Performance of gas-solid spouted bed benefit from solids uniformity structure (UI).Therefore, the focus of this work is to maximize UI across the bed based on process variables. Hence, UI is to be considered as the objective of the optimization process .Three selected process variables are affecting the objective function. These decision variables are: gas velocity, particle density and particle diameter. Steady-state solids concentration measurements were carried out in a narrow 3-inch cylindrical spouted bed made of Plexiglas that used 60° conical shape base. Radial concentration of particles (glass and steel beads) at various bed heights and different flow patterns were measured using sophisticated optical probes. Stochastic Genetic Algorithm (GA) has been found better than deterministic search for study mutation of process variables of the non-linear bed. Spouted bed behaved as hybrid system. Global GA could provide confirmed data and selected best operating conditions. Optimization technique would guide the experimental work and reduce the risk and cost of operation. Optimum results could improve operating of the bed at high-performance and stable conditions. Maximum uniformity has been found at high-density, small size of solid beads and low gas velocity. Density of solids has been effective variable on UI.Velocity of gas and diameter of solid particles has been observed more sensitive decision variables with UI mutations. Uniformity of solid particles would enhance hydrodynamic parameters, heat and mass transfer in the bed because of improving of hold-up and voids distributions of solids. The results of the optimization have been compared with the experimental data using sophisticated optical probe and Computed Tomography technique.
Amaranthus viridis L. belongs to the Amaranthaceae family. It is a rich source of numerous phytochemicals and amino acids. The objective of this work was to optimize Ultrasound-Assisted Extraction (UAE) based on the extraction yield and Thin-Layer Chromatography (TLC) profile under different conditions, to compare the optimized UAE to the Soxhlet extraction method and evaluate the cytotoxic effects of the ethyl acetate fraction of the 80 % ethanolic extract on the SKGT-4 (human esophageal adenocarcinoma), AGS (human gastric adenocarcinoma) and A431 (human epidermoid carcinoma). A one-factor at a time experiment was carefully designed to assess the influence of the following factors on the extraction: time, frequency, solid-to-solven
... Show More
(34)
(32)
This work investigates the impacts of eccentric-inclined load on ring footing performance resting on treated and untreated weak sandy soil, and due to the reduction in the footing carrying capacity due to the combinations of eccentrically-inclined load, the geogrid was used as reinforcement material. Ring radius ratio and reinforcement depth ratio parameters were investigated. Test outcomes showed that the carrying capacity of the footing decreases with the increment in the eccentric-inclined load and footing radius ratio. Furthermore, footing tilt and horizontal displacement increase with increasing the eccentricity and inclination angle, respectively. At the same time, the increment in the horizontal displacement due t
... Show More
(2)
(2)
Despite the broad approbation of additive manufacturing technologies over diverse industries, printed parts’ performance, quality, and related build time are still greatly influenced by printing parameters. These parameters majorly affect mechanical strength, surface finish, dimensional accuracy, and overall production time of the printed part. Customized 3D printing layer thickness, speed, and acceleration are crucial parameters that affect the speedy printing process and final product quality. The current work considers layer thickness in addition to speed and high acceleration values effect on the surface quality, surface roughness and productivity time of 3D printed Polylactic Acid (PLA). The experimental methodology implemented withi
... Show More
(3)
(2)
(1)
(1)
The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of
... Show More
(9)
(5)
(35)
(34)