A numerical investigation has been performed to study the effect of eccentricity on unsteady state, laminar aiding mixed convection in a horizontal concentric and eccentric cylindrical annulus. The outer cylinder was kept at a constant temperature
while the inner cylinder was heated with constant heat flux. The study involved numerical solution of transient momentum (Navier-Stokes) and energy equation using finite difference method (FDM), where the body fitted coordinate system (BFC) was
used to generate the grid mesh for computational plane. The governing equations were transformed to the vorticity-stream function formula as for momentum equations and to the temperature and stream function for energy equation.
A computer program (Fortran 90) was built to calculate the bulk Nusselt number (Nub) after reaching steady state condition for fluid Prandtl number fixed at 0.7 (air) with radius ratio ( =2.6), Rayleigh number (Ra=200), Reynolds number (Re=50) for both concentric and eccentric cylindrical annulus with different eccentricity ratios (ε=0, 0.25, 0.50, 0.75) and angular positions (φo=0o
, 45o , 90o , 135o , 180o ).
The results show a reasonable representation to the relation between Nusselt number and (ε, φo). Generally, Nub decreased with the increase in (ε and φo). Also, results show that the best thermal performance for the inner cylinder was at the angular
position (φo=0o ) for eccentricity ratio (ε=0.25), while the maximum reduction in the rate of heat transfer for the inner cylinder was at the angular position (φo=180o) for eccentricity ratio (ε=0.75).
Comparison of the result with the previous work shows a good agreement.
This study aimed to investigate the feasibility of treatment actual potato chips processing wastewater in a continuously operated dual chambers microbial fuel cell (MFC) inoculated with anaerobic sludge. The results demonstrated significant removal of COD and suspended solids of more than 99% associated with relatively high generation of current and power densities of 612.5 mW/m3 and 1750 mA/m3, respectively at 100 Ω external resistance.
Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac
... Show MorePolycystic ovary syndrome (PCOS) is one of the most common endocrine disorder. To determine the metabolic disorders in women with PCOS, (25) women with PCOS ages (15 - 47) years have been investigated and compared with (20) healthy individuals. All the studied groups were carried out to measure fasting blood sugar, (anti-GAD Ab, anti ?-islet cell Ab by IFAT) and measured insulin level by ELISA. There was significant elevation in the concentration of fasting blood sugar than in control groups (p ? 0.05) and there was negative results for anti-GAD Ab and anti ?-islet cell Ab by IFAT test for serum of women with PCOS, while there was significant differences in the insulin level for women with PCOS compared with control groups (p ? 0.05), these
... Show MoreWith the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica
... Show MoreAssessment of Salivary Macrophage Inflammatory Protein-1 Alpha Level in Different Stages of Periodontitis, Riyam Muthanna Muhammed*, Hadeel Mazin Akram
Objective Neutrophils own an arsenal of dischargeable chemicals that enable them to handle bacterial challenges, manipulating innate immune response and actual participation in acquired immunity. The reactive oxygen species (ROS) are one of the most important chemicals that neutrophils discharge to eradicate pathogens. Despite their beneficial role, the ROS were strongly correlated to periodontal tissue destruction. Lowdensity neutrophils (LDN) have been recognized for producing enhanced quantities of ROS. However, the potential role of ROS produced by LDN in periodontitis is unknown. The aim of the study was to investigate the impact of ROS produced by LDN in periodontal diseases.
Current design codes and specifications allow for part of the bonded flexure tension reinforcement to be distributed over an effective flange width when the T-beams' flanges are in tension. This study presents an experimental and numerical investigation on the reinforced concrete flanged section's flexural behavior when reinforcement in the tension flange is laterally distributed. To achieve the goals of the study, numerical analysis using the finite element method was conducted on discretized flanged beam models validated via experimentally tested T-beam specimen. Parametric study was performed to investigate the effect of different parameters on the T-beams flexural behavior. The study revealed that a significant reduction in the
... Show MoreThe continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre
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