Metal foam has recently been used in many engineering applications, such as solar collectors, heat exchangers, and cooling of electronic devices, which calls for studying different cases of using metal foam in these applications. The current study conducts a numerical analysis of heat transfer and fluid flow characteristics for air in a rectangular channel filled with high-porosity copper foam. The study examined the thermal performance for two cases of gradient pore density, which are arranged as (10-20-40) PPI and (40-20-10) PPI. These cases were compared with two other cases for constant pore density, 10 and 40 PPI, and empty cases. The ANSYS FLUENT 20.0 employed the Darcy-Forchheimer extended Brickman model in the two-dimensional domain with the local thermal non-equilibrium model (LTNE) for the energy equation to obtain the numerical simulation for this study. The working parameters included air with Re from 200 to 2100 and applied heat flux from 450 to 6000 W/m2. The results indicated that employing metal foam with a low pore density led to a decrease in both the Nusselt number and pressure drop. Both gradient cases exhibited Nusselt numbers and friction factors that fell within the range of the constant PPI cases, but one of the gradient cases increased the performance factor by 10%. In general, the PPI configuration of 10-20-40 exhibited a higher heat transfer coefficient in comparison to the 40-20-10 PPI arrangement with the same pressure drop.
Composite materials are widely used in the engineered assets as aerospace structures, marine and air navigation owing to their high strength/weight ratios. Detection and identification of damage in the composite structures are considered as an important part of monitoring and repairing of structural systems during the service to avoid instantaneous failure. Effective cost and reliability are essential during the process of detecting. The Lamb wave method is an effective and sensitive technique to tiny damage and can be applied for structural health monitoring using low energy sensors; it can provide good information about the condition of the structure during its operation by analyzing the propagation of the wave in the
... Show MoreThe study aimed to investigate the effect of different times as follows 0.5, 1.00, 2.00 and 3.00 hrs, type of solvent (acetone, methanol and ethanol) and temperature (~ 25 and 50)ºc on curcumin percentage yield from turmeric rhizomes. The results showed significant differences (p? 0.05) in all variables. The curcumin content which were determined spectrophotometrically ranged between (0.55-2.90) %. The maximum yield was obtained when temperature, time and solvent were 50ºC, 3 hrs and acetone, respectively.
A series of new 4-(((4-(5-(Aryl)-1,3,4-oxadiazol-2-yl)benzyl)oxy)methyl)-2,6-dimethoxy phenol (6a-i) were synthesized from cyclization of 4-(((4-hydroxy-3,5-dimethoxy benzyl)oxy)methyl)benzohydrazide with substituted carboxylic acid in the presences of phosphorusoxy chloride.The resulting compounds were characterized by IR, 1H-NMR, 13C-NMR, and HRMS data. 2,2-Diphenyl-1-picrylhydrazide (DPPH) and ferric reducing antioxidant power (FRAP) assays were used to screen their antioxidant properties. Compounds 6i and 6h exhibited significant antioxidant ability in both assay. Furthermore, type of substituent and their position of the aryl attached 1,3,4-oxadiazole ring at position five are play an important roles in enhancing or declining the antio
... Show MoreMultiple Sclerosis (MS), is a common autoimmune disease that affects the central nervous system. Currently, there is no cure for MS, and most treatments involve the use of immunosuppressive drugs that can have adverse effects or increased toxicity. Cannabis, commonly known as marijuana, is a product of the Cannabis sativa, and for several centuries has been used as an alternative medicine in many cultures. Cannabis sativa produces over 421 chemical compounds, including about 80 terpenophenols named phytocannabinoids, and include both psychotropic THC and non-psychoactive CBD. In the currently study, we show that a combination therapy using THC and CBD results in amelioration of EAE, a
The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
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