Pressure retarded osmosis (PRO) can be considered as one of the methods for utilizing osmotic power, which is a membrane-based technology. Mathematical modeling plays an essential part in the development and optimization of PRO energy-generating systems. In this research, a mathematical model was developed for the hollow fiber module to predict the power density and the permeate water flux theoretically. Sodium chloride solution was employed as the feed and draw solution. Different operating parameters, draw solution concentration (1 and 2 M), the flow rate of draw solution (2, 3, and 4 L/min), and applied hydraulic pressure difference (0 - 90 bar) was used to evaluate the performance of PRO process of a hollow fiber module. The effect of these operational parameters was investigated on the theoretical permeate water flux and power density. According to the theoretical results, the permeate water flux and the power density increased with increasing the concentration of draw solution and the flow rate of the draw solution. While decreased with increasing the feed solution concentration. By increasing the applied hydraulic pressure on the draw solution, the water flux decreased and the produced power density increased. The maximum power density and the corresponding permeate water flux of 2 M NaCl draw solution was approximately 16.414 W/m2 and 11.818 LMH respectively, which occurs at an applied hydraulic pressure of 50 bar.
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
... Show MoreThe present study focuses on synthesizing solar selective absorber thin films, combining nanostructured, binary transition metal spinel features and a composite oxide of Co and Ni. Single-layered designs of crystalline spinel-type oxides using a facile, easy and relatively cost-effective wet chemical spray pyrolysis method were prepared with a crystalline structure of MxCo3−xO4. The role of the annealing temperature on the solar selective performance of nickel-cobalt oxide thin films (∼725 ± 20 nm thick) was investigated. XRD analysis confirmed the formation of high crystalline quality thin films with a crystallite si
In most manufacturing processes, and in spite of statistical control, several process capability indices refer to non conformance of the true mean (µc ) from the target mean ( µT ), and the variation is also high. In this paper, data have been analyzed and studied for a blow molded plastic product (Zahi Bottle) (ZB). WinQSB software was used to facilitate the statistical process control, and process capability analysis and some of capability indices. The relationship between different process capability indices and the true mean of the process were represented, and then with the standard deviation (σ ), of achievement of process capability value that can reduce the standard deviation value and improve production out of theoretical con
... Show MoreThermal decomposition of used tires was studied under atmospheric pressure and thermal heating program up to 350 °C for 110-120 min in a glass reactor. The effects of using MgO or SiO2 as catalyst in the thermal pyrolysis of tires waste on the yield ratio, reaction time, initial degree of decomposition also the contents of BTEX compounds in resulting pyrolytic oil was estimated via GC-FID. The results showed that the MgO catalyst gave a gas output in proportion of 17.063%, a liquid in a proportion of 38.245% and a solid product in proportion of 44.733%, while the SiO2 catalyst gave proportions of 14.308%, 40.161% and 45.448% for gas, liquid and solid products respectively. The results revealed that the thermal pyrolysis produced minor cont
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Statistical control charts are widely used in industry for process and measurement control . in this paper we study the use of markov chain approach in calculating the average run length (ARL) of cumulative sum (Cusum) control chart for defect the shifts in the mean of process , and exponentially weighted moving average (EWMA) control charts for defect the shifts for process mean and , the standard deviation . Also ,we used the EWMA charts based on the logarithm of the sample variance for monitoring a process standard deviation when the observations (products are selected from al_mamun factory ) are identically and independently distributed (iid) from normal distribution in continuous manufacturing .
Two oil wells were tested to find the abnormal pressure zones using sonic log technique. We found that well Abu-Jir-3 and Abu-Jir-5 had an abnormal pressure zones from depth 4340 to 4520 feet and 4200 to 4600 feet, respectively. The maximum difference between obtained results and the field measured results did not exceed 2.4%.
In this paper, the formation pressures were expressed in terms of pressure gradient which sometimes reached up to twice the normal pressure gradient.
Drilling and developing such formations were dangerous and expensive.
The plotted figures showed a clear derivation from the normal trend which confirmed the existence of abnormal pressure zones.