A Study on the Performance of the Convective Heat Transfer of Hybrid Smart Mushroom Cultivation Equipment

Abstract

The hybrid smart mushroom cultivation equipment’s internal fluid was assumed to be air. Four each FCUs and FANs were assumed to be on the left and on the right and one each FCU and FAN were assumed to be on the front for forced flows. Four cases where the FCUs and FANs were installed high or low were analyzed. To analyze the smart farm at room temperature, the internal initial temperature was set to 10 ℃ and it was assumed that air at 15 ℃ would flow in through the FCUs at 0.5 m/s and flow out through the FANs. In addition, the internal temperature of smart mushroom growing facility was assumed to be optimal when it is constant in a range of 12~18 ℃ and the panels were assumed to be insulated. Analyses were conducted for four seasons too. By stably realizing consistent environmental management, smart mushroom cultivation equipment optimum conditions not only save the effort for ventilation repeated everyday but also enable the management of ventilation at the optimum thereby enabling high quality production. The present study is intended to examine sandwich insulation panel type smart farm systems through flow analyses. The positions of FCUs and FANs that are in charge of air inflows/outflows were adjusted to smoothen the air flows between the multiple array mushroom beds in four lines of seven layers and prevent environmental differences between upper and lower mushroom beds. The standard deviation of the smart mushroom growing facility where FCUs and FANs were positioned low was the smallest amounting to 0.298. Therefore, this smart mushroom cultivation was judged to be the optimum model because the temperatures around the shelves inside the smart mushroom cultivation equipment became the most evenly distributed. Select 635 points around the shelf in the inside where flows occur to determine temperature results and check the mean and standard deviation. The standard deviation refers to the average value of the differences (deviations) between all values from the mean. The larger the standard deviation is, the more the value deviates from the mean. Therefore, the standard deviation represents the degree of scattering of the observed values. Therefore, the smaller the standard deviations of the model, the more uniform the temperature distribution