Computational Fluid Dynamics Modeling and Predicting Environmental Conditions in a Poultry Incubator

Abstract Environmental conditions of a poultry incubator impact chick embryo development and pathogen survivability and spread. The current practices of monitoring and control based on limited sensor locations inside an incubator give incomplete knowledge of the overall spatiotemporal distributions of important environmental factors such as temperature, humidity, and carbon dioxide. To better understand the environmental conditions inside an incubator, a computational fluid dynamics (CFD) model was developed to predict air ventilation patterns and scalar transport in a small-scale commercial incubator with two egg racks (1620 eggs total) over 18-day incubation period. Various modeling approaches were investigated to identify cost-effective numerical models for long duration simulations. The CFD model was validated using experimental datasets procured at four interior locations measuring velocity, temperature, humidity, and CO2. The CFD model compared within 12% of the experimental data for velocity, temperature, and CO2 accumulation predictions, but showed higher 37% error for relative humidity (RH). The limitation in temperature predictions was attributed to challenges in modeling heat generation by the eggs. The large errors for relative humidity were attributed to the negligence of intermittent water spray. Overall, this study demonstrates the potential of CFD in accurately predicting complex biological spatiotemporal gradients of relevant environmental factors in a poultry incubator.