Cowpea is a very important legume in Nigeria that is being utilized to Substitute high-cost animal protein for low-income people. The knowledge of some physical properties of various moisture contents is of utmost importance in the design of its handling and processing equipment and machinery, which is the aim of this work, which studied the physical properties of IT99K-573-1-1 (SAMPEA14) variety of Cowpea within 8.77 to 21.58 % db moisture content. The properties studied include Major, Intermediate, and Minor diameters, Sphericity, Surface area, Specific gravity, Volume, Bulk density, 50-tap density, 100-tap density, 1250-tap density, seed mass, Angle of repose, Geometric mean diameter, and Arithmetic mean diameter. The obtained results indicate that the Size, Sphericity, Geometric, Arithmetic diameter, Surface area, and seed mass increase linearly with an increase in moisture content by 13.8%, 27.4%, and 16.1% for the size, respectively. While sphericity rises by 7.5% and geometric mean diameter, arithmetic mean diameter, surface area, and grain mass increase by 22.2%, 20.7%, 24.9%, and 16.11%, respectively. Specific gravity, density, and repose angle were inversely linearly related to moisture content. Regression equations for each of the properties related to the grains' moisture content were developed.
The specifications of lubricating oil are fundamentally the final product of materials that have been added for producing the desired properties. In this research, spherical nanoparticles copper oxide (CuO) and titanium oxides (TiO2) are added to SAE 15W40 engine oil to study the thermal conductivity, stability, viscosity of nano-lubricants, which are prepared at different concentrations of 0.1%, 0.2%, 0.5%, and 1% by weight, and also their pour point, and flash point as five quality parameters. The obtained results show that CuO nanoparticles in all cases, give the best functionality and effect on engine oil with respect to TiO2. With 0.1 wt. % concentration, the thermal conductivity of CuO/oil and TiO2/
... Show MoreThe growing demand for optical fibers is due to their superior the ability to transmit information with high efficiency and minimal loss across extensive distances. In this study, four optical fibers with core radii ranging from (2.05-5.05) μm, and with a numerical aperture of 0.1624 were analyzed. The modal properties of these fibers were calculated at a wavelength of 1030 nm using the RP Fiber Calculator software (free version 2025). Furthermore, the impact of increasing the core radius on these properties was examined. The results showed that multimode fibers are formed when the core radius is much larger than the wavelength used. In contrast, single-mode fiber is obtained when th
thin films of se:2.5% as were deposited on a glass substates by thermal coevaporation techniqi=ue under high vacuum at different thikness
This study was aime to investigate the effect of addition different concentration of celery leaves to white soft cheese ,Treated cheese between 2018-2019, ,The finely Celery (Apium graveolens) leaves were adding to crude white cheese after texturizing in three leveles included (A,B,C) in addition of control antimicrobial activity of celery treated cheese against total account bacteria and coliform bacteria was estimated during (0, 5, 10, 15, 20) days. The results were shown that the higher concentration of celery in treated cheese, had a lower concentration of protein, lipid and ash content ( 16.81,15.13 and 4.30% respectively, but it had a higher moisture content 59.50%.also the total bacteria counts were decreasing significantly (0.05 P)w
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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