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Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
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It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological properties of water-based drilling fluid using other simple measurable properties. While mud density, marsh funnel, and solid% are key input parameters in this study, the output models are plastic viscosity, yield point, apparent viscosity and gel strength. The prediction methods have been applied on datasets taken from the final reports of two wells drilled in the Ahdeb oil field, eastern Iraq. To test the performance ability of the developed models, two error-based metrics (determination coefficient R2 and root mean square error have been used in this study. The current results support the evidence that MW, MF, and solid% are consistent indexes for the prediction of rheological mud properties. Both mud density and solid content have a relative-significant effect on increasing PV, YP, AV, and gel strength. The results also reveal that both MRA and ANN are conservative in estimating the fluid rheological properties, but ANN is more precise than MRA. Eight empirical mathematical models with high performance capacity have been developed in this study to determine the rheological fluid properties using simple and quick equipment such as mud balance and marsh funnel. This study presents cost-effective models to determine the rheological fluid properties for future well planning in Iraqi oil fields.

Crossref
Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
A Developed Model for Selecting Optimum Locations of Water Harvesting Dams Using GIS Techniques
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An integrated GIS-VBA (Geographical Information System – Visual Basic for Application), model is developed for selecting an optimum water harvesting dam location among an available locations in a watershed. The proposed model allows quick and precise estimation of an adopted weighted objective function for each selected location. In addition to that for each location, a different dam height is used as a nominee for optimum selection. The VBA model includes an optimization model with a weighted objective function that includes beneficiary items (positive) , such as the available storage , the dam height allowed by the site as an indicator for the potential of hydroelectric power generation , the rainfall rate as a source of water . In a

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Crossref
Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Biosorption of Lead, Cadmium and Nickle from Industrial Wast water by Using Dried Macroalgae
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Biosorpion of lead (Pb), Cadmium (Cd) and Nickl(Ni) by dried biomass of Chara sp. for sample of BMP was used as alternative approach of conventional method. The range of removal percentages was between 92-97%, 70-98.7% and 46.6-96.6% for Pb, Cd and Ni respectively at 3h.Treatment time, with 300-500 mg dried weight from Chara sp. powder at pH 4, with 60 rpm at shaker. FTIR analysis showed the active groups which are responsible for sequestration of heavy metals represented by carboxyl, hydroxyl alkyl, amine and amide. The Biosorption equilibrium experiment for elements showed that the highest sorption percentage for three elements was, Pb 96.6% after 30 minute, for Cd was 100% after 15 minute and 40% to Ni after 75 minute, while the biosorp

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Crossref
Publication Date
Thu Jun 27 2019
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
A SURVEY OF WEEVILS (COLEOPTERA, CURCULIONOIDEA) FROM SOME LOCALITES OF KURDISTAN REGION- IRAQ, WITH NEW RECORDS TO THE ENTOMOFAUNA OF IRAQ
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This work is the first study of the Curculionoidea fauna from Kurdistan region of Iraq, based on the intensive survey in different localities of Kurdistan from March 2016 to November 2017. In total, 41 species belonging to 28 genera, 21 tribes and 3 families were collected and identified, including 25 species newly recorded for the Iraqi fauna.

 

General distribution, collecting localities and methods, with plant association data for each species are given.

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Scopus Crossref
Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Preparation and diagnosis of new types of Schiff bases one-and two- claw and complexes to study the effectiveness of chemical
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In this research we prepared shiff bases unilateral claw( benzyl imine aniline ) and Bilateral claw ( benzayal-2-imine phenol ) in high purity reach to 98% , which it's prepared from aromatic amine with aldehydes, it's solid,thermosetting, not dissolved in water in general. Diagnosed prepared article by using infra red spectroscopy (IR) which shows azomethen grop at 1640cm-1 At this diagnosis we suggest tetra headral mechanism in this Circumstances For a reaction.

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Crossref
Publication Date
Fri Jun 30 2023
Journal Name
Samarra Journal Of Pure And Applied Science
New Ligand-Based Metal Complexes: Synthesis, Spectroscopic Characterization, Thermal Behavior, Anticancer Properties, and Biological Activity
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New ligands, N1, N4-bis (benzo[d]thiazol-2- ylcarbamothioyl) succinamide (L1) and N1, N4- bis (benzylcarbamothioyl)succinamide (L2), derived from succinyl chloride and 2-amino benzothiazole or benzylamine, respectively, have been used to prepare a set of transition metal complexes with the general formula [M2(L)Cl4], where L=L1 or L2, M = Mn(II), Ni(II), Cu(II), Cd(II), Co(II), Zn(II) or Hg(II). The synthesized compounds were characterized using various analytical techniques including TGA, 13C NMR, mass spectroscopy, 1H and Fourier-transform infrared (FTIR) spectroscopy, magnetic measurement, molar conductivity, electronic spectrum, (%M, %C, %H, %N) and atomic absorption flame (AAF) analysis. The results showed that (L1, L2) bin

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Crossref
Publication Date
Thu Jun 26 2014
Journal Name
Engineering Optimization
A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
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The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola

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Crossref (6)
Scopus Clarivate Crossref
Publication Date
Thu Dec 03 2015
Journal Name
Iraqi Journal Of Science
New multispectral images classification method based on MSR and Skewness implementing on various sensor scenes
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Scopus (15)
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Scopus Crossref
Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
The effect of annealing temperatures on the optical parameters of NiO0.99Cu0.01 thin films
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NiO0.99Cu0.01 films have been deposited using thermal evaporation
technique on glass substrates under vacuum 10-5mbar. The thickness
of the films was 220nm. The as -deposited films were annealed to
different annealing temperatures (373, 423, and 473) K under
vacuum 10-3mbar for 1 h. The structural properties of the films were
examined using X-ray diffraction (XRD). The results show that no
clear diffraction peaks in the range 2θ= (20-50)o for the as deposited
films. On the other hand, by annealing the films to 423K in vacuum
for 1 h, a weak reflection peak attributable to cubic NiO was
detected. On heating the films at 473K for 1 h, this peak was
observed to be stronger. The most intense peak is at 2θ = 37

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Crossref
Publication Date
Tue Oct 30 2018
Journal Name
Journal Of Engineering
Study the Effect of Various Parameters on the Synthesis of ZSM-5 Zeolite
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ZSM-5 zeolite was synthesis under hydrothermal conditions at 175oC. The synthesis parameters have been investigated to find optimum synthesis method. Firstly, the crystallization time has been investigated to find the optimum crystallization time. Also, the ageing time was studied. The morphology, structure, and composition of the synthesized ZSM-5 zeolite were characterized using scanning electron microscopy (SEM), pH meter, viscometer, and X-ray powder diffraction (XRD). The bulk Si/Al ratio of ZSM-5 zeolite was in the range of 9.5—11.7. The synthesized ZSM-5 zeolite with appropriate ageing time could adjust crystal size and degree of the crystallinity. The crystal size of ZSM-5 zeolite obtained at an agei

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