Abstract
An environmental prediction model was developed for optimal ventilation in a mushroom house utilising a sensible heat balance and a three-dimensional (3-D) computational fluid dynamics (CFD) model. The respiration of the mushrooms and the use of a low-capacity cooler were considered. A mushroom-house-specific ventilation equation was developed to calculate the ventilation rate for a given environmental condition. Calculated ventilation rates were compared with the experimentally measured data for the indoor temperature set to the optimum for growing mushrooms (16.2 °C) with varying outdoor temperature. There was good agreement between the measured and predicted rates (0.2-5.1% error). Calculated ventilation rates (from the sensible heat balance) were used as an input parameter for 3-D CFD model, eliminating the need for experimental measurement of ventilation rate. 3-D CFD simulations were conducted using the same environmental condition to establish the local heat distribution in a mushroom house. The simulation results for temperature were compared with the experimental data at several different locations in a mushroom house and showed negligible errors. The CFD model was also used to improve heat distribution of a mushroom house. It was predicted that enhanced cooling and more uniform temperature distribution could be achieved just by changing the direction of airflow from air inlet ducts and/or installing small fans onto them, but not by changing the directions of airflow from a cooler. This would be a more economical than replacing a cooler or redesigning the entire structure. The model could be used to predict the environmental conditions over different locations in a mushroom house without the need for experimentally determining the ventilation rate.
Original language | English (US) |
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Pages (from-to) | 417-424 |
Number of pages | 8 |
Journal | Biosystems Engineering |
Volume | 104 |
Issue number | 3 |
DOIs | |
State | Published - Nov 2009 |
ASJC Scopus subject areas
- Food Science
- Agronomy and Crop Science
- Control and Systems Engineering
- Soil Science