bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural and DC-electrical properties of novel PMMA-PVA nanocomposites reinforced with graphene nanosheets
Authors: Kadhim M Abdul , Al-Bermany E 
Published: March 2021

Abstract
Polymer-graphene nanocomposites offer interesting opportunities to enhance the properties of polymer nanocomposites. In this study, new nanocomposites with polymethyl methacrylate and polyvinyl alcohol were successfully fabricated for the first time with various loading ratios of graphene oxide nanosheets (GO), with dimethylformamide-co-distilled water used as the developing solution. Fourier-transform infrared spectroscopy (FTIR), optical microscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), and DC electrical conductivity tests were conducted to investigate the structure and DC electrical properties of the resulting PMMA-PVA/GO nanocomposites. The OM and SEM images recorded a fine homogenous matrix and good distribution of GO in the nanocomposites, while the FTIR spectra displayed functional groups of all polymers and GO in the nanocomposites, with strong interfacial interaction between GO nanosheets and polymers, as confirmed by shifts in the XRD spectra of the PMMA. The results for conductivity in the DC electrical systems showed improvement after the addition of GO. The value of DC conductivity for PMMA-PVA/GO nanocomposites was 7.86 × 10-15 per ohm-cm at a GO ratio of 0.09%, while an increase in GO loading ratio to 0.27% caused an increase in conductivity to 4.53 × 10-9 per ohm-cm. The values of the activation energy of the nanocomposites were - 6.8%, -24.8%, and -66.91% eV for 0.09%, 0.18%, and 0.27% GO, respectively. These results suggest that such inclusions could allow for the development of better and wider applications for nanocomposites, including solar cells, electrical devices, IR-windows, microwave absorption panels, and sensors.
New Design of Single Band Elliptical Microstrip Antenna for Satellite Communication
Authors: Thaher Raad H , Jassim Hasanain M 
Published: March 2021

Abstract
An elliptical microstrip antenna with a special slot pattern on the patch was designed covering a bandwidth of 9.8701 GHz to 10.535 GHz, with gain of 3.1 dBi to 3.49 dBi with a voltage standing wave (VSWR) of less than two and reflection coefficient (S 11) of -63.4 dB. Computer simulation technology (CST) was used to obtain simulation results, while a vector network analyser (VNA) was used to obtain practical results. The proposed antenna is intended for radiolocation and satellite communications, with dimensions of (19 × 23 × 1.6)mm
3, making it smaller than most UWB antennas, manufactured on a substrate with a relative dielectric constant (εr) of 4.3 and loss tangent (tan δ) of 0.025. Reasonable agreement was found between the practical and simulation results.
Optimal PID Controller based on Convex Optimisation and Particle Swarm Techniques
Authors: Makki O T , Mohammad L S 
Published: March 2021

Abstract
This paper discusses the design and implementation of multiple optimisation algorithms for tuning a PID controller. A metaheuristic algorithm known as particle swarm optimisation (PSO) is used together with convex optimisation techniques, and the validity of the proposed algorithm is examined by comparing its performance with the performance of the classic PSO-PID and the well-known Ziegler–Nichols PID (ZN-PID). To obtain useful comparisons, a non-linear system, the air levitation system (AL), was utilised, controlled using a PID with three tuning strategies: the modified particle swarm technique (M-PSO-PID), the classic particle swarm (C-PSO-PID), and the Ziegler-Nichols method. The performance of the controllers was monitored through a cost function, the Integral Absolute Error (IAE). A disturbance was also imposed on the AL system to test the performance and the robustness of the algorithm under different conditions. The proposed algorithm is designed to determine and set the parameters for the M-PSO-PID controller utilising stabilising regions Kp, Ki, and Kd which form a convex problem. The PSO technique is then used to search for the optimal values inside the convex area. The simulation results for the control system show that the M-PSO-PID offered good closed-loop performance with advantages over other algorithms with regard to the system settling time and rise time. The results thus indicate the supremacy of the proposed algorithm.
Design and Implementation of a Smart Meter for Load Management
Authors: Hadi Abdul-Razzak Shehab , Mahdi Mohammed Chessab , Jassem Abed Al-Abass Muhseen , Sahib Ali 
Published: March 2021

Abstract
In this work, a method is outlined to convert a conventional electro-mechanical meter into a digital power meter as part of an Automated Meter Reading (AMR) system using a simple and cost-effective technique. A conventional electro-mechanical meter was converted to emit digitised pulses with the addition of an optical encoder, allowing automatic transmission of meter reading data and detection of meter tampering. In testing the proposed AMR system, the meter readings as read from the LCD were found to offer an accurate representation of the total power consumed. Further improvements suggested to enhance the functions of the AMR system, including load management and pre-payment. The proposed meter offers substantial savings for electric utility companies as well as enabling users to take advantage of fully automated meter readings.
Design and Implementation of a Zigbee, Bluetooth, and GSM-Based Smart Meter Smart Grid
Authors: Alubodi A O A , Al-Mashhadani I B N , Mahdi Dr S S 
Published: March 2021

Abstract
The first step in upgrading the billing and metering systems available in Iraq in most areas supplied by IMOELC (the Iraqi Ministry of Electricity) is the development and application of smart meter systems. These systems are based on two-way communication between consumers and suppliers, and the smart meter approach is thus more reliable than even digital meters with regard to billing and tamper prevention, as well as allowing the government to monitor electricity consumption in an enhanced and organised way based on the information obtained from data centres. To facilitate this data exchange, a new meter was proposed and tested in real-time in a few houses in Karbala, with the measured voltage, current, and power factors for energy multiplied every second and summed to determine energy consumption before being stored on the SD (Secure Digital) card in a backup text file in case of shutdown. The readings collected from the tested region were send to a Data Concentrator Unit (DCU) using three communication methods (Bluetooth, XBee and GSM). The data was then transferred from the DCU to the server via GSM, as GSM offers the lowest interference and fault occurrence, making it most suitable for long-distance transfers. Bills were generated based on the readings over time, with the division by time shown on the bill to urge users to rationalise their energy use at certain times during the day. The final error in current reading was less than 8% and the error in voltage reading was less than 0.64%.
Design and Implementation of a Remotely Controlled Two-Wheel Self-Balancing Robot
Authors: Aldhalemi A A , Chlaihawi A A , Al-Ghanimi A 
Published: March 2021

Abstract
This research included the design and implementation of a real-time remotely controlled Two-Wheel Self-Balancing Robot (TWSBR). The aim was to build a low cost TWSBR that could be remotely navigated using Bluetooth wireless technology. Experimentally, the TWSBR consists of two parts: the hardware device and the software algorithm. Bluetooth protocols were used to facilitate communication between a smartphone device and a gyroscope sensor. As the dynamic structure of the robot is inherently unstable, self-stabilisation represents a major challenge, and a robust control algorithm was thus required for this task. A Proportional-Integral-Derivative (PID) was employed to achieve this in real-time with the help of an 8-bit microcontroller. The feedback signal was fed to the PID controller through the gyroscope sensor with the aim of maintaining TWSBR stability and balance based on adjusting its longitudinal angle in response to the gyroscope feedback signal. A prototype robot was then built to validate the proposed algorithm.
Biosensor Based on Photonic Crystal Fibre with Mode Coupling of a Dual-Core
Authors: Naife Riyadh Mwad , Abbas AbdulSattar K. 
Published: March 2021

Abstract
In recent years, photonic biosensors have attracted increasing attention due to the enormous range of applications in many fields to which they may be put, including medical diagnostics, environment monitoring, organic chemical detection, temperature sensing, and work with magnetic fields. In this work, photonic crystal fibre (PCF) was utilised as a biosensor using a Finite Element Method (FEM). Several important optical sensor properties such as the field distribution profiles, the real part of the effective refractive index and the relative sensitivity of the proposed PCF structure are affected by mode coupling between the fundamental mode and the second order super mode of the inner and outer cores, respectively. These properties were thus those studied by applying FEM. The proposed biosensor can thus be used for bio-sensing, as the holes in the PCF are filled with analytes. Relatively high sensitivity can thus be obtained using appropriate design by selecting design parameters such as the radius of holes in the cladding region and pitch distance, or distance between the centres of neighbouring holes, appropriately. The results from this work show that the electric field distribution is affected by mode coupling between the outer and inner modes; the effects of mode coupling of the PCF on the relative sensitivity were also determined.
Design and Analysis of a Novel Artificial Ankle-Foot Joint Mechanism
Authors: Kokz Samer A , Alher Murtadha A , Ajibori Hakim S Sultan , Muhsin J.Jweeg 
Published: March 2021

Abstract
Globally, more than one million limbs are amputated annually. Theoretical and experimental studies thus been undertaken in many countries to develop prosthetics to help alleviate the suffering of people with amputated limbs. This study aimed to design and simulate an artificial ankle joint to mimic huma walking on sloped surfaces efficiently. The new design also attempts to mimic the shape, the size and the range of angle motion of the human ankle joint while simultaneously reducing the cost and weight of the prototype prosthetic ankle unit and increasing durability and responsiveness. The weight of the individual user is the main factor controlling the engagement and disengagement of the artificial ankle joint during the gait cycle, and the new design for the artificial ankle joint was prepared and tested using CATIA and ANSYS software. The suggested model was shown to be effective and reliable and able to adapt to multiple different surfaces. It also achieved high flexibility under various weights of users.
A Finite Element Simulation of Nano Effects on Stress Distribution in a Below Knee Prosthetic
Authors: Jweeg Muhsin J. , Hamzah H. A. , Al-Waily Muhannad , Al-Shammari Mohsin Abdullah 
Published: March 2021

Abstract
In the authors’ previous work, various mechanical properties such as modulus of elasticity, strength, creep, impact and fatigue behaviours for different laminates composites with and without different Nano-material additions and reinforcements with different types of fibres were tested experimentally. The four best lamination types and suitable Nano-material percentages were used in this work to develop a numerical investigation of a below knee prosthesis, facilitating the investigation of the effect of different Nano-material types and weight fractions on the stress and deformation in below-knee socket prosthetic structures manufactured from composite laminated materials with various reinforcement fibres. Numerical analysis using the finite element method was adopted to estimate the Von Mises stresses and deformation behaviours for the below-knee prosthetic structures, with the mechanical properties of the relevant composite materials taken from previous published work. The comparison of different Nano-material types and weight fractions suggested that the best Nano-material was SiO2 at a weight fraction of about 2% for the sample 2Perlon+2Kevlar+1Perlon+2Carbon+1Perlon+2Kevlar+2Perlon, where the stress for the socket was reduced by about 40%, with a reduction in the deformation of about 38%.
Movement of polymers in an asymmetric nano-channel under various parameters
Authors: Taghavi Firoozeh , Bianco Valentino , Malgaretti Paolo , Nikoofard Narges 
Published: March 2021

Abstract
Separation is an important process in various fields in science and technology, and nano-structures are now being widely used to improve the resolution and speed of separation processes. Continuous separation occurs when the components of a mixture separate at different locations in a device; this makes it possible to inject a new sample into the device at any time during an on-going separation process. Continuous separation of nano-particles in a nano-channel composed of consecutive cones has been shown previously, while this study investigates whether a nano-channel can perform continuous separation of polymers such that polymers of different lengths are separated at the two sides of the channel. For this purpose, the motion of a charged polymer in an asymmetric nano-channel under constant and alternating applied electric fields was studied theoretically and by applying computer simulations. Theoretical formalism was used to determine the situation under which the channel could perform continuous separation, with computer simulations used to check the theoretical results. The effect of different channel parameters on the performance of the nano-channel, as a device for continuous separation, was thus determined.
Human Gait Cycle Classification Improvements Using Median and Root Mean Square Filters Based on EMG Signals
Authors: Ghalyan M F , Alher M A , Jweeg M J 
Published: March 2021

Abstract
Human walking is an important and intuitive operation in daily life, but it is different for people missing this ability. Recognizing human gait cycle portions during walking is very useful for understanding the biomechanics of the muscles, pre-disease’s diagnosis, and designing lower limb prosthetics. The normal gait cycle is divided into stance and swing phases. In this work, benchmarking of several classification techniques is performed, based on electromyography (EMG) data collected from seven lower limb muscles, with the gait cycle phase used as a target vector to label the EMG data. The dataset is split into a training set used to build a statistical model using a specified classification technique, and a test set for purpose of testing a pre-generated statistical model. EMG signals are unfortunately normally corrupted with noise, which drastically reduces their classification performance. A median filter and root mean square (RMS) filter were thus applied to the raw EMG signals, and the performance of the classification techniques calculated in all cases for the raw EMG, EMG with median filter, and EMG with RMS filters for comparison purposes. The use of filters offered good enhancement in the classification process. The median filtered EMG signal performed best and gave higher accuracy than the raw EMG and RMS filtered EMG signals due to the technique’s efficacy in removing outliers. This work also offers a simple explanation of each classifier algorithm used, and a graphical feature selection was also applied to all seven muscles of interest to identify the muscle with the most influence on the gait cycle. The Rectus Femoris muscle shows the best activity separation between swing and stance phases, working mainly during the swing phase; this higher activity during the swing phase thus caused it to be identified as the muscle with the most influence over the normal gait cycle.
Electrochemical treatment enhancment with dissolved air floatation to minimise organic pollutants of leachate in the press stations in Baghdad
Authors: Mahdi Ruqaya S , Asrar A Hassan , Jaafar Mahdi Sh 
Published: March 2021

Abstract
Leachate is a complex solution of contaminants produced from municipal waste compacting stations, being primarily comprised of household waste. In this research, leachate was treated in an electrochemical batch process with a dissolved air floatation system using aluminium as the anode with cathode electrodes. Conditions such as pH, current density (i), contact time, and air flowrate were varied and tested to determine their effects on the removal efficiency in terms of Chemical Oxygen Demand (COD), Oil, and Turbidity (Turb.). Under the best conditions, the removal efficiencies for oil, COD, and turbidity were 78.7%, 77.5%, and 98.6%, respectively, suggesting that this method can be considered an efficient and effctive treatment for leachate.
Evaluation of transport processes in a catalytic reforming reactor with high performance nanocatalysts
Authors: Sukkar Khalid A. 
Published: March 2021

AbstractCatalytic reforming reactors are the most important multiphase reactors in petroleum refineries producing high octane gasoline. The reforming process usually generates an unstable operation combined with catalyst activity loss due to the high levels of interaction between the heat transfer and mass transfer processes in the reactor and the specifications of the catalyst. In this investigation, n-heptane reforming reactions were investigated by preparing three types of nanocatalysts (Pt/HY, Pt-Ge/HY, and Pt-Re/HY). The reforming reactions were investigated at 440, 460, 480, 500, and 520 °C under atmospheric pressure in a reactor of dimensions 2 cm (inner diameter) by 30 cm (height) manufactured from stainless steel. The H2/n-heptane was selected to operate at a value of 2 with WHSV=2, and the effects of heat and mass transfer processes on the catalyst and reactor performance were thus evaluated. The results indicated that the Pt-Gr/HY catalyst showed the highest activity, selectivity, and stability at a reaction temperature of 480 °C. It was also noted that the heating rate and diffusional processes were severely affected by reaction selectivity during formation of the desired products as well as by the hydrodynamic parameters of the reactor. The activity of the prepared nanocatalysts demonstrated the sequence Pt-Ge/HY> Pt-Re/HY> Pt/HY, and the prepared nanocatalysts were able to offer high performance under controlled transport processes in terms of producing high-quality gasoline.
Predicting Drilling Rate of Penetration Using Artificial Neural Networks
Authors: Mahdi Doaa Saleh 
Published: March 2021

Abstract
Oil well drilling processes are generally high-cost operations; however, these costs can be reduced by optimising drilling operations. In particular, it is vital to optimise the drilling rate of penetration during oil well drilling operations. Many parameters affect drilling penetration rate, and these have complex relationships with each other. The accurate prediction of the drilling rate of penetration has particular importance in the optimisation of all drilling parameters and the reduction of drilling costs. In this paper, a neural network model is developed to predict the rate of penetration for an Iraqi oil field as a function of well depth, drilling fluid inflow, bit rotation speed (RPM), weight on bit (WOB), standpipe pressure, and bit size. The data on which the network was trained was collected from one drilled oil well, and 3,939 data points were used to develop the new model. These were randomly divided into two parts, with 70% used for training and 30% used for testing. The results showed that the resulting neural network model offers high accuracy for predicting the drilling rate of penetration. The statistical analysis showed that the developed neural network model predicted the rate of penetration very high accuracy (correlation coefficient of 0.983 and average absolute error of just 7.78%). The new model can also be used to determine the optimum drilling parameters to obtain a desired rate of penetration.
An approach for applying managed pressure drilling techniques to troublesome formations in an oil well in southern Iraq
Authors: Dhayea Batool Abdullah , Almahdawi Faleh H. M. 
Published: March 2021

Abstract
Many southern Iraqi oil field formations, such as Dammam and Hartha, are characterised as loose formations, making overbalanced drilling difficult due to increased frequency and volume of mud losses. Managed pressure drilling techniques (MPD) may thus be applied. This process uses conventional hydrostatic column pressure and annular friction pressure in addition to the surface back pressure to generate a constant bottomhole pressure (CBHP) to drill such formations, which enables the use of the lowest mud weight (closest to pore pressure) and back pressure treatment utilising a choke manifold during the drilling process to maintain an equivalent circulating density (ECD) slightly greater than the pore pressure, reducing the risk of mud loss, and the concomitant stuck pipes and non-productive time (NPT), thus enhancing drilling efficiency. In this paper, Wellflo software was utilized to model multi-phase flow in wells to examine the use of aerated mud used at different injection rates for gas and liquid to identify the best injection rate for drilling operations without losses. Several cases were examined using various mud weights and surface back pressure of the assumed injection rates, to choose the appropriate mud weight and the surface back pressure ranges. The highest pore pressure gradient expected in such holes is 0.465 psi/ft, and consequently, the minimum required mud weight was 8.95 ppg, in order to ensure control and avoid loss; however, due to back pressure and friction pressure in the annular region, this weight leads to problems in some formations. A mud weight of 8.8 ppg was therefore chosen as the closest feasible weight to pore pressure, with back pressures of 200 and 250 psi. A gas injection rate of 1,200 gpm was selected as the best injection rate for various liquid rates (581, 631, 681,731, and 781 gpm). The use of aerated mud at 8.8 ppg mud weight increased the penetration rate, offering a more efficient cutting transportation ratio (CTR) and allowing more control over wellbore instability and formation damage, as well as limiting mud losses.
Estimation of Bourgoyne and Young Model Coefficients to Predict Optimum Drilling Rates and Bit Weights using Genetic Algorithms – a case study of the Faihaa Oil Field in Iraq
Authors: Khaleel AbdulKareem A , Adnan Mohammed S , Alhamd Salem J 
Published: March 2021

Abstract
Drilling optimization requires maximizing rate of penetration (ROP) by controlling parameters such as bit weight (WOB) and rotary speed (N) to reduce drilling time and cost and to mitigate hole problems. The Bourgoyne and Young model was selected to study the effects of all parameters concerned with oil well drilling (depth, pore pressure, equivalent circulating density, bit weight, rotary speed, bit tooth dullness and jet impact force) based on actual bit records for a well in Faihaa oil field. A multiple regression analysis technique and genetic algorithm procedure were employed to analyze the field data, with the results used to develop a general equation relating rate of penetration to all variables. All the constants of the model were thus determined, and the optimized bit weight calculated for different depths of well to achieve the optimum penetration rate.