NT, 2% NS, 2% CNT, and 1% NZ, while higher concentrations often caused agglomeration and performance decline. IDEAL-CT and DIC analyses validated these findings by demonstrating increased fracture energy, CT index, and more uniform strain distributions in nano-modified mixtures compared to neat asphalt. FTIR spectra confirmed reduced oxidative aging most prominently with NT and NA while SEM revealed enhanced microstructural cohesion and reduced surface defects. The integration of the Overall Desirability (OD) framework confirmed NT-6 as the most effective dosage, followed by NZ-1 and NS-2, while higher dosages often led to poor compatibility and performance decline. Complementary cost–effectiveness analysis further demonstrated that lower dosages of NZ, NT, and NS achieved the best balance between technical performance and economic viability, whereas excessive CNT and NT contents were not recommended due to unfavorable cost-to-performance ratios. These findings highlight that dosage optimization is critical for translating nanomaterial benefits into practical pavement engineering applications, ensuring enhanced durability with rational investment of resources.
The important aspect of this unconventional approach is that eco-friendly, commercially available and straight forward method was used to prepared Silver Nanoparticles by using AgNO3 and curcumin solution as agent factor. The (TEM), (XRD), and (FTIR) was used to characterise these silver nanoparticles (AgNPs). Two types of bacterial isolates were used to indicate the antibacterial activity silver nanoparticles which prepared by curcumin solution, Gram negative like (Escherichia Coli E. Coli), & Gram positive (Stapha Urous). The results exhibit that silver nanoparticles synthesized by curcumin solution has effective antibacterial activities.
In this research, we did this qualitative and quantitative study in order to improve the assay of aspirin colorimetrically using visible spectrophotometer. This method depends on aqueous hydrolysis of aspirin and then treating it with the ferric chloride acidic solution to give violet colored complex with salicylic acid, as a result of aspirin hydrolysis, which has a maximum absorption at 530nm. This procedure was applied to determine the purity of aspirin powder and tablet. The results were approximately comparative so that the linearity was observed in the high value of both correlation coefficient (R= 0.998) and Determination Coefficient or Linearity (R2= 0.996) while the molar absorpitivity was 1.3× 103 mole
The effect of using grinded rocks of (quartzite and porcelanite) as powder of (10 and 20) % replacement by weight of cement for self-compacting concrete slabs was investigated in this study. Five slabs with 15 concrete cubes were tested experimentally at 28 days to study the compressive strength, ultimate load, ultimate deflection, ductility, crack load and steel strain. The test results show that, the compressive strength improvement when replacement of local rock powder reached to (7.3, 4.22) % for (10 and 20) % quartzite powder and (11.3, 16.1) % for (10 and 20) % porcelanite powder, respectively compared to the reference specimen. The ultimate load percentage increase for slabs with (10 and 20) % rep
... Show MoreA long-span Prestressed Concrete Hunched Beam with Multi-Quadrilateral Opening has been developed as an alternative to steel structural elements. An experimental program was created and evaluated utilizing a single mid-span monotonic static load on simply supported beams, which included six beams with openings and the solid control beam without openings, to investigate the performance of such beams. The number and height of the quadrilateral openings are the variables to consider. According to test results, the presence of openings in the prestressed concrete hunched beam with multi-quadrilateral opening did not considerably affect their ultimate load capacity with respect to a contro
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
... Show MoreAbstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped
... Show MoreThis 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
... Show MoreThe 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
... Show MoreSupport 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
... Show MoreThe study investigated the behaviour of asphalt concrete mixes for aggregate gradations, according to the Iraqi specification using the Bailey method designed by an Excel spreadsheet. In mixing aggregates with varying gradations (coarse and fine aggregate), The Bailey method is a systematic methodology that offers aggregate interlocking as the backbone of the framework and a controlled gradation to complete the blends. Six types of gradation are used according to the bailey method considered in this study. Two-course prepared Asphalt Concrete Wearing and Asphalt Concrete binder, the Nominal Maximum Aggregate Sizes (NMAS) of the mixtures are 19 and 12.5 mm, respectively. The total number of specimens was 240 for both layers (15 samp
... Show More