Modeling
A. Shahraki; M. Khojastehpour; M. R. Golzarian; E. Azarpazhooh
Abstract
IntroductionDrying is one of the oldest methods of food preservation. To increase the efficiency of heat and mass transfer while maintaining product quality, the study of the drying process is crucial scientifically and meticulously. It is possible to conduct experimental tests, trial and error, in the ...
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IntroductionDrying is one of the oldest methods of food preservation. To increase the efficiency of heat and mass transfer while maintaining product quality, the study of the drying process is crucial scientifically and meticulously. It is possible to conduct experimental tests, trial and error, in the drying process. However, this approach consumes time and cost, with a significant amount of energy resources. By harnessing available software and leveraging technological advancement to develop a general model for drying food under varying initial conditions, the drying process can be significantly optimized.Materials and MethodsThis study was conducted with the aim of simulating heat and mass transfer during Refractance window drying for aloe vera gel. Comsol Multiphysics version 5.6 is a three-dimensional model used to solve heat and mass transfer equations. For this purpose, the differential equations of heat and mass transfer were solved simultaneously and interdependently. The above model considered various initial conditions: water temperature of 60, 70, 80, and 90℃, and aloe vera gel thickness of 5 and 10 mm. The initial humidity and temperature of the aloe vera is uniform. The initial temperature is 4℃ and the initial humidity of the fresh aloe vera sample is 110 gwater/gdry matter. Heat is supplied only by hot water from the bottom surface of the product.Results and DiscussionThe drying time was needed to reduce the moisture content of aloe vera gel from 110 to 0.1 gwater/gdry matter during Refractance window drying. Aloe vera gel with a thickness of 5 mm dried in 120, 100, 70, and 50 minutes at water temperatures of 60, 70, 80, and 90℃, respectively. For a 10 mm thick layer of aloe vera gel, the drying time was 240, 190, 150, and 120 minutes, for water temperatures of 60 to 90℃, respectively. These results demonstrate the importance of both the water temperature and thickness on the drying time. Furthermore, the drying rate of aloe vera gel increased as the water temperature increased from 60 to 90℃, the drying rates were 0.915, 1.099, 1.57, and 2.198 gwater/min for 5 mm thickness and 0.457, 0.578, 0.732, and 0.915 gwater/min for 10 mm thick layer of aloe vera gel, respectively.ConclusionBased on the simulation results, the optimal model is with a water temperature of 90℃ and an aloe vera gel thickness of 5 mm. Overall, the modeling results are consistent with the results of experimental data.
Bioenergy
D. Baveli Bahmaei; Y. Ajabshirchy; Sh. Abdollahpour; S. Abdanan Mehdizadeh
Abstract
This research aims to optimize the mixing process in gas-lift anaerobic digesters of municipal sewage sludge since mixing and maintaining uniform contact between methanogenic bacteria and nutrients is essential. Wastewater municipal sludge sampling was performed at the Ahvaz West treatment plant (Chonibeh, ...
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This research aims to optimize the mixing process in gas-lift anaerobic digesters of municipal sewage sludge since mixing and maintaining uniform contact between methanogenic bacteria and nutrients is essential. Wastewater municipal sludge sampling was performed at the Ahvaz West treatment plant (Chonibeh, Iran) during the summer of 2022. A Computational Fluid Dynamics (CFD) model was implemented to simulate, optimize, and confirm the simulation process using ANSYS Fluent software 19.0. The velocity of the inlet-gas into the digester was determined and a draft tube and a conical hanging baffle were added to the digester design. Different inlet-gas velocities were investigated to optimize the mixing in the digester. Furthermore, turbulence kinetic energy and other evaluation indexes related to the sludge particles such as their velocity, velocity gradient, and eddy viscosity were studied. The optimal inlet-gas velocity was determined to be 0.3 ms-1. The simulation results were validated using the Particle Image Velocimetry (PIV) method and the correlation between CFD and PIV contours was statistically sufficient (98.8% at the bottom corner of the digester’s wall). The results showed that the model used for simulating, optimizing, and verifying the simulation process is valid. It can be recommended for gas-lift anaerobic digesters with the following specifications: cylindrical tank with a height-to-diameter ratio of 1.5, draft tube-to-digester diameter ratio of 0.2, draft tube-to-fluid height ratio of 0.75, the conical hanging baffle distance from the fluid level equal to 0.125 of the fluid height, and its outer diameter-to-digester diameter of 2/3.
H. Farzanpour; S. S. Seiiedlou Heris; H. Nalbandi
Abstract
IntroductionIn livestock and specifically poultry houses, controlling the internal environment conditions is a key factor to increase animal productivity and prevent their casualties. Controlling the atmospheric conditions like the air temperature and gas concentration in semi-enclosed spaces like poultry ...
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IntroductionIn livestock and specifically poultry houses, controlling the internal environment conditions is a key factor to increase animal productivity and prevent their casualties. Controlling the atmospheric conditions like the air temperature and gas concentration in semi-enclosed spaces like poultry houses can improve the living conditions. Experimental tests on the atmospheric conditions of livestock and poultry houses are challengeable and due to limitation of measurement points, unstable climate conditions and experimental errors. Simulation of the air temperature and momentum conditions is used unlimitedly with computer resources by Computational Fluid Dynamics (CFD) methods to overcome the limitations of experimental tests. This method has vast abilities of parametric analysis and predicting the optimum range of functional parameters. So in this research, the air temperature and velocity distribution of a poultry house were simulated using CFD to achieve the best condition for the air ventilation and uniform temperature distribution. Materials and MethodsIn the present study, the geometrical model of poultry house was created using Gambit software and meshed. The mesh independence study was also performed. According to the results, 166550 elements were enough to solve the problem with an acceptable accuracy.The Reynolds-averaged Navier-Stokes (RANS) equation was selected to simulate the momentum transfer inside the poultry house. The k-ε model is one of the most used turbulence models for industrial applications. The main assumption in this model is that the flow is incompressible and that the fluid is Newtonian. A transient heat transfer equation within the fluid domain was selected to predict the air temperature that describes a time-dependent process that includes the conduction and convection terms. All the boundary condition was measured experimentally during 24 hours and their temperature was modeled using the proper mathematical models and applied to the developed model. The mathematical models were solved simultaneously in ANSYS- FLUENT software. The developed simulator was validated experimentally by measuring the air temperature of some specified locations (13 points).Results and DiscussionThe results demonstrate that the model enjoyed satisfactory accuracy so that the RMSE value between the measured and predicted air temperature was in the range of 0.405 to 1.29 and the simulator could predict the air temperature with the accuracy of 0.6 degrees. Therefore, it is possible to use the validated simulator for the real-time controlling of poultry houses to optimize the ventilation process. According to the results, the high heterogeneity in the air temperature and about an 18-degree difference was observed in the air temperature distribution at various locations of poultry houses. In addition, the air velocity was not uniform at the different plans of poultry house; especially in the central points of poultry house, it was higher than 1 m/s that is higher than the recommended value. Therefore, the simulator was used to improve the ventilation of the poultry house. The results of various simulations carried out indicated that the angle of the air inlets vents affects the air turbulence. Also, the air temperature and velocity distribution were more uniform when the air inlet vents were across each other. Therefore, some new gates were opened and the angle of the existing gates was changed to improve the ventilation condition of the poultry house. By such modification, the ventilation condition of the poultry house was improved and the air velocity and temperature distribution in the optimized house were more uniform than that observed in the primary one. The air temperature and velocity were in the range of 291 to 297 K (18 to 24 °C) and 0.23 and 0.46 m s-1, respectively. These values are at the recommended condition for poultry houses.ConclusionThe opening angle of the vents had a significant effect on the air distribution. Application of across vents in the side-walls of poultry house led to uniform distribution of air velocity and temperature. The developed simulator has good performance and accuracy to design and construct poultry houses.
