A Review of Thin Layer Drying of Foods: Theory, Modeling, and Experimental Results
Drying is a complicated process with simultaneous heat and mass transfer, and food drying is especially very complex because of the differential structure of products. In practice, a food dryer is considerably more complex than a device that merely removes moisture, and effective models are necessary for process design, optimization, energy integration, and control. Although modeling studies in food drying are important, there is no theoretical model which neither is practical nor can it unify the calculations. Therefore the experimental studies prevent their importance in drying and thin layer drying equations are important tools in mathematical modeling of food drying. They are practical and give sufficiently good results. In this study first, the theory of drying was given briefly. Next, general modeling approaches for food drying were explained. Then, commonly used or newly developed thin layer drying equations were shown, and determination of the appropriate model was explained. Afterwards, effective moisture diffusivity and activation energy calculations were expressed. Finally, experimental studies conducted in the last 10 years were reviewed, tabulated, and discussed. It is expected that this comprehensive study will be beneficial to those involved or interested in modeling, design, optimization, and analysis of food drying.
Comparison of genetic algorithm and neural network approaches for the drying process of carrot
Abstract Drying kinetic of carrot was investigated considering different drying conditions, in this study. The drying experiments were performed at four levels of drying air temperatures of 60–90 °C, together with three levels of air flow velocities of 0.5–1.5 m/s, and also three levels of thickness 0.5–1 cm. Four different mathematical models available in the literature were fitted to the experimental data. Among the considered mathematical drying models, modified Page model, was found to be more suitable for predicting drying of carrot. In order to optimize mathematical models obtained by using regression analysis, genetic algorithm was used. In all stages of the mathematical modeling, genetic algorithms were applied. In addition, a feed-forward artificial neural network was employed to estimate moisture content of carrot. Back propagation algorithm, the most common learning method for the feed-forward neural networks, was used in training and testing the network. Comparing the r (correlation coefficient), r 2 (coefficient of determination), χ 2 , and SSR (sum of squares of the difference between the experimental data and fit values) values of the four models, together with the optimized model by using genetic algorithms and the feed-forward neural network based estimator, it was concluded that neural network represented drying characteristics better than the others.
Evaluation of buckling load and dynamic performance of steel shear wall retrofitted with strips made of shape memory alloy
One of the most imperfections of the steel shear wall is out of plane displacements that cause severe damage in both structural and non-structural elements. In this paper, the effects of shape-memory alloys on steel shear walls are investigated. First, a numerical analysis using the finite element method in ABAQUS software has been carried out according to an experimental test. The results of the numerical analysis have been verified with experimental results. Next, shape-memory alloy fibers have been added vertically and horizontally to various parts of the steel shear wall. The results show that retrofitting with the shape-memory alloy reduces the out-of-plane displacement of the steel shear wall under both cyclic and seismic loadings. Besides, the buckling load in the steel shear wall increases when it is retrofitted with the shape-memory alloy. Also, the total out-of-plane movement (accumulated absolute displacements) of the steel shear wall and non-structural damage are controlled by the characteristic of a shape-memory alloy material called “super-elastic”.