Simulation of Grain Quantity, Fan and Solar Collector Sizes for an Experimental Forced Convection Grain Dryer

Osodo, Booker; Nyaanga, D. M.; Kiplagat, J.K.

doi:10.20448/journal.512.2019.61.98.108

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…Overall, post-harvest losses in sub-Saharan Africa are estimated to be between 40% and 80% [ 67 , 68 , 69 ]. Mycotoxin post-harvest control stages are a challenge, and this is one of the main reasons why mycotoxin occurrence is high in Africa, due to lack of infrastructure for adequate drying and proper storage.…”

Section: Factors Responsible For High Levels Of Mycotoxin Contaminati...mentioning

confidence: 99%

Six Main Contributing Factors to High Levels of Mycotoxin Contamination in African Foods

Ngum

Babalola

Ekwomadu

et al. 2022

Toxins

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Africa is one of the regions with high mycotoxin contamination of foods and continues to record high incidences of liver cancers globally. The agricultural sector of most African countries depends largely on climate variables for crop production. Production of mycotoxins is climate-sensitive. Most stakeholders in the food production chain in Africa are not aware of the health and economic effects of consuming contaminated foods. The aim of this review is to evaluate the main factors and their degree of contribution to the high levels of mycotoxins in African foods. Thus, knowledge of the contributions of different factors responsible for high levels of these toxins will be a good starting point for the effective mitigation of mycotoxins in Africa. Google Scholar was used to conduct a systemic search. Six factors were found to be linked to high levels of mycotoxins in African foods, in varying degrees. Climate change remains the main driving factor in the production of mycotoxins. The other factors are partly man-made and can be manipulated to become a more profitable or less climate-sensitive response. Awareness of the existence of these mycotoxins and their economic as well as health consequences remains paramount. The degree of management of these factors regarding mycotoxins varies from one region of the world to another.

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Section: Factors Responsible For High Levels Of Mycotoxin Contaminati...mentioning

confidence: 99%

Six Main Contributing Factors to High Levels of Mycotoxin Contamination in African Foods

Ngum

Babalola

Ekwomadu

et al. 2022

Toxins

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“…Using regression analysis, a correlation was created between moisture ratio, drying time, drying temperature, and air velocity using Minitab version.17 [33,34]. (Fig.…”

Section: Moisture Ratio Processing By Ann Predictive Modelingmentioning

confidence: 99%

Artificial neural network modeling for drying kinetics of paddy using a cabinet tray dryer

Subramanyam

Narayanan

2023

CI&CEQ

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The study of drying kinetics and characteristics of agricultural products is essential for drying time estimation, designing dryers, and optimizing the drying process. Moisture diffusivity under different drying conditions is crucial to process and equipment design. The drying kinetics of paddy using a cabinet tray dryer was modeled using an Artificial Neural Network (ANN) technique. For predicting moisture ratio and drying rate, the Levenberg-Marquardt (L.M.) training algorithm with TANSIGMOID and TANSIGMOID hidden layer activation function provided superior results. A comparative evaluation of the predicting abilities of ANN and 12 different mathematical drying models was also carried out. The Midilli model was found to be adequate for fitting the experimental data with an R2 comparable to that of the ANN. However, the RMSE observed for ANN (0.0360) was significantly lower than that of the midilli model (0.1673 to 0.712). Effective moisture diffusivity increased with an increase in temperature from 15.05 to 28.5 x 10-9 m2/s. The activation energy for drying paddy grains varied between 6.8 to 7.3 kJ/mol, which showed a moderate energy requirement for moisture diffusion.

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“…The chosen range of velocities allows for a comprehensive analysis of the system's response to airflow. Lower velocities (0.1 m/s) represent typical airflow rates under natural convection conditions, while higher velocities (1.0 and 1.5 m/s) simulate scenarios with forced convection, such as when the cavity is subjected to forced air cooling or ventilation [40][41][42].…”

Section: Introductionmentioning

confidence: 99%

Heat Convection in a Channel-Opened Cavity with Two Heated Sources and Baffle

Rashid,

Al-Gaheeshi,

Mohammed

et al. 2024

Energies

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This study employs COMSOL software v 5.6 to investigate a novel approach to heat transfer via mixed convection in an open hollow structure with an unheated 90° baffle elbow. Two 20 W heat sources are strategically positioned on the cavity’s bottom and right-angled wall for this research. Notably, the orientation of the baffle perpendicular to the airflow is used to direct external, unrestricted flow into the square cavity. The research investigates a range of air velocities (0.1, 0.5, 1.0, and 1.5 m/s) and the intricate interaction between input air velocity, dual heated sources, and the presence of a right-angle baffle on critical thermodynamic variables, such as temperature distribution, isotherms, pressure variation, velocity profile, air density, and both local and mean Nusselt numbers. Validation of the applicable computational method is achieved by comparing it to two previous studies. Significant findings from numerical simulations indicate that the highest velocity profile is in the centre of the channel (2.3–2.68 m/s at an inflow velocity of 1.5 m/s), while the lowest profile is observed along the channel wall, with a notable disruption near the inlet caused by increased shear forces. The cavity neck temperature ranges from 380 to 640 K, with inflow air velocities varying from 0.1 to 1.5 m/s (Re is 812 to 12,182), respectively. In addition, the pressure fluctuates at the channel-cavity junction, decreasing steadily along the channel length and reaching a maximum at the intake, where the cavity neck pressure varies from 0.01 to 2.5 Pa with inflow air velocities changing from 0.1 to 1.5 m/s, respectively. The mean Nusselt number exhibits an upward trend as air velocity upon entry increases. The mean Nusselt number reaches up to 1500 when the entry air velocity reaches 1.5 m/s. Due to recirculation patterns, the presence of the 90° unheated baffle produces a remarkable cooling effect. The study establishes a direct correlation between input air velocity and internal temperature distribution, indicating that as air velocity increases, heat dissipation improves. This research advances our understanding of convective heat transfer phenomena in complex geometries and provides insights for optimising thermal management strategies for a variety of engineering applications.

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Simulation of Grain Quantity, Fan and Solar Collector Sizes for an Experimental Forced Convection Grain Dryer

Cited by 5 publications

References 10 publications

Six Main Contributing Factors to High Levels of Mycotoxin Contamination in African Foods

Six Main Contributing Factors to High Levels of Mycotoxin Contamination in African Foods

Artificial neural network modeling for drying kinetics of paddy using a cabinet tray dryer

Heat Convection in a Channel-Opened Cavity with Two Heated Sources and Baffle

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