The study area soils suffer from several problems appear as tkhesvat and cracks in the roads and waterlogging which reduces the susceptibility of soil to withstand pressure, this study was conducted on the soil of the Karkh district based on field study that included (6) samples of soil physical analyses contain different ratios of (mud, sand, silt) as percentages (52%, 45%, 3 #) respectively, and liquidity limit rate (39%) Stroke rate plasticity was (20.6%) The rate coefficient of plasticity total (19.2%)0
Purepolyaniline and doped with hydrochloric acid was prepared in different molarities at room temperature. The a.c electrical properties were stadied.AC conductivityσac (ω), is found to vary as ωS in the frequency range (100Hz-10MH), S< 1and decreases indicating a dominate hopping process. Thedielectric constant ε1and dielectric loss ε2 have been determined for bulk polyaniline. ε1 decrease with the increase frequency. Electrical conductivity measurements increase with the increases both of the amount of HCl and the dose of radiation. The dielectric investigations show decrease with dose radiation.
In this study, the concentrations of uranium for four species of plants; Spinacia, Brassica Oleracea, BEASSICA Oleracea Var Capitata and Beta Vulgaris were measured in addition to the measurement of uranium concentrations in the selected soil by calculating the number of significant traces of alpha in CR-39. The 2.455 Bq/kg in Spinacia plant were the highest concentration while the lowest concentration of uranium were 1.91 Bq/kg in BEASSICA Oleracea Var Capitata plant. As for the transfer factor, the highest value 0.416 were found in Spinacia plant and the lowest value 0.323 were found in BEASSICA Oleracea Var Capitata plant. The uranium in the models studied in it did not exceed the international limit, according to the International Atomi
... Show MoreA particulate polymer composite material was prepared by reinforcing with the Aluminum Oxide (Al2O3) or Aluminum (Al) metallic particles with a particle size of (30) µm to an unsaturated Polyester Resin with a weight fraction of (5%, 10%, 15%, 20%).
Tensile test results showed the maximum value of elastic modulus reached (2400MPa.) in the case of reinforcing with (Al) particles with weight fraction (20%) and (1500 MPa.) in the case of reinforcing with (Al2O3) particles of the same weight fraction.
When the impact and the flexural strength tests were done, the results showed that flexural strength (F.S), maximum shear stress (τmax), impact strength
... Show MoreThis paper displays a survey about the laboratory routine core analysis study on ten sandstone core samples taken from Zubair Reservoir/West Quarna Oil Field. The Petrophysical properties of rock as porosity, permeability, grain's size, roundness and sorting, type of mineral and volumes of shales inside the samples were tested by many apparatus in the Petroleum Technology Department/ University of Technology such as OFITE BLP-530 Gas Porosimeter, PERG-200TM Gas Permeameter and liquid Permeameter, GeoSpec2 apparatus (NMR method), Scanning Electron Microscopy (SEM) and OFITE Spectral Gamma Ray Logger apparatus. By comparing all the results of porosity and permeability measured by these instruments, it is clear a significant vari
... Show MoreA novel series of mixed-ligand complexes of the type, [ML1(L2)3]Clx [M= Cr(III), Fe(III), Co(II),Ni(II), Cu(II), Cd(II) and Hg(II), n = 2, 3], was synthesized using Schiff base (HL1) as main ligand, nicotinamide (L2) as secondary ligand, and the corresponding metal ions in 1:3:1 molar ratio. The main ligand, HL1 was prepared by the interaction of ampicillin drug and 4-chlorobenzophenone. The synthesized mixed ligand complexes were characterized by elemental analysis, UV-Vis, FT-IR,1H-NMR,13C-NMR and TG/DTG studies. In the mixed-ligand complexes, the Schiff base ligand, HL1 showed coordination to the central metal ion in tridentate manner via azomethine nitrogen, β-lactam ring oxygen and deprotonated carboxylic oxygen atoms, whereas the sec
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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