Modeling and Simulation
L. Mahmoodi; B. Vaferi; M. Kayani
Volume 14, Issue 4 , December 2017, , Pages 48-58
Abstract
Temperature distribution is a key function for analyzing and optimizing the thermal behavior of various process equipments. Moving bed reactor (MBR) is one of the high-tech process equipment which tries to improve the process performance and its energy consumption by fluidizing solid particles in a base ...
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Temperature distribution is a key function for analyzing and optimizing the thermal behavior of various process equipments. Moving bed reactor (MBR) is one of the high-tech process equipment which tries to improve the process performance and its energy consumption by fluidizing solid particles in a base fluid. In the present study, thermal behavior of MBR has been analyzed through mathematical simulation. Good agreement between the obtained results and both experimental data and analytical solution by self-adjoint method is observed. Mathematical results confirm that the average particle temperature linearly increases across the reactor length. Fluid temperature changes in a parabolic manner, and then it changes linearly. Increasing the Biot number ( ) results in increasing the temperature gradient inside the particle to a maximum value, and thereafter a decreasing pattern is observed. The numerical results confirmed that the finite difference method can be used for thermal analysis of the moving bed reactor.
Biomedical and Biotechnology,
M. Saeedi; O. Vahidi
Volume 14, Issue 4 , December 2017, , Pages 59-79
Abstract
In this paper, we simulate magnetic hyperthermia process on a mathematical phantom model representing cancer tumor and its surrounding healthy tissues. The temperature distribution throughout the phantom model is obtained by solving the bio-heat equations and the consequent cell death amount is calculated ...
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In this paper, we simulate magnetic hyperthermia process on a mathematical phantom model representing cancer tumor and its surrounding healthy tissues. The temperature distribution throughout the phantom model is obtained by solving the bio-heat equations and the consequent cell death amount is calculated using correlations between the tissue local temperature and the cell death rate. To have an estimate of heat generated from typical magnetic nanoparticles, magnetite nanoparticles are synthesized and the heat dissipation amount from the synthesized nanoparticles exposed to an alternating magnetic field is measured and used in the computer simulation. The impact of the amount of heat generated from the magnetic nanoparticles exposed to an alternating magnetic field, their distribution patterns in the tumor and hyperthermia process duration time on the cell death rate in both cancer and healthy tissues are investigated. It is indicated that while various factors contributing in the heat dissipation amount from the magnetic nanoparticles are important in the effectiveness of the magnetic hyperthermia process, the distribution pattern plays the major role in determining the efficiency of the process.
Modeling and Simulation
I. Omidi; M. Kalbasi
Volume 14, Issue 2 , 2017, , Pages 17-32
Abstract
The performance of the solid acid fuel cell by CsH2PO4 electrolyte was analyzed using the present model of the electrochemical reaction and transport phenomena, which are fully coupled with the governing equations. Development of such a model requires creating the three-dimensional geometry and its mesh ...
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The performance of the solid acid fuel cell by CsH2PO4 electrolyte was analyzed using the present model of the electrochemical reaction and transport phenomena, which are fully coupled with the governing equations. Development of such a model requires creating the three-dimensional geometry and its mesh grid, discretization of momentum, mass and electric charge balance equation and solving the equations based on the information of electrical and electrochemical models in different areas of the cell consisting of porous electrodes, gas channels, and the solid parts like the current collector. The model equations were solved employing a finite elements technique solver of cell potential. Different parameters including current density (i), cell potential (V), cell power and concentration distribution of hydrogen, oxygen and water vapor have been investigated in this study. Also, the effect of different voltages on the concentration distribution of all the mentioned species through the cell length are taken into account. Comparing the polarization curve values with the experimental results shows a good agreement between the computed and experimental values (Maximum error is less than 4%). The results showed that there is a noticeable difference between H2, O2 and H2O concentration through the cell length subjected to various voltages. This difference was more apparent at lower voltages due to higher current density and higher consumption of species. The polarization curve is well consistent with the model and experimental data which verify the present simulation results.
Reaction Engineering, Kinetics and Catalysts,
Mahdi Bayat; M.R. Rahimpour
Volume 13, Issue 3 , July 2016, , Pages 3-18
Abstract
Nowadays, hydrogen and methanol are attractive prospects because of lower emission compared to the other energy sources and their special application in fuel cell technology, which are now widely regarded as key energy solution for the 21st century. These two chemicals also can be utilized in transportation, ...
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Nowadays, hydrogen and methanol are attractive prospects because of lower emission compared to the other energy sources and their special application in fuel cell technology, which are now widely regarded as key energy solution for the 21st century. These two chemicals also can be utilized in transportation, distributed heat and power generation and energy storage systems. In this study, a novel double fluidized-bed two-membrane reactor (DFTMR) is proposed to produce ultrapure hydrogen and enhance methanol synthesis as environmentally friendly fuels, simultaneously. The fluidization concept is used in both sides to overcome drawbacks such as internal mass transfer limitations, pressure drop, radial gradients of concentration and temperature in thermally coupled membrane reactors. The DFTMR system is modeled based on the two-phase theory of fluidization and then its performance is compared with those of thermally coupled membrane reactor (TCMR) and conventional methanol reactor (CR) under the same operating conditions. The simulation results show 24.69% enhancement in hydrogen production in comparison with TCMR. Furthermore, 14.39% and 15.78% improvement in the methanol yield can be achieved compared with TCMR and CR, respectively.
Petroleum and Reservoir Engineering
A. Mohammadi Doust; M. Rahimi; M. Feyzi
Volume 13, Issue 1 , January 2016, , Pages 3-19
Abstract
In this study, response surface methodology (RSM) based on central composite design (CCD) was applied for investigation of the effects of ultrasonic waves, temperature and solvent concentration on viscosity reduction of residue fuel oil (RFO). Ultrasonic irradiation was employed at low frequency of 24 ...
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In this study, response surface methodology (RSM) based on central composite design (CCD) was applied for investigation of the effects of ultrasonic waves, temperature and solvent concentration on viscosity reduction of residue fuel oil (RFO). Ultrasonic irradiation was employed at low frequency of 24 kHz and power of 280 W. The results showed that the combination of ultrasonic waves and solvent injection caused to further reduce of viscosity. To obtain optimum conditions and significant parameters, the results were analyzed by CCD method. In this method, maximum viscosity reduction (133 cSt) was attained in ultrasonic irradiation for 5 min, temperature of 50 °C and acetonitrile volumetric concentration of 5 % by means of experimental and three dimensional response surface plots. The kinematic viscosity decreased from 494 cSt to 133 cSt at the optimum conditions. In addition, a multiple variables model was developed by RSM which the second-order effect of ultrasonic irradiation time was significant on viscosity reduction of FRO. Finally, a comparison between the RSM with artificial neural network (ANN) was applied. The results demonstrated that both models, , were powerful to predict of kinematic viscosity of RFO. The results demonstrated that both models, RSM and ANN, with R2 more than 0.99 were powerful to predict kinematic viscosity of RFO.