124 research outputs found
Construction of Exact Solutions for Gilson–Pickering Model Using Two Different Approaches
No full textIn this paper, the extended simple equation method (ESEM) and the generalized Riccati equation mapping (GREM) method are applied to the nonlinear third-order Gilson–Pickering (GP) model to obtain a variety of new exact wave solutions. With the suitable selection of parameters involved in the model, some familiar physical governing models such as the Camassa–Holm (CH) equation, the Fornberg–Whitham (FW) equation, and the Rosenau–Hyman (RH) equation are obtained. The graphical representation of solutions under different constraints shows the dark, bright, combined dark–bright, periodic, singular, and kink soliton. For the graphical representation, 3D plots, contour plots, and 2D plots of some acquired solutions are illustrated. The obtained wave solutions motivate researchers to enhance their theories to the best of their capacities and to utilize the outcomes in other nonlinear cases. The executed methods are shown to be practical and straightforward for approaching the considered equation and may be utilized to study abundant types of NLEEs arising in physics, engineering, and applied sciences
Lane Line Detection and Object Scene Segmentation Using Otsu Thresholding and the Fast Hough Transform for Intelligent Vehicles in Complex Road Conditions
No full textAn Otsu-threshold- and Canny-edge-detection-based fast Hough transform (FHT) approach to lane detection was proposed to improve the accuracy of lane detection for autonomous vehicle driving. During the last two decades, autonomous vehicles have become very popular, and it is constructive to avoid traffic accidents due to human mistakes. The new generation needs automatic vehicle intelligence. One of the essential functions of a cutting-edge automobile system is lane detection. This study recommended the idea of lane detection through improved (extended) Canny edge detection using a fast Hough transform. The Gaussian blur filter was used to smooth out the image and reduce noise, which could help to improve the edge detection accuracy. An edge detection operator known as the Sobel operator calculated the gradient of the image intensity to identify edges in an image using a convolutional kernel. These techniques were applied in the initial lane detection module to enhance the characteristics of the road lanes, making it easier to detect them in the image. The Hough transform was then used to identify the routes based on the mathematical relationship between the lanes and the vehicle. It did this by converting the image into a polar coordinate system and looking for lines within a specific range of contrasting points. This allowed the algorithm to distinguish between the lanes and other features in the image. After this, the Hough transform was used for lane detection, making it possible to distinguish between left and right lane marking detection extraction; the region of interest (ROI) must be extracted for traditional approaches to work effectively and easily. The proposed methodology was tested on several image sequences. The least-squares fitting in this region was then used to track the lane. The proposed system demonstrated high lane detection in experiments, demonstrating that the identification method performed well regarding reasoning speed and identification accuracy, which considered both accuracy and real-time processing and could satisfy the requirements of lane recognition for lightweight automatic driving systems
A comparative analysis of generalized and extended (G′G)-Expansion methods for travelling wave solutions of fractional Maccari's system with complex structure
No full textFractional partial differential equations emerge as a prominent research area in recent times owing to their ability to depict intricate physical phenomena. Discovering travelling wave solutions for fractional partial differential equations is an arduous task, and several mathematical approaches devise to address this issue. This investigation aims to compare two distinguished methods, namely, the generalized (G′G)-Expansion and the extended (G′G)-Expansion, in discovering the most optimal travelling wave solutions for fractional partial differential equations. Our observations indicate that the generalized (G′G)-Expansion method surpasses the extended (G′G)-Expansion method regarding the count of travelling wave solutions obtained. Moreover, the generalized (G′G)-Expansion method furnishes a more comprehensive and in-depth comprehension of physical phenomena by revealing a greater number of travelling wave solutions. This exploration validates the effectiveness of the generalized (G′G)-Expansion method in resolving intricate fractional partial differential equations and underscores its potential for further investigation and application in a variety of fields. Lastly, this study demonstrates the effectiveness of the proposed approaches in discovering travelling wave solutions and shed light on the intricate behavior of waves through plotted graphs, thereby contributing to the body of knowledge on this subject
Application of neural network and dual-energy radiation-based detection techniques to measure scale layer thickness in oil pipelines containing a stratified regime of three-phase flow
No full textfirst_pagesettingsOrder Article Reprints
Open AccessArticle
Application of Neural Network and Dual-Energy Radiation-Based Detection Techniques to Measure Scale Layer Thickness in Oil Pipelines Containing a Stratified Regime of Three-Phase Flow
by Abdulilah Mohammad Mayet 1ORCID,Tzu-Chia Chen 2,3,*ORCID,Ijaz Ahmad 4,*,Elsayed Tag Eldin 5ORCID,Ali Awadh Al-Qahtani 1,Igor M. Narozhnyy 6,John William Grimaldo Guerrero 7ORCID andHala H. Alhashim 8
1
Electrical Engineering Department, King Khalid University, Abha 61411, Saudi Arabia
2
College of Management and Design, Ming Chi University of Technology, New Taipei City 243303, Taiwan
3
International College, Krirk University, Bangkok, 3 Ram Inthra Rd, Khwaeng Anusawari, Khet Bang Khen, Krung Thep Maha Nakhon 10220, Thailand
4
Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences (UCAS), Shenzhen 518055, China
5
Electrical Engineering Department, Faculty of Engineering & Technology, Future University in Egypt, New Cairo 11845, Egypt
6
Department of Commercialization of Intellectual Activity Resultse Center for Technology Transfer of RUDN University, Mining Oil and Gas Department, RUDN University, 117198 Moscow, Russia
7
Department of Energy, Universidad de la Costa, Barranquilla 080001, Colombia
8
Department of Physics, College of Science, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia
*
Authors to whom correspondence should be addressed.
Mathematics 2022, 10(19), 3544; https://doi.org/10.3390/math10193544
Received: 3 August 2022 / Revised: 15 September 2022 / Accepted: 17 September 2022 / Published: 28 September 2022
(This article belongs to the Special Issue Application of Artificial Neural Network as Mathematical Tool in Engineering and Management Problems)
Download Browse Figures Versions Notes
Abstract
Over time, oil pipes are scaled, which causes problems such as a reduction in the effective diameter of the oil pipe, an efficiency reduction, waste of energy, etc. Determining the exact value of the scale inside the pipe is very important in order to take timely action and to prevent the mentioned problems. One accurate detection methodology is the use of non-invasive systems based on gamma-ray attenuation. For this purpose, in this research, a scale thickness detection system consisting of a test pipe, a dual-energy gamma source (241Am and 133Ba radioisotopes), and two sodium iodide detectors were simulated using the Monte Carlo N Particle (MCNP) code. In the test pipe, three-phase flow consisting of water, gas, and oil was simulated in a stratified flow regime in volume percentages in the range from 10% to 80%. In addition, a scale with different thicknesses from 0 to 3 cm was placed inside the pipe, and gamma rays were irradiated onto the pipe; on the other side of the pipe, the photon intensity was recorded by the detectors. A total of 252 simulations were performed. From the signal received by the detectors, four characteristics were extracted, named the Photopeaks of 241Am and 133Ba for the first and second detectors. After training many different Multi-Layer Perceptron(MLP) neural networks with various architectures, it was found that a structure with two hidden layers could predict the connection between the input, extracted features, and the output, scale thickness, with a Root Mean Square Error (RMSE) of less than 0.06. This low error value guarantees the effectiveness of the proposed method and the usefulness of this method for the oil and petrochemical industry
Islanded green energy system optimal analysis using PV, wind, biomass, and battery resources with various economic criteria
No full textThe main goal of this paper is to design an efficient renewable energy system that meets the required electricity demands. Consequently, it is essential to find the most cost-effective hybrid system that can reduce energy costs and provide access to the required electricity generation. An international school in New Administrative Capital in New Cairo, Egypt was chosen as a study area for the proposed system. Solar, wind, and biomass resources are abundant at the chosen location throughout the year. Using the HOMER (hybrid optimization model for electric renewables) software, eight distinct models of renewable energy hybrid systems were designed, simulated, and optimized to meet the required load in this study. For wind and solar resources, the National Aeronautics and Space Administration (NASA) provided the input data; for biomass resources, real-time field data were used for the selected study site. In this study, lithium-ion and lead acid batteries were used to choose the most cost-effective option. The hybrid power system's PV, wind, and biomass generators were utilized to meet the load demand. The overabundance of energy requests was utilized to charge the battery banks as required when accessible to cover the load requirements during times of low energy production
Effects of stenosis and aneurysm on blood flow in stenotic-aneurysmal artery
No full textBlood is indeed a suspension of the different type of cells along with shear thinning, yield stress and viscoelastic characteristics, which can be expressed by Newtonian and a lot of non-Newtonian models. Choosing Newtonian fluid as a sample, an unsteady solver for Newtonian fluid is constructed to determine the transient flow of blood in the obscure region. In this probe, the computational unsteady flow of blood in artery with aneurysm and symmetric stenosis has been considered, which is novelty of current research. The results of this investigation can be applied to detect stenotic-aneurysmal diseases and enhance knowledge of the stenotic-aneurysmal artery, which may increase the understanding of medical science. The blood artery is modeled as a circular tube having a 0.3-m radius and a 2-m length along the horizontal axis. The velocity of blood is taken at 0.12 ms−1 so that the geometry satisfies the characteristics of the blood vessel. The governing mass and momentum equations are then solved by finite difference technique of discretization. In this research, important variations in blood pressure and velocity at stenosis and aneurysms in the artery are found. The significant influences on blood flow of the stenotic-aneurysmal artery for pressure and velocity profiles of blood are displayed graphically for the Newtonian model
Risk Probabilistic Characteristics for Contaminated Porcelain Insulator in the Egyptian Sinai Desert
No full textTransmission lines in the desert are exposed to the desert environment, which includes sandstorms as one of its hallmarks. A conductive layer develops with prolonged sand deposition and the presence of moisture, ambient humidity, and dew. The ensuing leakage current causes surface discharge, which limits the life of the insulator and interrupting the power supply. The locations of power lines in the Egyptian Sinai desert, where sandstorms are known to occur frequently, are exposed to such a risk. In order to estimate the danger of insulator failure, this paper studies the flow of leakage current on porcelain insulators that have been contaminated with sand. This work relies on accurate data collected and published in a prior study regarding Sinai, which mainly focused on contaminating sand’s grain sizes. Porcelain insulator is simulated using finite element method to determine the leakage current that results on its contaminated surface. The probabilistic characteristics of the insulator’s leakage current are derived using Monte Carlo technique, allowing for the risk assessment of insulator failure. This assessment can be used to justify the suitability of using this kind of insulator in Sinai
Multi-Objective Quantum-Inspired Seagull Optimization Algorithm
No full textObjective solutions of multi-objective optimization problems (MOPs) are required to balance convergence and distribution to the Pareto front. This paper proposes a multi-objective quantum-inspired seagull optimization algorithm (MOQSOA) to optimize the convergence and distribution of solutions in multi-objective optimization problems. The proposed algorithm adopts opposite-based learning, the migration and attacking behavior of seagulls, grid ranking, and the superposition principles of quantum computing. To obtain a better initialized population in the absence of a priori knowledge, an opposite-based learning mechanism is used for initialization. The proposed algorithm uses nonlinear migration and attacking operation, simulating the behavior of seagulls for exploration and exploitation. Moreover, the real-coded quantum representation of the current optimal solution and quantum rotation gate are adopted to update the seagull population. In addition, a grid mechanism including global grid ranking and grid density ranking provides a criterion for leader selection and archive control. The experimental results of the IGD and Spacing metrics performed on ZDT, DTLZ, and UF test suites demonstrate the superiority of MOQSOA over NSGA-II, MOEA/D, MOPSO, IMMOEA, RVEA, and LMEA for enhancing the distribution and convergence performance of MOPs
Self-Lubricating Pulsed Ion Beam-Assisted PTFE Coating of Titanium in Argon Discharge to Tailor Wear Resistance and Friction
No full textPolytetrafluoroethylene (PTFE) ions were deposited on titanium substrate by using a 1.5 kJ Mather plasma focus device in argon, equipped with a PTFE source. The PTFE and argon ions generated during different number of shots of dense plasma focus (DPF) resulted in deposition of PTFE on the Ti surface. Prepared samples were characterized for structural properties, elemental composition, surface morphology, wear resistance and frictional behavior by X-ray diffraction, energy dispersive X-ray, scanning electron microscope and pin on disc test, respectively. The area of the coherent X-ray scattering region of PTFE coated on Ti estimated by XRD is 9 nm. Both XRD and SEM show that the area of the coherent X-ray scattering region increases with the increase in the number of focus shots. The EDX results confirmed that the concentration of carbon and fluorine on the Ti substrate increases with the increase in energy of ion flux. Finally, the pin on disc test confirms that PTFE ion plasma coating on the Ti surface reduces the friction up to 35% and enhances wear resistance of the Ti surface up to 89%. The above analysis reflects that PTFE coating shows remarkable tribological behavior with low value of friction coefficient and enhanced value of wear resistance. Moreover, this study provides an intuition for organizing the design of self-lubricating and effective wear-resistant coatings
Mathematical analysis of unsteady blood flow through bifurcated abdominal aorta featured aneurysm
No full textAn abdominal aortic aneurysm (AAA) is a localized dilatation of abdominal aorta. This study investigates a 2-dimensional unsteady and laminar flow through a bifurcated artery with an aneurysm that is computationally and mathematically simulated using 3-dimensional geometry. The fluid used in this simulation is blood which is Newtonian for high shear rate. The computational technique is used to solve the equations that governs due to the flow. The flow of blood is analyzed with the assist of cut planes of pressure and velocity in the abdominal aortic aneurysm (AAA) for t=1s and t=4s. The pressure on the wall and complete velocity profile are also displayed with the assist of graphs. The streamlines are also shown with the help of graphs for t=1s and t=4s. The results can be used in the treatment of abdominal aortic aneurysm
- …
