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259 research outputs found
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Utilize Ground Hazelnut Shells and Willow Decoction to Improve the Effectiveness of Drilling Mud
No full textcrucial to follow environmental regulations when preparing drilling mud. These regulations are becoming more important and will remain significant in the future. It\u27s essential to use sustainable, eco-friendly materials at every stage of the oil and gas industry to uphold high standards of sustainable practices. This study investigates how adding Nano 10 Nano meter ground hazelnut shells and willow leaf water can improve lubrication and reduce friction in drilling fluid. The results show that incorporating these environmentally friendly materials also impacts other properties of the drilling fluid, including viscosity, density, filtration, and stability. The findings demonstrate that these materials reduced filtration and density, while improving stability and viscosity. When compared to conventional additives like carboxyl methyl cellulose and diesel oil, the additives used in this study showed promising efficiency, economic viability, and environmental benefits. As per the laboratory results, the Model 12 demonstrated superior performance due to its composition of 15g of Ground Hazelnut Shells, 88ml of diesel, 10g of Ben, 25 gm of Willow Decoction, and 350ml of water. The results showed that the lubrication coefficient for Model 12 was 0.89, which is the best, and the stability after 24 hours was 1%, and after 48, 72, and a week, the stability was 1.5, which is the best, as the lower the value for stability, the better the model, and this is what the above-mentioned model indicated
A Review of Seismic Behavior of Circular Shallow Foundations Using PLAXIS
No full textThis This paper presents a comprehensive review of the seismic behavior of circular shallow foundations, with a focus on the role of soil-structure interaction (SSI) under earthquake loading. Both experimental and numerical studies are examined, including large-scale shaking table tests, advanced finite element simulations using PLAXIS, and analytical models. Special attention is given to the effects of dynamic loads, liquefaction, bearing capacity, settlement, foundation uplift, and nonlinear soil behavior. Geogrid-reinforced soils and their potential in improving seismic performance are also discussed. The review highlights recent developments in SSI modeling, parametric studies on soil and footing properties, and the influence of ground motion characteristics. Limitations in current modeling approaches and gaps in experimental data are identified, suggesting directions for future research. The findings aim to support improved design methodologies for safer and more resilient foundation systems in seismic regions.
EVALUATING THE ACCURACY OF CLASSICAL AND BAYESIAN CONFIDENCE INTERVALS FOR THE POISSON MEAN
No full textThis research aims to evaluate and compare classical (frequentist) confidence intervals and Bayesian confidence intervals in estimating the mean of the Poisson distribution (λ).
The study relied on a systematic computer simulation approach to compare the main classical methods (such as Garwood, modified Wald, Begaud) and Bayesian methods (such as Jeffreys and HPD). The simulations were conducted by generating 10,000 Poisson samples for various λ levels (0.1–20) and sample sizes (n) (5–100).
Custom Python algorithms were used: SciPy to calculate inverse distributions, NumPy for statistical simulation, and Matplotlib to visualize the results.
The evaluation criteria were applied: actual coverage (% coverage), expected interval length (E(L)), and non-coverage equilibrium.
And The important results that research reached is following: Bayesian superiority in small samples: Bayesian-Jeffreys intervals achieved coverage closer to the 95% confidence level when n<30 (coverage: 92–94% versus 85–90% for classical methods).
Narrow Bayesian intervals: Bayesian HPD intervals were 15–30% shorter than classical methods when λ<5.
Performance of classical methods: Garwood\u27s (exact) method demonstrated overconservatism (coverage up to 98%), increasing the interval length by 40% when n=10
Advanced Numerical Methods for Solving Nonlinear Differential Equations: Theory, Algorithms, and Applications
No full textNonlinear differential equations (NDEs) are considered a crucial part in modeling complex physical, biological, and engineering systems. Classical numerical methods exhibit limitations in stability, accuracy, and efficiency. The purpose of this paper is to present a comprehensive review and analysis of advanced methods for solving NDEs. In this paper, we focused on recent numerical novel algorithms and laid the theoretical foundations and practical performance considerations
A Hybrid EPO-SVM Model for Efficient Anaemia Classification
No full textAnemia, a prevalent blood disorder affecting approximately 1.62 billion people worldwide, represents a significant global health challenge requiring accurate and efficient diagnostic methods. Traditional manual analysis of peripheral blood smear (PBS) images for anemia classification is time-consuming, error-prone, and requires specialized expertise. This paper presents a novel hybrid approach that integrates the Emperor Penguin Optimizer (EPO) algorithm for feature selection with Support Vector Machine (SVM) classifier to achieve efficient anemia classification from microscopic red blood cell (RBC) images. The proposed methodology addresses the critica challenge of high-dimensional feature spaces in medical image analysis by employing EPO\u27s bio-inspired optimization capabilities to reduce feature dimensionality from 121 extracted features to approximately 64 optimal features. The hybrid EPO-SVM mode demonstrates superior performance in terms of classification accuracy, reduced computational complexity, and enhanced diagnostic efficiency. Experimental results show significant improvements in accuracy (93.2%) while substantially reducing training time (51.3% reduction) compared to traditional approaches using full feature sets. The integration of EPO\u27s huddling behavior-inspired optimization with SVM\u27s robust classification capabilities provides a promising solution for automated anemia diagnosis, contributing to more accessible and reliable healthcare diagnostics
Numerical Methods for Eigenvalue Problems
No full textThis investigation centers on tactics for overseeing eigenvalues, merging both established and current methodologies. In various fields like engineering and science, eigenvalues serve an essential purpose, impacting crucial functions such as structural evaluations and quantum studies. Approaches like the Power Method and QR method run into obstacles, mainly when managing large or sparse matrices. The primary eigenvalue is disclosed through the power method, but the QR method does compute eigenvalues and may find larger matrices to be problematic. This paper delves into iterative techniques that enhance efficiency for extensive systems through Lanczos and Arnoldi, all while reducing size. Additionally, it will examine strategies aimed at accelerating operational processes, highlighting parallel execution and proactive conditioning, to enhance the effectiveness of iterative methods. In the near past, the landscape of quantum computing has transformed, alongside the progress of quantum systems that incorporate machine learning to handle eigenvector complications. An elaborate investigation into progressive eigenvalue calculation methods could aid professionals in attaining their targets with superior dexterity and capability
Ethical and Technical Challenges of Using Artificial Intelligence in Military Robots
No full textThough their use creates great operational advantages as well as technical and moral problems. Although these systems try to lower human personnel hazards, quicken response times, and, in addition to improving mission efficiency, they also pose serious issues of accountability for deadly decisions, compliance with international humanitarian law (IHL), and the potential algorithmic bias undermining civil life. Incorporating technology dangers such cyber security vulnerabilities, system dependability in conflict zones, and the adaptability of artificial intelligence in fast combat adds still further complication. circumstances. Study suggests a new Ethical Technical Governance Framework (ETGF) emphasizing embedded ethical principles, Ongoing human observation and independent audits ensure ethical and legal application of artificial intelligence. By blending defense aims with legal and moral responsibilities, this research offers pragmatic direction for legislators, military groups, and AI developers, therefore extending the discussion. regarding ethical artificial intelligence in military environments
Comparative Study of Slotless and Slotted Feedline Microstrip Patch Antennas for Multiband Millimetre-Wave Operation
No full textModern communication systems, such as fifth-generation (5G) networks, require antennas with a simple structure, lightweight, and high gain to achieve efficient performance. However, designing compact and effective antennas capable of working in the millimeter-wave (mmWave) band with multiband capability remains a challenge. This paper presents the design and simulation of two ultra-compact rectangular microstrip patch antennas with feedline transmission, fabricated on a compact Rogers RT5880 (lossy) substrate with a small size (1.52 mm×2 mm). The first design (RMSPA-I) is a traditional rectangular patch antenna without a slot, while the second (RMSPA-II) is incorporates an H-shaped slot on the patch plane and a slot on the ground plane to improve performance. Both designs achieve multiband operation, with RMSPA-I resonating at (2.3GHz and 95.3GHz), and RMSPA-II resonating at (2.3GHz, 73.5GHz, and 88.5GHz). The proposed designs demonstrate improved gain, VSWR, and return loss compared to existing works, while maintaining ultra-compact dimensions suitable for modern mmWave communication systems, including 5G and beyond
The influence of bending on weld joint integrity of Refrigeration Tube using x-ray Technique
No full text
In this investigation bending is applied on pure copper pipe with a weld joint made by oxyacetylene welding method to access the integrity and soundness of the weld joint under this type of mechanical testing, the chemical composition inspection of pipes metals is confirmed that is a pure copper (99.96% Cu). Pure copper is known to be weld able and can produce a weldment with good mechanical properties. High achievement weld joint resistance under bending without any evidence of surface defects and internal discontinuities that was confirmed by applying a liquid penetrant examination for the weld surfaces and also using x-ray test to detect internal defects. All tests’ processes were confirmed that, all weld rejoin is free from all possible discontinuities after performing bend testing.
Synergetic Effect of Nano-Particle Synthesized from the Bran of Rice with Petroleum for Enhancing Crude Oil Physical Properties
No full textThis study modified zinc oxide nanoparticles using rice bran. Rice bran is crucial for zinc oxide nanoparticle production. Finally, XRD and SEM investigations verified nanoparticle production quality. Photos showed the synthesized organic zinc oxide nano-particles\u27 surface uniformity. Afterwards, medium and light crud oils were treated with customized nanoparticles at varying weight percentages. At pressures from 10 to 300 bar, injection was done at 30-150 C. Adding rice bran to the adhesion force of light or medium crud oil molecules modified organic zinc oxide nanoparticles. Both the light and medium crud oil samples showed a rise in thermal conductivity from 0.19 to 2.45 W/m C and 1.61 to 6.45 W/m C, respectively, as the working temperature was raised. Findings showed that asphaltene precipitation % fell as crud oil API grew. Nano-light and medium crud oil had more asphaltene precipitation than basic light and medium crud oil. Nanoparticles improved reservoir crud oil recovery. Compared to normal light crud oil, light crud oil nanoparticles reduce asphaltene precipitation by 28.3%. Compared to simple medium crud oil, this is an 8.1% increase