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Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parameters. A databases from one well drilled in carbonate environments were subjected to the predictive methods. Each raw dataset is described by eight parameters including rate of penetration (ROP), true vertical depth (TVD), weight on bit (WOB), bit rotational speed (RPM), torque (TQ), flow rate (Q), equivalent circulating density (ECD), standpipe pressure (SPP), and unconfined compressive strength (UCS). First, both MRA and ANNs are tested as predictive methods. The prediction capacity of each model was also verified by using two-based error metrics: the determination coefficient (R2) and the mean square error (MSE).</p><p>The current results support the evidence that MRA and ANNs are able to be effectively utilize the drilling data, and thus provide accurate ROP prediction. However, more attention to the multiple regression analysis is required where it is implemented for ROP prediction. ANNs appear to be more conservative in predicting ROP than MRA as indicated by a higher value R2 (0.96) and lower value MSE (1.89) of the ANN model. Considering the input parameters, the obtained results showed that TVD, WOB, RPM, SPP, and ECD had the greatest effect on estimated ROP-conditions, followed in decreasing by pump flow rate, drilling torque, and rock strength. Another important point that highlights in this study is that the drilling rate may increase with depth in carbonate rocks because of their heterogeneity. This study presents new models to estimate ROP from other parameters which can help the driller to achieve an optimal drilling rate through monitoring controllable parameters.</p>
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Publication Date
Thu Apr 28 2022
Journal Name
Iraqi Journal Of Science
Study The Spin Down Luminosity And Flux Density For Pulsar Stars By Using Hallo Cone Model
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There are different types of young isolated NSs: radio pulsars, compact central X-ray sources in supernova, magentas: anomalous x-ray pulsars (AXPs) and soft gamma-ray repeaters (SGRs).This paper shows that the value of magnetic field (B), characteristic age ( ), spin down luminosity ( equilibrium period ( and Flux density ( ) was determined depending on some properties of pulsar star, such as the value of period of the pulsar (P) and the time derivative period ( for sample stars which were adopted. The model that which adopted is Hallo Cone Model. The results showed that the Normal pulsar stars have a big magnetic field, equilibrium period and Spin down than the Millisecond pulsar stars.But Millisecond pulsar stars have large values of

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Publication Date
Sat Oct 01 2022
Journal Name
Colloids And Surfaces A: Physicochemical And Engineering Aspects
Application of natural deep eutectic solvents in bulk liquid membrane system for removal of free glycerol from crude fatty acid methyl ester
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Fatty Acid Methyl Ester (FAME) produced from biomass offers several advantages such as renewability and sustainability. The typical production process of FAME is accompanied by various impurities such as alcohol, soap, glycerol, and the spent catalyst. Therefore, the most challenging part of the FAME production is the purification process. In this work, a novel application of bulk liquid membrane (BLM) developed from conventional solvent extraction methods was investigated for the removal of glycerol from FAME. The extraction and stripping processes are combined into a single system, allowing for simultaneous solvent recovery whereby low-cost quaternary ammonium salt-glycerol-based deep eutectic solvent (DES) is used as the membrane phase.

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Publication Date
Wed Dec 05 2018
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
X-Ray Fluorescence Determination of Trace Elements in Vitamin-Mineral Complexes and Medicinal Herbs Using Chemically Modified Polyurethane Foam Sorbents
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In this paper we proposed the method of X-ray fluorescence (XRF) determination of some essential trace elements in medicinal herbs and vitamin-mineral complexes at the level of 100-101 mg/ml. To increase sensitivity and selectivity of the determination we simple and effective approach based on the extraction of metal ions from aqueous solutions with chemically modified polyurethane foam sorbents followed by direct XRF analysis. The conditions of sorption preconcentration of Co(II), Ni(II) and Zn(II) ions with modified sorbents were optimized. The proposed approach is used for the determination of trace elements in several kinds of medicinal herbs (coltsfoot leaves, nettle leaves and yarrow herb) and vitamin-mineral

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
Arabic Keywords Extraction using Conventional Neural Network
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    Keywords provide the reader with a summary of the contents of the document and play a significant role in information retrieval systems, especially in search engine optimization and bibliographic databases. Furthermore keywords help to classify the document into the related topic. Keywords extraction included manual extracting depends on the content of the document or article and the judgment of its author. Manual extracting of keywords is costly, consumes effort and time, and error probability. In this research an automatic Arabic keywords extraction model based on deep learning algorithms is proposed. The model consists of three main steps: preprocessing, feature extraction and classification to classify the document

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Studying of Some Mechanical Properties of Reactive Powder Concrete Using Local Materials
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This research aims to investigate and evaluate a reactive powder concrete (RPC) cast using economical materials. Its mechanical properties were investigated and evaluated by studying the effects of using different cement and silica fume contents and locally steel fibers aspect ratios as reinforcement for this concrete. A compressive strength of about 155.2MPa, indirect tensile strength of 16.0MPa, modulus of elasticity of 48.7GPa, flexural strength of 43.5MPa, impact energy of 3294.4kN.m and abrasion loss 0.59%  have been achieved for reinforced RPC contains  910 kg/m3 cement content, silica fume content 185 kg/m3 of cement weight and fiber volume fraction 2%. The water absorption values w

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Analytical Chemistry
A Spectrophotometric Method for Tetracycline Determination in its Bulk Powder and Pharmaceutical Formulations Using Flow Injection and Batch Procedures: a Comparative Study
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A reliable and environmental analytical method was developed for the direct determination of tetracycline using flow injection analysis (FIA) and batch procedures with spectrophotometric detection. The developed method is based on the reaction between a chromogenic reagent (vanadium (III) solution) and tetracycline at room temperature and in a neutral medium, resulting in the formation of an intense brown product that shows maximum absorption at 395 nm. The analytical conditions were improved by the application of experimental design. The proposed method was successfully used to analyze samples of commercial medications and verified throughout the concentration ranges of 25–250 and 3–25 µg/mL for both FIA and batch procedures, respecti

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Publication Date
Thu Aug 01 2024
Journal Name
Advances In Science And Technology Research Journal
Power Predicting for Power Take-Off Shaft of a Disc Maize Silage Harvester Using Machine Learning
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Publication Date
Wed May 01 2019
Journal Name
Iraqi Journal Of Science
The Minimum Cost for the Vascular Network Using Linear Programming Based Its Path Graph
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As of late, humankind has experienced radiation issues either computerized tomography (CT) or X-rays. In this investigation, we endeavor to limit the effect of examination hardware. To do this the medical image is cropping (cut and zoom) then represented the vascular network as a graph such that each contraction as the vertices and the vessel represented as an edges, the area of the coagulation was processed already, in the current search the shortest distance to reach to the place of the blood vessel clot is computed

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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Nonlinear Anal. Appl.
Feeble regular and feeble normal spaces in α-topological spaces using graph
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This paper introduces some properties of separation axioms called α -feeble regular and α -feeble normal spaces (which are weaker than the usual axioms) by using elements of graph which are the essential parts of our α -topological spaces that we study them. Also, it presents some dependent concepts and studies their properties and some relationships between them.

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Publication Date
Thu Jun 01 2017
Journal Name
Iosr Journal Of Computer Engineering
Lossy Image Compression Using Wavelet Transform, Polynomial Prediction And Block Truncation Coding
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