The present research had dealt with preparing  bars  with the length of about  (13 cm) and  adiametar  of  (1.5 cm) of composite materials with metal  matrix  represented by (Al-Cu-Mg) alloy cast enforced by (ZrO₂) particles with chosen weight  percentages (1.5, 2.5 ,3.5, 5.5 %). The base  cast and the composite  materials were prepared by casting method by uses vortex  Technique inorder to  fix up (ZrO₂) particles in homogeneous way on  the  base cast. In addition to  that, two main groups of composite materials were prepared depending on the particles size of (ZrO₂) , respectively.       &n

Evaluating a reservoir to looking for hydrocarbon bearing zones, by determining the petrophysical properties in two wells of the Yamama Formation in Siba field using Schlumberger Techlog software. Three porosity logs were used to identify lithology using MN and MID cross plots. Shale volume were calculated using gamma ray log in well Sb-6ST1 and corrected gamma ray in well Sb-5B. Sonic log was used to calculate porosity in bad hole intervals while from density log at in-gauge intervals. Moreover, water saturation was computed from the modified Simandoux equation and compared to the Archie equation. Finally, Permeability was estimated using a flow zone indicator. The results show that the Yamama Formation is found to be mainly limest

Our goal in the present paper is to recall the concept of general fuzzy normed space and its basic properties in order to define the adjoint operator of a general fuzzy bounded operator from a general fuzzy normed space V into another general fuzzy normed space U. After that basic properties of the adjoint operator were proved then the definition of fuzzy reflexive general fuzzy normed space was introduced in order to prove that every finite dimensional general fuzzy normed space is fuzzy reflexive.

Blends of Polymethyl methacrylate (PMMA)/polyvinyl alcohol (PVA) doped with 2% weight percentage of Sn were prepared with different blend ratios using casting technique. The measurements of A.C conductivity σa.c within the frequency range (25kHz – 5MHz) of undoped and Sn doped PMMA/PVA blends obeyed the relationship σ= Aw^s were the value of s within the range 0 > s > 1. The results showed that σa.c increases with the increase of frequency. The exponent s showed preceding increase with the increase of PVA content for PMMA/PVA blends doped with Sn. The dielectric constant, dielectric loss, A.C electrical conductivity are varied with the concentration of PVA in the blend and frequency of applied electrical field.

The products of composites material are very sesetive to many variables, such as manufacturing process, additive materials, …. etc. Filler or additive plays a major role to determine the formation of the properties and behavior of the composites. In this study, polyethylene terephthalate-based compounds were produced and characterized. The work is concerned to prepare samples of Polyethylene terephthalate (PET) - zinc-ferrite (ZnFe₂O₄) with different addition ratio as zinc-ferrite (1, 2, 5, 10, 15 and 20) wt% obtained from mixing the solution with a hot pressing method applied under optimum conditions. The densities of the composites for all samples were calculated. Through the work the diffusion of zinc-ferrite i

High temperature superconductor with nominal composition Bi1.6Pb0.4Sr1.8Ba0.2Ca2 Cu3O10+? was prepared by solid state reaction method. Two sets of samples have been prepared .The first one was quenched in air; the second set was quenched in liquid nitrogen. X-ray diffraction analyses showed an orthorhombic structure with two phases, high –Tc phase (2223) and low-Tc phase (2212) in addition to that impure phase was found. It has been observed that quenched in air samples display a sharp superconducting transition and a higher-Tc phase than that of the quenched in liquid nitrogen samples.

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho