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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
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
The Performance Differences between Using Recurrent Neural Networks and Feedforward Neural Network in Sentiment Analysis Problem
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 With the spread use of internet, especially the web of social media, an unusual quantity of information is found that includes a number of study fields such as psychology, entertainment, sociology, business, news, politics, and other cultural fields of nations. Data mining methodologies that deal with social media allows producing enjoyable scene on the human behaviour and interaction. This paper demonstrates the application and precision of sentiment analysis using traditional feedforward and two of recurrent neural networks (gated recurrent unit (GRU) and long short term memory (LSTM)) to find the differences between them. In order to test the system’s performance, a set of tests is applied on two public datasets. The firs

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Publication Date
Wed May 01 2024
Journal Name
Heliyon
Determining the bacterial and viral meningitis trend in Iraq from 2007 till 2023 using joinpoint regression
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Publication Date
Sat Jul 28 2018
Journal Name
Journal Of Engineering
Experimental and Numerical Analysis of Expanded Pipe using Rigid Conical Shape
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The experimental and numerical analysis was performed on pipes suffering large plastic deformation through expanding them using rigid conical shaped mandrels, with three different cone angles (15◦, 25◦, 35◦) and diameters (15, 17, 20) mm. The experimental test for the strain results investigated the expanded areas. A numerical solution of the pipes expansion process was also investigated using the commercial finite element software ANSYS. The strains were measured for each case experimentally by stamping the mesh on the pipe after expanding, then compared with Ansys results. No cracks were generated during the process with the selected angles. It can be concluded that the strain decreased with greater angles of con

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of The World Federation Of Orthodontists
Validity and reliability of three-dimensional modeling of orthodontic dental casts using smartphone-based photogrammetric technology
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Publication Date
Tue Oct 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Surface Contamination and Dose Rate Verification of Fertilizers common in Iraqi Plantations using RadEye B20 Detector
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Twenty three samples of granular chemical fertilizers and organic fertilizers commonly utilized in Iraqi ranches were collected. The samples were prepaid and stored in a Marinelli beaker to measure; dose rate, general count rate and surface contamination of the samples using the RadEye B20 detector, firstly with shield, secondly without the shield to estimate the effect of shielding on the measurements. The results showed that using shield made a significant decrease in the radiation measurements reached about 25%. However the mean value of surface contamination, dose rate and general count rate with shield were 0.54Bq/cm2, 0.65µsv/h, and 0.28Cps respectively, and without shield being 0.34Bq/cm2, 1.33µsv/h, and 1.52Cps respectively

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Using The Maximum Likelihood And Bayesian Methods To Estimate The Time-Rate Function Of Earthquake Phenomenon
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In this research, we dealt with the study of the Non-Homogeneous Poisson process, which is one of the most important statistical issues that have a role in scientific development as it is related to accidents that occur in reality, which are modeled according to Poisson’s operations, because the occurrence of this accident is related to time, whether with the change of time or its stability. In our research, this clarifies the Non-Homogeneous hemispheric process and the use of one of these models of processes, which is an exponentiated - Weibull model that contains three parameters (α, β, σ) as a function to estimate the time rate of occurrence of earthquakes in Erbil Governorate, as the governorate is adjacent to two countr

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Publication Date
Fri Dec 01 2023
Journal Name
Applied Energy
Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent
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The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

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Publication Date
Wed Jan 01 2014
Journal Name
Proceedings Of The Aintec 2014 On Asian Internet Engineering Conference - Aintec '14
LTE Peak Data Rate Estimation Using Modified alpha-Shannon Capacity Formula
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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
A Real-Time Fuzzy Load Flow and Contingency Analysis Based on Gaussian Distribution System
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Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Taibah University Medical Sciences
Preparing polycaprolactone scaffolds using electrospinning technique for construction of artificial periodontal ligament tissue
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Objectives The strategies of tissue-engineering led to the development of living cell-based therapies to repair lost or damaged tissues, including periodontal ligament and to construct biohybrid implant. This work aimed to isolate human periodontal ligament stem cells (hPDLSCs) and implant them on fabricated polycaprolactone (PCL) for the regeneration of natural periodontal ligament (PDL) tissues. Methods hPDLSCs were harvested from extracted human premolars, cultured, and expanded to obtain PDL cells. A PDL-specific marker (periostin) was detected using an immunofluorescent assay. Electrospinning was applied to fabricate PCL at three concentrations (13%, 16%, and 20% weight/volume) in two forms, which were examined through field emission

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