In the present work, a closed loop circulation system consist of three testing sections was designed and constructed. The testing sections made from (3m) of commercial carbon steel pipe of diameters(5.08, 2.54 and 1.91 cm) . Anionic surfactant (SDBS )with concentrations of (50, 100, 150, 200 and 250 ppm) was tested as a drag reducing agent. The additive(SDBS)studied using crude oil from south of Iraq. The flow rates of crude oil were used in 5.08 and 2.54 cm I.D. pipes are (1 - 12) m3/hr while (1-6) m3/hr were used in 1.91 cm J .D. pipe . Percentage drag reduction (%Dr) was found to increase by increasing solution velocity, pipe diameter and additives concentration (i.e. increasing Renolds number). Also it was found that there is no change in apparent physical properties (viscosity) of crude oil after the addition of SDBS. The higher value of drag reduction of 54% in 5.08 cm I.D. was observed using 250 ppm SDBS surfactant dissolved in the used crude oil at flow rate of 12 m3/hr. Friction factor was calculated from experimental data. The friction factors values for pure solvent lies near or at Blasius asymptote suggested for flow of Newtonian fluids. After the addition of small amount of SDBS, the friction factor values were positioned below Blasius asymptote toward Virk maximum drag reduction asymptote, which was never reached.
Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia
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The fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascal's triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely develo
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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In this paper, third order non-polynomial spline function is used to solve 2nd kind Volterra integral equations. Numerical examples are presented to illustrate the applications of this method, and to compare the computed results with other known methods.
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In this work we used the environmentally friendly method to prepared ZrO2 nanoparticles utilizing the extract of Thyms plant In basic medium and at pH 12, the ZrO2 NPs was characterized by different techniques such as FTIR, ultraviolet visible, Atomic force microscope, Scanning Electron Microscopy, X-ray diffraction and Energy dispersive X-ray. The average crystalline size was calculated using the Debye Scherres equation in value 7.65 nm. Atomic force microscope results showed the size values for ZrO2 NPs were 45.11nm, and there are several distortions due to the presence of some large sizes. Atomic force microscope results showed the typical size values for ZrO2 NPs were 45.11 nm, and there are several distortions due to the presence of so
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