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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.

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Chemical and Thermal Investigation on Stability of Tanuma Formation Using Different Additives with Drilling Fluids
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Wellbore stability is considered as one of the most challenges during drilling wells due to the
reactivity of shale with drilling fluids. During drilling wells in North Rumaila, Tanuma shale is
represented as one of the most abnormal formations. Sloughing, caving, and cementing problems
as a result of the drilling fluid interaction with the formation are considered as the most important
problem during drilling wells. In this study, an attempt to solve this problem was done, by
improving the shale stability by adding additives to the drilling fluid. Water-based mud (WBM)
and polymer mud were used with different additives. Three concentrations 0.5, 1, 5 and 10 wt. %
for five types of additives (CaCl2, NaCl, Na2S

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Publication Date
Sat May 21 2011
Journal Name
The International Journal Of Advanced Manufacturing Technology
Magneto-rheological directional control valve
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The main part in hydraulic system is directional control valve. Directional control valve has complex construction such as moving spool to control the direction of actuator for required speed. Magneto-rheological (MR) fluid is one of controllable fluids. Utilizing the MR fluid properties, direct interface can be realized between magnetic field and fluid power without the need for moving parts like spool in directional control valves. This study proposes the design of four ways/three position MR proportional directional control valve (4/3 MR valve). The construction of valve and the principle of work are presented. Analysis for magnetic circuit and simulation for valve performance were done. The experiment was conducted to show the principle

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Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
Effect of the electric field on drilling Brass by Laser
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The research include a pulsed Nd: YAG Laser with (300µs) pulse duration in the TEM00 mode at (1.06µm) wavelength for energies between (0.5-3) J was employed to drill Brass material which is use in industrial applications. The process of drill was assisted by an electric field. This resulted in an increase in the hole aspect ratio by the value (45%) and decrease in the hole taper by the value (25%) of its value under ordinary drilling conditions using the same input energy.

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Crossref
Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Scopus (26)
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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Using Factor Analysis In Determine the Important Influenced Factors In Student Outcomes Pheonema From Primary School In The Province Of Baghdad
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Abstract

The Purpose of This Research is The  Main Factors  In out Comes Phenomena From Primary School Which in Creased in Lost Period in Iraq And to Find Solutions to The This Problem.

In Order to Achieve Al The Aim The Research Choose a Systematic Random Sample of School Records For Students in Some Primary Schools in Karkh and Rusafa and Year of Study (2010-2015) and Size (40) Samples, included  (16) Variable , Collected in Form Prepared by The Research As a Way to Analyze The Data.

Remember to Summarize The (6) Main components Pay a Student to Drop out of Primary Schools in The Province of Baghdad are Arranged As Follows:

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Disney’s Girls: The Development of Persona from Snow White to Pocahontas
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Through his female characters, Walt Disney was able to reflect the
development of the general outlook upon women in the Western world over a period
of sixty years.
This paper sheds light in how the cartoon characters changed in their reaction
to problems and means of solving them from the 30s through to the 90s of the
previous century. The main characters will be seen according to the films’ dates of
production and release.

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering Science And Technology
THE INFLUENCE OF CHEMICAL COMPOSITION OF ASPHALT CEMENT ON THE PHYSICAL AND RHEOLOGICAL PROPERTIES
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Failure in asphalt mixture and distress in pavement are major issues to roads infrastructure. Selecting an appropriate chemical composition of asphalt cement is a key component in avoiding these issues. This work aimed to investigate the effect of the chemical composition of different polar fractions on the rheological and physical properties of asphalt cement. Four types of asphalt cement with penetration grades of 20/30, 40/50, 60/70 and 85/100 were divided into four fractions. Complex shear modules, rutting resistance and rotational viscosity of the asphalt cement were determined by using a Dynamic Shear Rheometer and a Rotation Viscometer, respectively. The results show that an increase in the asphaltene content and Gastel index resulte

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Publication Date
Sat Aug 08 2026
Journal Name
Scientific Reports
Enhancement of selecting the cluster head based on the voting mechanism and Elliptic Curve Cryptography for Wireless Sensor Networks (ECHVM)
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Abstract<p> The Wireless Sensor Networks (WSNs), which are deployed in harsh environments, are extremely susceptible to localized battery exhaustion as well as intelligent inside routing threats, especially sinkhole and data falsification attacks. In this paper, we present ECHVM (Enhanced Cluster Head selection by Voting and an ECC-based Blockchain Mechanism), a novel, secure, and energy-efficient routing framework to achieve an optimal trade-off between network security and hardware resource efficiency. We present the ECHVM protocol that combines Elliptic Curve Cryptography (ECC) with a lightweight, local distributed ledger to mitigate risks of centralized authority by tr</p> ... Show More
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Publication Date
Thu Dec 01 2016
Journal Name
Swarm And Evolutionary Computation
A new multi-objective evolutionary framework for community mining in dynamic social networks
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