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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
Wed Oct 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Spatial Regression Model Estimation for the poverty Rates In the districts of Iraq in 2012
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Theresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had

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Publication Date
Sat Dec 11 2021
Journal Name
Engineering, Technology &amp; Applied Science Research
Post-Fire Behavior of Non-Prismatic Beams with Multiple Rectangular Openings Monotonically Loaded
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The main objective of this paper is to study the behavior of Non-Prismatic Reinforced Concrete (NPRC) beams with and without rectangular openings either when exposed to fire or not. The experimental program involves casting and testing 9 NPRC beams divided into 3 main groups. These groups were categorized according to heating temperature (ambient temperature, 400°C, and 700°C), with each group containing 3 NPRC beams (solid beams and beams with 6 and 8 trapezoidal openings). For beams with similar geometry, increasing the burning temperature results in their deterioration as reflected in their increasing mid-span deflection throughout the fire exposure period and their residual deflection after cooling. Meanwhile, the existing ope

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Publication Date
Sat Dec 11 2021
Journal Name
Engineering, Technology &amp; Applied Science Research
Post-Fire Behavior of Non-Prismatic Beams with Multiple Rectangular Openings Monotonically Loaded
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The main objective of this paper is to study the behavior of Non-Prismatic Reinforced Concrete (NPRC) beams with and without rectangular openings either when exposed to fire or not. The experimental program involves casting and testing 9 NPRC beams divided into 3 main groups. These groups were categorized according to heating temperature (ambient temperature, 400°C, and 700°C), with each group containing 3 NPRC beams (solid beams and beams with 6 and 8 trapezoidal openings). For beams with similar geometry, increasing the burning temperature results in their deterioration as reflected in their increasing mid-span deflection throughout the fire exposure period and their residual deflection after cooling. Meanwhile, the existing ope

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Publication Date
Fri Jan 01 2016
Journal Name
Applied Numerical Mathematics
Multiple time-dependent coefficient identification thermal problems with a free boundary
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Publication Date
Sun Jan 01 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees22fr
Study the contrast of thermal expansion behavior for PMMA denture base, single and hybrid reinforced using the thermomechanical analysis technique (TMA)
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Publication Date
Sat Feb 01 2020
Journal Name
Meta Gene
Interleukin-2 serum level, genetic polymorphism (rs2069763), anti-rubella antibody and risk of multiple sclerosis among Iraqi patients
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Background: Multiple sclerosis (MS) is a chronic neurodegenerative autoimmune disease mediated by autoreactive T cells against myelin-basic proteins. Cytokines are suggested to play a role in the etiopathogenesis of the disease. Among these cytokines is interleukin-2 (IL-2). Aim of the study: To investigate the association between IL2+166 G/T single nucleotide polymorphism (SNP: rs2069763) and MS in Iraqi patients. Serum level of IL-2 was also detected. Anti-rubella IgG antibody was further determined in the sera of patients. Patients and methods: Eighty MS patients (28 males and 52 females; age mean ± SD: 39.2 ± 16.1 years) and 80 healthy control matched patients for age (32.15 ± 16.13 years) and gender (28 males and 52 females) were en

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Publication Date
Sun May 01 2022
Journal Name
International Journal Of Multiphase Flow
Application of artificial neural network to predict slug liquid holdup
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Publication Date
Tue Aug 15 2023
Journal Name
Al-academy
The effectiveness of artificial intelligence in contemporary digital graphic design
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In our world, technological development has become inherent in all walks of life and is characterized by its speed in performance and uses. This development required the emergence of new technologies that represent a future revolution for a fourth industrial revolution in various fields, which contributed to finding many alternatives and innovative technical solutions that shortened time and space in terms of making Machines are smarter, more accurate, and faster in accomplishing the tasks intended for them, and we find the emergence of what is called artificial intelligence (artificial intelligence), which is the technology of the future, which is one of the most important outputs of the fourth industrial revolution, and artificial inte

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Publication Date
Sun Jan 01 2017
Journal Name
Medical Journal Of Babylon
Dual and Multiple AV Nodal Pathways, What is The Deference in Typical Atrioventricular Nodal Reentrant Tachycardia
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Abstractin adult typical atrioventricular nodal reentrant tachycardia (AVNRT) consider most common paroxysmalsupraventricular tachycardia. Dual pathway idea still accepted and used widely and commonly. According tothe guide line, ablations of slow pathway still the first treatment with good success rate.Identify the electrophysiological difference of atrioventricular nodal pathways pre and post ablation.Electrophysiological study was done to 54 patients with only typical type AVNRTs; they were 40 (74%)females and 14 (26%) males. Divided into two groups G1 with 38 patients (70.4%) having one pathway andG2 with 16 patients (29.6%) with multiple pathway. After induction we study the clinical andelectrophysiological feature of tachycardia and s

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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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