توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Comparison of Artificial Neural Network and Bayesian Belief Network for Prediction of Drying Time in a Fluidized Bed Dryer
نویسنده(ها): ، ،
اطلاعات انتشار: چهاردهمین کنگره ملی مهندسی شیمی ایران، سال
تعداد صفحات: ۴
In this study the process of drying of peas in a batch fluidized bed dryer was simulated. Two different methods were used to fit the experimental data. Artificial neural network (ANN) andBayesian belief network (BBN) were used for predicting the time that is required to reach to a certain moisture of the particles in the dryer. Comparing \ r \Correction Factor and \ \factor anderrors like MRE, MAE, SE in the two models shows that the predictions of artificial neural network is better than Bayesian belief network<\div>

۲Effect of Shrinkage on the Effective Diffusivities of Water andSucrose during Osmotic Dehydration of apple cylinders
نویسنده(ها): ، ،
اطلاعات انتشار: چهاردهمین کنگره ملی مهندسی شیمی ایران، سال
تعداد صفحات: ۵
The water and sucrose effective diffusion coefficients were estimated in apple cylinders during osmotic dehydration in sucrose solution at three different concentrations of 30, 40 and 50% andtemperatures of 30, 40 and 50°C .The solution to sample mass ratio was more than 20:1 (w\w) andthe process duration varied from 0 to 6 hr. A mathematical model developed by Azuara was used for describing the mass transfer in osmotic dehydration of apple cylinders. The effect of changes in the volume of apple cylinders during osmotic dehydration on the kinetics of moisture diffusion were studied. The experimental drying curves were adjusted to the diffusional model of Fick’s law for infinite cylinder with and without consideration of shrinkage to measure water and sucroseeffective diffusivities.The effective diffusivities without shrinkage ranged from 1.59 ×10–10 m2\s to 2.49 ×10–10 m2\s and with considering shrinkage varied from 1.41 ×10–10 m2\s to 2.28 ×10–10 m2\s. The values of effective diffusivity obtained by considering the samples shrinkage were smaller than those calculated without considering shrinkage<\div>

۳Prediction of equilibrium water loss during osmotic dehydration in green bean using artificial neural network
نویسنده(ها): ، ، ،
اطلاعات انتشار: هفتمین کنگره ملی مهندسی شیمی، سال
تعداد صفحات: ۸
In this paper, estimation equilibrium water loss of green bean in osmotic dehydration using artificial neural network has been presented. Processing factors were solute concentrations and process temperatures. Feed forward neural network with Levenberg–Marquardt training algorithm was used to calculate the output values of the neurons of the hidden layer. According to the network's training, validation and testing results, a two layer neural network with eight neurons in the hidden layer is selected as the best architecture for accurate prediction of the water loss. The acceptable agreement between the results of ANN model and experimental data demonstrates the capability of the neural network technique for estimating equilibrium water loss during osmotic dehydration<\div>

۴Mathematical Modelling of a Batch Fluidized Bed Dryer Using a Distributed Mass Transfer and a Lumped Heat Transfer Model
نویسنده(ها): ،
اطلاعات انتشار: هفتمین کنگره ملی مهندسی شیمی، سال
تعداد صفحات: ۸
In this article, heat and mass transfer phenomena in a batch fluidized–bed dryer were investigated using a distributed mass transfer and a lumped heat transfer model. A pilot scale fluidized bed dryer was set up for experimental investigation and grean peas particles were used as spherical drying materials. Model equations have been solved by the finite difference numerical method and using MATLAB software. The results, obtained from the mathematical model were compared with experimental data. Good agreement is achieved between model predictions and experimental data.<\div>
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