The present work reports the performance of three types of polyethersulfone (PES) membrane in the removal of highly polluting and toxic lead Pb2+ and cadmium Cd2+ ions from a single salt. This study investigated the effect of operating variables, including pH, types of PES membrane, and feed concentration, on the separation process. The transport parameters and mass transfer coefficient (k) of the membranes were estimated using the combined film theory-solution-diffusion (CFSD), combined film theory-Spiegler-Kedem (CFSK), and combined film theory-finely-porous (CFFP) membrane transport models. Various parameters were used to estimate the enrichment factors, concentration polarization modulus, and Péclet number. The pH values significantly affected the permeation flux of the Pb2+ solution but only had a slight effect on the Cd2+ solution. However, Cd2+ rejection was highly improved by increasing the pH value. The rejection of the PES membranes increased greatly as the heavy metal concentration rose, while the heavy metal concentration moderately affected the permeation flux. The maximum rejection of Pb2+ in a single-salt solution was 99%, 97.5%, and 98% for a feed solution containing 10 mg Pb/L at pH 6, 6.2, and 5.7, for PES1, PES2, and PES3, respectively. The maximum rejection of Cd2+ in single-salt solutions was 78%, 50.2%, and 44% for a feed solution containing 10 mg Cd/L at pH 6.5, 6.2, and 6.5, for PES1, PES2, and PES3, respectively. The analysis of the experimental data using the CFSD, CFSK, and CFFP models showed a good agreement between the theoretical and experimental results. The effective membrane thickness and active skin layer thickness were evaluated using the CFFP model, indicating that the Péclet number is important for determining the mechanism of separation by diffusion.
Single mode-no core-single mode fiber structure with a section of tuned no-core fiber diameter to sense changes in relative humidity has been experimentally demonstrated. The sensor performance with tuned NCF diameter was investigated to maximize the evanescent fields. Different tuned diameters of of (100, 80, and 60)μm were obtained by chemical etching process based on hydrofluoric acid immersion. The highest wavelength sensitivity was obtained 184.57 pm/RH% in the RH range of 30% –100% when the no-core fiber diameter diameter was 60 μm and the sensor response was in real-time measurements
Over the last few years, there has been a worldwide increase in the use of composite materials for rehabilitation of deficient reinforced concrete structures. One important application of this technology is the use of Carbon Fiber Reinforced Polymer (CFRP) jacket to provide external confinement of reinforced concrete columns. Square concrete column specimens 100×100×1000 mm with concrete
compressive strength of about 30 and 50 MPa, steel fiber volume fraction 0%, 0.5%, 0.75%, and percentage of longitudinal reinforcement 2.01%, 3.14% and 4.52% were tested until failure in previous research. In this research seven tested columns were repaired and rehabilitated using one layer of CFRP flexible wraps and tested to determine their ultim
In this study, the mechanical properties of an epoxy and unidirectional woven carbon with fiberglass composite were experimentally investigated. When preparing the composite samples, American Society for Testing and Materials (ASTM)standard was used. Tensile, impact and flexural test were conducted to investigate the mechanical properties of the new produced epoxy Unidirectional Woven Carbon and Epoxy Fiberglass composites. The outcome showed that the strength of the produced samples increased with the increase in the number of unidirectional woven carbon layers added. Two methods were utilized: (1) woven carbon composite with glass fiber (2) woven carbon composite). The two methods of composite were compared with each other. The resul
... Show MoreIn 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.
Tin oxide was deposited by using vacuum thermal method on silicon wafer engraved by Computer Numerical Controlled (CNC) Machine. The inscription was engraved by diamond-made brine. Deep 0.05 mm in the form of concentric squares. Electrical results in the dark were shown high value of forward current and the high value of the detection factor from 6.42 before engraving to 10.41 after engraving. (I-V) characters in illumination with powers (50, 100, 150, 200, 250) mW/cm2 show Improved properties of the detector, Especially at power (150, 200, 250) mW/cm2. Response improved in rise time from 2.4 μs to 0.72 μs and time of inactivity improved 515.2 μs to 44.2 μs. Sensitivity angle increased at zone from 40o to 65o.
Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorit
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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