Preferred Language
Articles
/
eRaTGIcBVTCNdQwCZzZc
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
...Show More Authors
Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the modeling part, a one-dimension mechanical earth model (1D MEM) parameters, drilling fluid properties, and rig- and bit-related parameters, were included as inputs. The optimizing process was then performed to propose the optimum drilling parameters to select the drilling bit that provides the maximum possible ROP. To achieve this, the corresponding mathematical function of the ANNs model was implemented in a procedure using the genetic algorithm (GA) to obtain operating parameters that lead to maximum ROP. The output will propose an optimal bit selection that provides the maximum ROP along with the best drilling parameters. The statistical analysis of the predicted bit types and optimum drilling parameters comparing the actual flied measured values showed a low root mean square error (RMSE), low average absolute percentage error (AAPE), and high correction coefficient (R2). The proposed methodology provides drilling engineers with more choices to determine the best-case scenario for planning and/or drilling future wells. Meanwhile, the newly developed model can be used in optimizing the drilling parameters, maximizing ROP, estimating the drilling time, and eventually reducing the total field development expenses.</p>
Crossref
View Publication
Publication Date
Wed Jul 13 2016
Journal Name
International Journal Of Mathematics Trends And Technology
Designed Algorithms for Compute the Tenser Product of Representation for the Special Linear Groups
...Show More Authors

The main objective of this paper is to designed algorithms and implemented in the construction of the main program designated for the determination the tenser product of representation for the special linear group.

View Publication Preview PDF
Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
...Show More Authors

The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

... Show More
Preview PDF
Scopus (3)
Crossref (5)
Scopus Clarivate Crossref
Publication Date
Tue Jan 02 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Multiple choice questions and essay questions in assessment of success rate in medical physiology
...Show More Authors

Background: Assessment is an important part of the learning cascade in education. Students realize it as an influential motivator to direct and guide their learning. The method of assessment determines the way the students reach high levels of learning. It has been documented that one of factor affecting students’ choice of learning approach is the way how assessment is being performed. Many methods of assessment namely multiple choice questions, essay questions and others are mainly used to assess basic science knowledge in undergraduate education. Objectives: The aim of this study is to compare multiple choice questions (MCQ) and essay questions (EQ) (record the success and failure rate of multiple choice questions (MCQ) and essay quest

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Surface Roughness and Material Removal Rate in Electrochemical Machining Using Taguchi Method
...Show More Authors

Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

... Show More
View Publication Preview PDF
Crossref (5)
Crossref
Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
A Study of Wear Rate Epoxy Resin filled with SiO2 particle and Glass fibers
...Show More Authors

This research is devoted to study the effect of different in weight percentage of Sio2 particles and glass fibers (5, 10, 15, 20) wt. % on the wear rate epoxy resin. The results show that the value of hardness increase with the increase for the weight percentage of reinforcing particles and fibers, while the wear rate decrease with the increase the load level of the reinforcing particles and fibers . The largest value of the hardness, and the lowest value of the wear rate for epoxy reinforced with 20% of SiO2, the wear rate increase in general with increasing the applied load.

View Publication Preview PDF
Crossref
Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
Photophysics of Coumarin 460: Temperature Effect upon Fluorescence Lifetime and Non-Radiative Rate Parameter
...Show More Authors

The temperature influence on the fluorescence lifetime, quantum yields and non-radiative rate parameter or coumarin 460 dye dissolved in methanol was investigated in the temperature range (160-300 k). A single photon counting technique was used or measuring the fluorescence decay curves. A noticeable decrease of the fluorescence lifetime with increasing the temperature was observed. The non-radiative activation energy of 10.57 K.J. mole-1 was measured by the help of Arrhenius plot.

View Publication Preview PDF
Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Damage Detection and Assessment of Stiffness and Mass Matrices in Curved Simply Supported Beam Using Genetic Algorithm
...Show More Authors

In this study, a genetic algorithm (GA) is used to detect damage in curved beam model, stiffness as well as mass matrices of the curved beam elements is formulated using Hamilton's principle. Each node of the curved beam element possesses seven degrees of freedom including the warping degree of freedom. The curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory. The identification of damage is formulated as an optimization problem, binary and continuous genetic algorithms
(BGA, CGA) are used to detect and locate the damage using two objective functions (change in natural frequencies, Modal Assurance Criterion MAC). The results show the objective function based on change in natural frequency i

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Nov 01 2021
Journal Name
Archives Of Razi Institute
RAPD Fingerprinting and Genetic Diversity of Salmonella Spp. Isolated from Broiler and Layer Flocks in Karbala, Iraq
...Show More Authors

Salmonellosis in poultry is one of the most significant bacterial infections causing mortality, reduced production, and serious economic losses. This study aimed to study the molecular diversity among Salmonella isolates and investigate the epidemiological spread of these bacteria in broiler and layer chicken flocks in five different farms in Karbala, Iraq, using random amplified polymorphic DNA (RAPD) polymerase chain reaction (PCR). In total, 217 cloac a swabs were collected from the farms, out of which 129 and 88 swabs were taken from broiler and layer chickens. The samples were screened by PCR for S. enterica subsp. enterica using primers specific for the invA gene. Afterward, RAPD-PCR with uniplex or multiplex octamer primers was appli

... Show More
View Publication Preview PDF
Scopus (4)
Scopus
Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fully Automated Magnetic Resonance Detection and Segmentation of Brain using Convolutional Neural Network
...Show More Authors

     The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
...Show More Authors

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

... Show More
View Publication Preview PDF
Crossref (1)
Crossref