In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity Ug , liquid velocity UL, liquid viscosity μL, and particle density ρs on bed porosity BP and solid holdups εg were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid velocities and liquid viscosity. Solid holdup with "low density particles" shows a higher numerical quantity "than that in the beds" with "high density". Levenberg-Marquardt back propagation of "artificial neural network (ANNs)" was utilized to predict the bed porosity and solid holdup. The expected values are in an excellent relationship with the experimental values, where the advanced model is high-fidelity and own a large capacity to predict bed porosity and solid holdup.
In the present study the performance of drying process of dffirent solid materials by batch fluidized bed drying
under vacuum conditions was investigated. Three, different solid materials, namely; ion exchange resin-8528,
aspirin and paracetamol were used. The behavior of the drying curves as well as the rate of drying of these
materials had been studied. The experiments were caried out in a 0.0381 m column diameter fluidized by hot
air under yacuum conditions. Four variables affecting on the rate of drying were studied' these variables are
vacuum pressure (100 - 500 mm Hg), air temperature (303-323 K), particle size (0.3-0.8 mm) and initial
moisture content (0.35-0.55 g/g solid)-for resin and (0.1-0.2 g/g soltid) for a
Focusing of Gaussian laser beam through nonlinear media can induce spatial self- phase modulation which forms a far field intensity pattern of concentric rings. The nonlinear refractive index change of material depends on the number of pattern rings. In this paper, a formation of tunable nonlinear refractive index change of hybrid functionalized carbon nanotubes/silver nanoparticles acetone suspensions (F-MWCNTs/Ag-NPs) at weight mixing ratio of 1:3 and volume fraction of 6x10-6 , 9x10-6 , and 18x10-6 using laser beam at wavelength of 473nm was investigated experimentally. The results showed that tunable nonlinear refractive indices were obtained and increasing of incident laser power density led to increase the nonlinear refractive inde
... Show MoreIn the present work experiments were conducted to study the effect of solid loading (1,5 and 9 vol.%) on the enhancement of carbon dioxide absorption in bubble column at various volumetric gas flow rate (0.75, 1 and 1.5 m3/h) and absorbent concentration (caustic soda)( 0.1,0.5 and 1 M ). Activated carbon and alumina oxide (Al2O3) are used as solid particles. The Danckwerts method was used to calculate interfacial area and individual mass transfer coefficients during absorption of carbon dioxide in a bubble column. The results show that the absorption rate was increased with increasing volumetric gas flow rate, caustic soda concentration and solid loading. Mass transfer coefficient and interfac
... Show MoreThe study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. Moreover, the sequence of inverse of Hessian matrix generated by the method would never approach a near-singular matrix, such that the program would never break before the minimum value of the objective function is obtained. Moreover, the new modification of BFGS update (H-vers
... Show MoreAssessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem
The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev
... Show MoreThe purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be
... Show MoreIn this study, thermal characteristics of a two-phase closed heat pipe were investigated experimentally and theoretically. A two-phase closed heat pipe (copper container, Fluorocarbon FC-72 (C6F14) working fluid) was fabricated to examine its performance under the effect of input heat flux range of 250–1253 W/m2 , 70% fill charge ratio and various tilt angles. The temperature distribution along the heat pipe, input heat to evaporator section, and output heat from condenser were monitored. A comprehensive mathematical model was developed to investigate the steadystate heat transfer performance of a two-phase closed heat pipe. A steady state analytical model, is presented to determine important parameters on the design of two-phase close
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