Modeling deep-bed grain drying using Comsol Multiphysics

CFD simulations were carried out to predict the convective heat and mass transfer coefficients in the rice bed, and correlations were developed for the convective heat and mass transfer coefficients as a function of drying air flow rate. The developed correlations were used to extend the coupled CFD and diffusion model developed by ElGamal et al. (2013) for thinlayer rice drying to volumetric heat and mass transfer in a deep-bed of rice. All mathematical models were solved using the Comsol Multiphysics® simulation program v4.3 (Comsol Inc, Palo Alto), which uses the finite element method to solve the model equations. The model was used to predict the air temperature, as well as the grain moisture content and temperature at different locations of the dryer during the drying process. The theoretical predictions of moisture and temperature profiles inside a deep-bed of rice were verified by experimental data from literature

Multi-scale model for heat and mass transfer during rice drying

Grain drying is a simultaneous heat and moisture transfer problem. The modeling of such a problem is of significance in understanding and controlling the drying process. The main goal of this study was to predict the heat and mass transfer processes during deep-bed rice drying. To achieve this, first, CFD simulations were carried out to analyze the external flow and temperature fields at steady-state for a control volume of a stationary rice bed. The model was used to predict the convective heat and mass transfer coefficients in the rice bed, and correlations were developed for the convective heat and mass transfer coefficients as a function of drying air flow rate. Then, the coupled CFD and diffusion model developed by ElGamal, Ronsse, Radwan & Pieters (2013) to investigate the heat and mass transfer for thin-layer drying of rice was extended to volumetric heat and mass transfer in a deep-bed of rice using the predicted heat and mass transfer coefficients. All models were solved numerically using the finite element method. The model was used to predict the air temperature, as well as the grain moisture content and temperature at different locations of the dryer during the drying process. The theoretical predictions of moisture and temperature profiles inside a deep-bed of rice were verified by experimental data from literature. The average mean relative deviation values for the prediction of grain moisture content varied between 1.00 to 3.13%

A global coating quality model for top-spray fluidized beds: spray sub model

Fluidized beds are amongst others used in industrial applications for coating particles. Little research has been performed in developing a quality model for a coating process. A quality model is able to predict the quality of the process in terms of coating thickness and uniformity and the occurrence of unwanted side-effects, including agglomeration, attrition and spray loss. The quality of the coating process in a fluidized bed is largely determined by the spray characteristics and the particle motion. A new quality model was developed for the coating process in a top-spray fluidized bed. The first step in the development of the new model was the creation of an accurate spray sub-model that describes the movement and the heat and mass balances of the droplets in the coating process. The second step was the creation of a particle sub-model that describes the movement and the heat and mass balances of the particles in the fluidized bed. The third and final step will be the development of the global coating quality model by combining the spray and the particle sub model. Experimental validation of the spray sub-model has already been carried out and is presented in this paper

3D Simulation with virtual stereo rig for optimizing centrifugal fertilizer spreading

Stereovision can be used to characterize of the fertilizer centrifugal spreading process and to control the spreading fertilizer distribution pattern on the ground reference. Fertilizer grains, however, resemble each other and the grain images contain little information on texture. Therefore, the accuracy of stereo matching algorithms in literature cannot be used as a reference for stereo images of fertilizer grains. In order to evaluate stereo matching algorithms applied to images of grains a generator of synthetic stereo particle images is presented in this paper. The particle stereo image generator consists of two main parts: the particle 3D position generator and the virtual stereo rig. The particle 3D position generator uses a simple ballistic flight model and the disc characteristics to simulate the ejection and the displacement of grains. The virtual stereo rig simUlates the stereo acquisition system and generates stereo images, a disparity map and an occlusion map. The results are satisfying and present an accurate reference to evaluate stereo particles matching algorithms

Hyperspectral classification of Cyperus esculentus clones and morphologically similar weeds

Cyperus esculentus (yellow nutsedge) is one of the world's worst weeds as it can cause great damage to crops and crop production. To eradicate C. esculentus, early detection is key-a challenging task as it is often confused with other Cyperaceae and displays wide genetic variability. In this study, the objective was to classify C. esculentus clones and morphologically similar weeds. Hyperspectral reflectance between 500 and 800 nm was tested as a measure to discriminate between (I) C. esculentus and morphologically similar Cyperaceae weeds, and between (II) different clonal populations of C. esculentus using three classification models: random forest (RF), regularized logistic regression (RLR) and partial least squares-discriminant analysis (PLS-DA). RLR performed better than RF and PLS-DA, and was able to adequately classify the samples. The possibility of creating an affordable multispectral sensing tool, for precise in-field recognition of C. esculentus plants based on fewer spectral bands, was tested. Results of this study were compared against simulated results from a commercially available multispectral camera with four spectral bands. The model created with customized bands performed almost equally well as the original PLS-DA or RLR model, and much better than the model describing multispectral image data from a commercially available camera. These results open up the opportunity to develop a dedicated robust tool for C. esculentus recognition based on four spectral bands and an appropriate classification model

Technical and economic feasibility of gradual concentric chambers reactor for sewage treatment in developing countries

A major challenge in developing countries concerning domestic wastewaters is to decrease their treatment costs. In the present study, a new cost-effective reactor called gradual concentric chambers (GCC) was designed and evaluated at lab-scale. The effluent quality of the GCC reactor was compared with that of an upflow anaerobic sludge bed (UASB) reactor. Both reactors showed organic matter removal efficiencies of 90%; however, the elimination of nitrogen was higher in the GCC reactor. The amount of biogas recovered in the GCC and the UASB systems was 50% and 75% of the theoretical amount expected, respectively, and both reactors showed a slightly higher methane production when the feed was supplemented with an additive based on vitamins and minerals. Overall, the economical analysis, the simplicity of design and the performance results revealed that the GCC technology can be of particular interest for sewage treatment in developing countries