Electrospinning is a novel technique that can be used to produce highly porous fibers with highly tunable properties. In this research, this technique is adopted to prepare the electrospun nanofiber membrane for membrane distillation application. A custom-built electrospinning setup was made to prepare the nanofibers membrane. Polyvinylidene fluoride (PVDF) polymer was used in the electrospinning process due to its high hydrophobicity. Electrospun (PVDF) nanofibers were tested in direct contact membrane distillation (DCMD) process using 0.6 M sodium chloride as a feed solution. The resulting nanofiber membrane exhibited high performance in DCMD (i.e. relatively high water flux and high salt rejection). It has been found that the prepared membrane has a uniform and fibrous structure as indicated by the scanning electron microscopy (SEM). Relatively thin fibers with a diameter of 250 nm were produced during the Electrospinning process.
Calculations of sputtering yield for Lithium,Sodium and Krypton bombarded by the same own ions are achieved by using TRIM program.The relation of angular dependent of sputtering yield for each ion/target is studied. Also, the dependence of the sputtering yield of target on the energy of the same ion is discussed and plotted graphically. Many researchers applied polynomials function to fit the sputtering data from experimental and simulation programs, however, we suggest to use Ior function for fitting the angular distribution of the sputtering yield. A New data for fitting coefficients of the used ion/target are presented by applying used function for the dependence of the sputtering yield on the ion energy.
This paper presents the Taguchi approach for optimization of hardness for shape memory alloy (Cu-Al-Ni) . The influence of powder metallurgy parameters on hardness has been investigated. Taguchi technique and ANOVA were used for analysis. Nine experimental runs based on Taguchi’s L9 orthogonal array were performed (OA),for two parameters was study (Pressure and sintering temperature) for three different levels (300 ,500 and 700) MPa ,(700 ,800 and 900)oC respectively . Main effect, signal-to-noise (S/N) ratio was study, and analysis of variance (ANOVA) using to investigate the micro-hardness characteristics of the shape memory alloy .after application the result of study shown the hei
... Show MoreSolid‐waste management, particularly of aluminum (Al), is a challenge that is being confronted around the world. Therefore, it is valuable to explore methods that can minimize the exploitation of natural assets, such as recycling. In this study, using hazardous Al waste as the main electrodes in the electrocoagulation (EC) process for dye removal from wastewater was discussed. The EC process is considered to be one of the most efficient, promising, and cost‐effective ways of handling various toxic effluents. The effect of current density (10, 20, and 30 mA/cm2), electrolyte concentration (1 and 2 g/L), and initial concentration of Brilliant Blue dye (15 and 30 mg/L) on
This investigation aims to explore the potential of waterworks sludge (WS), low-cost byproduct of water treatment processes, as a sorbent for removing Congo Red (CR) dyes. This will be achieved by precipitating nano-sized (MgAl-LDH)-layered double hydroxide onto the surface of the sludge. The efficiency of utilizing MgAl-LDH to modify waterworks sludge (MWS) for use in permeable reactive barrier technology was confirmed through analysis with Fourier transform infrared and X-ray diffraction. The isotherm model was employed to elucidate the adsorption mechanisms involved in the process. Furthermore, the COMSOL model was utilized to establish a continuous testing model for the analysis of contaminant transport under diverse conditions.
... Show MoreSurvival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re
... Show MoreThe problem of generated waste as a result of the implementation of construction projects, has been aggravated recently because of construction activity experienced by the world, especially Iraq, which is going through a period of reconstruction, where construction waste represents (20-40%) of the total generated waste and has a negative effect on the environment and economic side of the project. In addition, the rate of consumpted amounts of natural resources are estimated to be about 40% in the construction industry, so it became necessary to reduce waste and to be manage well. This study aims to identify the key factors affecting waste management through the various phases of the project, and this is accom
... Show MoreBackground: The bonded orthodontic retainer constructed from multistrand wire and composite is an efficient esthetic retainer, which can be maintained long-term. Clinical failures of bonded orthodontic retainers, most commonly at the wire/composite interface, have been reported. This in vitro investigation aimed to evaluate the tensile forces of selected multistrand wires and composite materials that are available for use in the construction of bonded fixed retainers. Materials and Methods: The study sample includes 120 wires with three types of retainer wires (3 braided strands\ Orthotechnology, 8 braided strands\ G&H Orthodontics, 6 coaxial strands\ Orthoclassic wires), two types of adhesive (flowable\ Orthotechnology, non flowable\ G&H O
... Show MoreThe 3-parameter Weibull distribution is used as a model for failure since this distribution is proper when the failure rate somewhat high in starting operation and these rates will be decreased with increasing time .
In practical side a comparison was made between (Shrinkage and Maximum likelihood) Estimators for parameter and reliability function using simulation , we conclude that the Shrinkage estimators for parameters are better than maximum likelihood estimators but the maximum likelihood estimator for reliability function is the better using statistical measures (MAPE)and (MSE) and for different sample sizes.
Note:- ns : small sample ; nm=median sample
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