Application and Comparison of Two Mathematical Models for Simulating Grain Heat and Mass Transfer During In-Bin Drying

Liu, Jingyun; Zhou, Huiling; Xiao-guang, Zhou

doi:10.4156/jdcta.vol6.issue6.24

Cited by 5 publications

(1 citation statement)

References 28 publications

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“…Several studies, has been concentrated on the drying of grain considered as a single porous particle and thin layers [58][59][60] of foods like vegetables and fruits [61]. Different mathematical models were developed to predict heat and mass transfer within the granular bed dryers without taking into account the shrinkage phenomenon [62][63][64].…”

Section: Introductionmentioning

confidence: 99%

Significance of Bed Shrinkage on Heat and Mass Transfer During the Transport Phenomenon of Humid Air

et al. 2021

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Simultaneous heat and mass transfer inside a packed bed dryer between a fluid phase and corn kernels was studied. A developed two-phase model for evaluating the effect of bed shrinkage and non-constant physical properties on the drying efficiency was conducted. Experimental data were utilized to develop the governing equations of the bed shrinkage and structural parameters with moisture content inside the packed bed dryer. The developed model was verified by assessing predictions against experimentally obtained moisture content and temperature along the drying bed, as the standard errors of the experimental values compared to the model were found to be close to the accepted engineering accuracy of 5%. It has been concluded that the incorporation of bed shrinkage and alteration in properties within the operating model is capable of providing a more comprehensive and precise analysis of heat and mass transfer phenomenon in porous media drying, such as corn kernels.

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Section: Introductionmentioning

confidence: 99%

Significance of Bed Shrinkage on Heat and Mass Transfer During the Transport Phenomenon of Humid Air

et al. 2021

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An experimentally validated model for a multivariate drying industrial process

Yahya,

Lassoued,

Aboud

et al. 2024

Transactions of the Institute of Measurement and Control

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Modeling of industrial production processes is becoming increasingly challenging due to their large number of variables. These variables often are highly correlated and introduce nonlinear and complex features. In this paper, we are interested to model an industrial dicalcium phosphate (DCP) drying process. Attempting to solve this issue is motivated by the need to improve several production conditions, such as minimizing the consumption of natural gas and reducing the pollution rate. In fact, applying an advanced control approach requires a dynamic model for the monitored plant. This work proposes a multivariable mathematical model for the DCP dryer within the Tunisian Chemical Group factory. A steady-state model has been reproduced using Aspen Plus software tool to implement the different functionalities of the system as well as involved reactions. Indeed, since the main operation in the drying process is the combustion reaction of the liquified petroleum gas (LPG) in the furnace that produce the necessary heat to reach a target value of temperature at the dryer outlet, we focus on determining a dynamic model for the furnace. To do so, we have proposed two approaches. The first is based on the Aspen dynamic tool. The second is based on the left matrix fraction description (LMFD) identification approach. The obtained results have been successfully validated using real measurements.

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Control and Real-Time Data Acquisition of an Experimental Platform for Stored Grain Aeration Study

Liu

2021

Sensors

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Aeration is one of the most important methods to keep stored grain safe and maintain its quality. Experimental platforms are used for stored grain aeration study in a laboratory-scale. The purpose of this paper was to provide the real-time data acquisition and control system design of a new experimental platform with multifunction for stored grain study. Requirements of the aeration experiments were analyzed, and multi running modes were designed. The aeration inlet air conditions were designed to be adjustable and multi variables need to be controlled simultaneously, which was a key problem to be solved for the platform. An ON/OFF-PID based multivariable cooperative control method was proposed, and two control loops were formed where inlet air temperature and humidity were considered separately while could be controlled simultaneously with a logic judgement strategy. Real-time data needed to be monitored was acquired with different sensors and displayed intuitively. Experiments were carried out to test the static and dynamic characteristics of the control method and three inlet air flow rates of 0.03, 0.08 and 0.13 m·s−1were used. Performance of the data acquisition system was also tested. The results showed that, the inlet air conditions control error was within ±1 °C and 10% for temperature and relative humidity, respectively. The real-time data acquisition of multi parameters during aeration process was realized. The experimental platform can be used for studies of different aeration objectives.

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Application and Comparison of Two Mathematical Models for Simulating Grain Heat and Mass Transfer During In-Bin Drying

Cited by 5 publications

References 28 publications

Significance of Bed Shrinkage on Heat and Mass Transfer During the Transport Phenomenon of Humid Air

Significance of Bed Shrinkage on Heat and Mass Transfer During the Transport Phenomenon of Humid Air

An experimentally validated model for a multivariate drying industrial process

Control and Real-Time Data Acquisition of an Experimental Platform for Stored Grain Aeration Study

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