Moisture-induced damage is one of the primary causes of premature distress in asphalt pavements, leading to reduced service life and increased maintenance costs. Although nanomaterials have shown potential in enhancing asphalt performance, the underlying composite interaction mechanisms among nanomaterials, asphalt binder, and aggregate phases under moisture exposure are still not fully understood. In addition, comparative evaluations under consistent experimental conditions remain limited. This study investigates the influence of five nanomaterials: nano-silica (NS), nano-alumina (NA), nano-titanium dioxide (NT), nano-zinc oxide (NZ), and carbon nanotubes (CNT) on the physical and mechanical properties of asphalt binders and mixtures, with particular emphasis on moisture damage resistance. The nanomaterials were incorporated at dosages of 1.5%, 3.0%, 4.5%, and 6.0% by binder weight. Binder performance was evaluated using conventional and performance grading (PG) tests, while mixture performance was assessed through Marshall properties and moisture susceptibility indicators, including the tensile strength ratio (TSR) and the index of retained strength (IRS). Fluorescence microscopy (FM), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR) were employed to investigate nanomaterial dispersion characteristics, microstructural morphology, and physicochemical interactions within the asphalt composite system. The results indicate that nanomaterial modification reduced penetration and increased softening point and Marshall stability, reflecting enhanced stiffness and thermal resistance, although ductility decreased at higher dosages. Significant improvements in moisture resistance were observed, particularly under conditioned states. The TSR increased from 81.2% for the control mixture to 92.4% for NS and 91.7% for NA, while the IRS improved from 72.7% to 88.5% for NS. Statistical analysis indicated that both nanomaterial type and dosage significantly affected TSR and IRS performance, with dosage exhibiting comparatively greater influence on moisture resistance improvement. FM and SEM analyses revealed comparatively better dispersion and lower agglomeration tendency for NS and NA, which corresponded to their superior moisture resistance performance. FTIR analysis indicated that the modification process was predominantly physical, with no major formation of new chemical functional groups. Among the investigated nano materials, NS at 6% dosage exhibited the most pronounced improvement, followed by NA at similar dosage levels. Overall, the findings suggest that nanomaterial modification can considerably improve the moisture resistance and mechanical performance of asphalt mixtures under laboratory conditions. However, higher nanomaterial dosages may adversely affect binder workability due to increased viscosity, particularly in CNT-modified binders.
This paper has investigated experimentally the dynamic buckling behavior of AISI 303 stainless steel Aluminized and as received long columns. These columns, hot-dip aluminized and as received, are tested under dynamic buckling, 22 specimens, without aluminizing (type 1), and 50 specimens, with hot-dip aluminizing at different aluminizing conditions of dipping temperature and dipping time (type 2), are tested under dynamic compression loading and under dynamic combined loading (compression and bending) by using a rotating buckling test machine. The experimental results are compared with Perry Robertson interaction formula that used for long columns. Greenhill formula is used to get a mathematical model that descripts the buckling behavior
... Show MoreLearning the vocabulary of a language has great impact on acquiring that language. Many scholars in the field of language learning emphasize the importance of vocabulary as part of the learner's communicative competence, considering it the heart of language. One of the best methods of learning vocabulary is to focus on those words of high frequency. The present article is a corpus based approach to the study of vocabulary whereby the research data are analyzed quantitatively using the software program "AntWordprofiler". This program analyses new input research data in terms of already stored reliable corpora. The aim of this article is to find out whether the vocabularies used in the English textbook for Intermediate Schools in Iraq are con
... Show MoreThe Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process
The cytotoxic effect of catechol was examined in two human cancer cell lines, Epidermoid larynx carcinoma (Hep- 2), Cerebral glioblastoma multiforme (AMGM-5) and Murine mammary adenocarcinomacell (AMN3) treated with half concentrations of catechol (1000, 500, 250, 125, 62.5 and 32.25 μM) for 72 hr. The get hold of results showed catechol have a toxic effect of the cell viability of three types of cell lines after 72h of exposure, the toxicity was dependent on catechol concentrations and/or autoxidation for quinines formation, there were a marked decreased of cell viability in a dose dependent manner in all cell line types. Inhibition concentration of catechol for 50% of cell viability (IC50) were calculated, they were at 581.5 μM, 478 μM
... Show MoreThe raw material soil of Al-Sowera factory quarry (quarry soil and mixture) used for building brick industry was tested mineralogically, geochemically and geotechnically. Mineral components of soil are characterized by Clay minerals (Palygoriskite and chlorite) and nonclay minerals like calcite, quratz, feldspar, gypsum and halite. The raw material is deficient in SiO2, Al2O3, K2O, Fe2O3 and MgO, while enriched in CaO. Loss on ignition and Na2O are in suitable level and appear to be concordant with the standard. Grain size analyses show that the decreasing sand and clay, and increasing silt ratio in both quarry soil and mixture caused decreasing in strength of brick during molding and after firing. The quarry soil is characterized by high p
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A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.
Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm3.
The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap
... Show MoreTwo grades of paving asphalt with penetration of 46 and 65 are studied for determining changes in their physical and chemical properties caused by ageing.
The ageing process has been conducted on two petroleum paving asphalt cement using thin film oven test at 150, 163 and 175 C, and ageing time 5, 10,15, 20, 25 and 30 hours. The effect of ageing time and temperature on penetration, kinematic viscosity, softening point, solubility in trichloroethylene, heat loss and changes in chemical composition are investigated. The results of thin film oven test process indicte that the asphaltenes concentration of all aged asphalt increases with increasing ageing time, while the opposite was observed for polar-aromatic and naphthene-aromatic. The
The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre
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