Deep-bed Grain Research Articles

Inverse estimation of thermophysical properties and initial moisture content of cereal grains during deep-bed grain drying

This paper proposes and demonstrates the use of inverse methods to estimate grain properties during deep-bed drying. An inverse analysis was performed to estimate the bulk density, specific heat and initial moisture content of cereal grains, using only grain temperature measurements as inputs. Grain temperature data obtained from numerically solving the direct problem were used to generate the temperature measurements. An iterative procedure, based on minimizing a sum of squares function with the conjugate gradient method and the discrepancy principle, was used to solve the inverse problem. A statistical analysis was performed to evaluate the accuracy of the estimated results. The effects of measurement errors and the sensor location on the inverse solution were also investigated. The close agreement between the exact and the estimated results shows the capability of the proposed method in estimating unknown parameters.

Investigation on rough rice drying kinetics at various thin layers of a deep bed

Moisture content gradients along the bed column are commonly neglected during simulation of deep-bed grain drying. In this study, rough rice drying kinetics at various thin layers of a deep bed was investigated. The experiments were conducted under different drying conditions and the data were compared with the values predicted by a previously developed non-equilibrium model for numerical simulation of grain drying. The moisture content gradients related to the rough rice column indicated that the higher the drying layer, the more was the moisture content at each drying time. The constant drying rate period was observed neither for any thin layers nor for the entire drying column. The drying rate of the lower layers continuously decreased with drying time, whereas that of the upper layers firstly increased and then decreased. The implemented model predicted drying process with a high accuracy at various layers. However, the values of maximum relative error (RE max ) and mean relative error (MRE) increased as the air temperature increased, and reversely decreased with the air velocity. The higher values of MRE and RE max were related to the layer 1 (0–5 cm bed height) at temperature of 60 °C and air velocity of 0.4 m s−1, and the lower values belonged to the layer 4 (15–20 cm bed height) at temperature of 40 °C and air velocity of 0.9 m s−1.

Modelling and Simulation of Momentum, Heat, and Mass Transfer in a Deep-Bed Grain Dryer

This article concerns the modelling and simulation of a deep-bed grain dryer in a large diameter-column. Two-dimensional (2D) models of deep-bed grain dryers were built by considering simultaneously momentum, heat, and mass transfer in the drying phase together with coupled heat and mass balance in the grain phase. The dynamic equations are solved numerically by using finite difference method. The momentum equations are applied to simulate pressure drop and velocity field of the drying air across the bed. The mass and heat balance in the two phases determine the profile of temperature and moisture content in both phases. Further, drying rate curves for various temperature of inlet drying gas together with moisture content of grain were simulated. The simulated profiles are in close agreement with experimental data.

A COMPREHENSIVE MATHEMATICAL AND NUMERICAL MODELING OF DEEP-BED GRAIN DRYING

ABSTRACT This paper deals with comprehensive mathematical and numerical modeling of deep-bed grain drying. In order to build the process model, it is necessary to analyze the transport in both grain and gas phases. Experimental works were carried out for a layer of grain bed in order to validate the models. The models consider momentum, energy, and mass conservation within grain and drying air phase. The two-dimensional dynamic equations of energy and mass conservation are solved numerically by finite-difference method (FDM) and utilizing alternating direction implicit algorithm within grain and drying air phase, while momentum conservation are solved by finite difference method by utilizing Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) algorithm. Furthermore, the models will be applied in consideration with developing and designing dryer in order to simulate humidity and temperature profiles of the drying gas together with moisture content and temperature of grain across dryer in term of the dryer performance. The simulations show that the models can be used to predict the dynamic drying characteristic profiles as well as the superficial velocity of drying air phase across dryer.

Estimation of the Latent Heat of Adsorption and Rewetting During Deep Bed Grain Cooling

Estimation of the Latent Heat of Adsorption and Rewetting During Deep Bed Grain Cooling

MODELING AND SIMULATION OF DEEP-BED GRAIN DRYERS

This paper concerns with heterogeneous modeling of deep-bed grain dryers based on two-phase model by taking into account coupled heat and mass transfer within grains. This model also consider axial mass and heat dispersion in the fluid phase. The dynamic two-phase equations are solved numerically by finite difference with alternating direction implicit method algorithm, and then applied to simulate humidity and temperature profile of drying gas across dryers together with moisture content and temperature of grains. The capabilities of these models were compared with experimental data obtained from available literatures, under drying conditions such as temperature and absolute humidity of drying gas and moisture content of grains. The simulation results show that the dynamic of corn drying within the bed is well predicted by the two-phase model.

Effect of thermal storage on the performance of a deep bed drying system

SYNOPSIS The effect of thermal energy storage on deep bed grain drying is studied. The rate of evaporation of moisture and humidity of drying air are analysed with time of the day for different depths of bed, heat capacity of storage material and flow rate. The effect of thermal storage is also studied on the fluid temperature, grain temperature and on the overall performance of the system. A parametric study has been done for a typical day of the month of June for climatic conditions in Delhi. It has been observed that the bed moisture content decreases with time of day unlike the humidity of the drying air and grain temperature also decreases with heat capacity.

Deep-Bed Grain Drying - A Review of Particular Theories

ABSTRACT Theories developed for explaining the drying phenomena in grain drying systems are referred to as particular grain drying theories. The objectives of this paper are to review various particular grain drying theories and to suggest directions for future research in this area. Grain drying models are classified as non-equilibrium, equilibrium, and logarithmic type. Four non-equilibrium models (stationary bed, cross-, concurrent-, and counter-flow) were reviewed. Under low temperature and low airflow conditions, drying in a stationary deep-bed occurs at near equilibrium. The derivation of an equilibrium grain drying model and its necessary assumptions were discussed. Logarithmic models were developed and applied by many researches mostly to low temperature drying in stationary deep-beds. A semi-empirical thin-layer equation is commonly used in the reported grain drying models. The inclusion of this equation is an important factor, that determines the cognitive and practical values of a grain drying ...

A mathematical model for A deep-bed grain drying system

A mathematical model is presented for deep-bed drying of grains which gives explicit expressions for the temperature and moisture contents of the grain, and the temperature changes of the drying air as functions of time and bed thickness. The model is based on heat and masss transfer relationships proposed by Brooker et al. (1978). The results of the numerical computation carried out using this model are in close agreement with the experimental results of Boyce (1965); the results are also compared with the theoretical results of O'Callaghan et al., (1971). The model is also applicable to situations when the inlet air parameters are functions of time.

Application of the Logarithmic Model to Cross-Flow Deep-Bed Grain Drying

Application of the Logarithmic Model to Cross-Flow Deep-Bed Grain Drying