Computational Fluid Dynamics (CFD) Analyses of Energy and Exergy in Thin Layer Drying of Okra (Abelmoschus esculentus) Slices using Centre Shaft Rotary Tray Cabinet (CSRTC) Dryer

This paper presents a simulation of the drying process of okra (Abelmoschus esculentus) in a Center Shaft (CS) Rotary Tray Cabinet Dryer using three drying temperatures (50, 60 and 70 °C). ANSYS 14.5 Workbench was used to simulate the dryer model in 2D (2 Dimensional). The detail of the CFD simulation was utilized to investigate the energy and exergy of the dryer. The ANSYS Design Modeler was used to model the 2D representation of the dryer and the meshing was done using ANSYS ICEM. ANSYS Fluent CFD solver was then used to calculate the alternative using the normal turbulence-realizable k-epsilon model in a steady-state system with improved wall temperature treatment. The simulation outcome was used in calculating the dryer's exergy and energy analysis based on the thermal efficiency. It was noted that the simulated temperature from the experiment is greater than that of the experiment. The results indicated that the experimental energy utilization (EU), energy utilization ratio (EUR) and energy efficiency increased from 14.1 to 57.93 J/s, 0.15 to 0.20 and 18.89 to 33.98 percent, while the simulated energy utilization ratio increased from 23.91 to 57.68 J/s, 0.19 to 0.20 and 26.21 to 33.40 percent, respectively, and as the drying air temperature increased from 50 °C to 70 °C. Experimental exergy inflow, outflow, exergy loss and exergy efficiency increased from 4.01 J/s to 6.98 J/s, 1.83 J/s to 1.9 J/s, 3.18 J/s to 5.07 J/s and 21 to 27%, while simulated air temperatures increased from 5.01 J/s to 7.49 J/s, 1.33 J/s to 2.20 J/s, 3.66 J/s to 5.29 J/s and 27 to 29% respectively with respect to the drying air temperature range (50–70 °C). Model equations were derived from the plotted graphs to express the energy and exergy parameters as a function of drying temperature

Application of Image Analysis in Food Grain Quality Inspection and Evaluation During Bulk Storage

With increased expectations for high quality food products and safety standards, the need for accurate, fast and objective quality determination of moisture, purity, germination and pathogen free food products and grains during bulk storage continues to grow. This paper reviews the application of image analysis in food grain quality inspection and discusses the potential of the technology for application in grain quality monitoring and evaluation during bulk storage. Image analysis procedure and physical properties of the grain bulk were also discussed. Image analysis is an automated alternative to manual inspection with less processing time and more accurate results. Human inspection has been found wanting due the bias judgment and results. Image analysis of food grains during bulk storage can only get better with its diverse applications in varietal identification, distinctness, uniformity and stability (DUS) testing, detection of insects and foreign bodies within the grain bulk and the detection of hot spot in the bin to mention a few. In Nigeria, image analysis will be a great tool in terms of grain quality preservation in National Grain Reserves (NGRs), providing seeds for farmers for the next planting season and reviving the grain reserves in Nigeria to boost gainful employment of citizens. An automated grain reserves using image analysis is possible in Nigeria only if appropriate government policies and funding can throw its full weight behind the innovation. &nbsp