In the present work, nanocomposite of poly (vinyl alcohol) (PVA) incorporated with functionalized graphene oxide (FGO) were fabricated using casting method. PVA was dispersed by varying content of FGO (0.3, 0.5, 0.8, 1 wt %). The PVA- FGO nanocomposite was characterized by FT‐IR, FE-SEM and XRD. Frequency dependence of real permittivity (ε’), imaginary (ε’’) and a.c conductivity of PVA/FGO and PVA/GO nanocomposite were studied in the frequency range 100 Hz- 1 MHz. The experimental results showed that the values of real (ε’) and imaginary permittivity (ε’’) increased dramatically by increasing the FGO content in PVA matrix. PVA/ FGO (1 wt %) nanocomposite revealed higher electrical conductivity of 6.4×10-4 Sm-1 compared to

Oil well drilling fluid rheology, lubricity, swelling, and fluid loss control are all critical factors to take into account before beginning the hole's construction. Drilling fluids can be made smoother, more cost-effective, and more efficient by investigating and evaluating the effects of various nanoparticles including aluminum oxide (Al₂O₃) and iron oxide (Fe₂O₃) on their performance. A drilling fluid's performance can be assessed by comparing its baseline characteristics to those of nanoparticle (NPs) enhanced fluids. It was found that the drilling mud contained NPs in concentrations of 0,0.25, 0. 5, 0.75 and 1 g. According to the results, when drilling fluid was used without NPs, the coeff

Stone Matrix Asphalt (SMA) is a gap-graded asphalt concrete hot blend combining high-quality coarse aggregate with a rich asphalt cement content. This blend generates a stable paving combination with a powerful stone-on-stone skeleton that offers excellent durability and routing strength. The objectives of this work are: Studying the durability performance of stone matrix asphalt (SMA) mixture in terms of moisture damage and temperature susceptibility and Discovering the effect of stabilized additive (Fly Ash ) on the performance of stone matrix asphalt (SMA) mixture. In this investigation, the durability of stone matrix asphalt concrete was assessed in terms of temperature susceptibility, resistance to moisture damage, and sensitivity t

 The transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method  local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned m