Skip to main content
ARS Home » Southeast Area » Mississippi State, Mississippi » Poultry Research » Research » Publications at this Location » Publication #426384
Research Project: Intervention Strategies to Mitigate Avian Escherichia coli Infections and Antimicrobial Resistance in the Poultry Environment

Location: Poultry Research

Title: Computational fluid dynamics modeling and predicting environmental conditions in a poultry incubator

Author
item FERNANDES, MELVY - Mississippi State University
item BURGREEN, GREG - Mississippi State University
item DREWRY, JESSICA - Mississippi State University
item Purswell, Joseph
item BHUSHAN, SHANTI - Mississippi State University

Submitted to: Journal of Fluids Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/12/2025
Publication Date: 1/8/2026
Citation: Fernandes, M., Burgreen, G., Drewry, J., Purswell, J.L., Bhushan, S. 2026. Computational fluid dynamics modeling and predicting environmental conditions in a poultry incubator. Journal of Fluids Engineering. 148: 4. https://doi.org/10.1115/1.4070566.
DOI: https://doi.org/10.1115/1.4070566

Interpretive Summary: Environmental conditions that affect hatching success and disease transmission are poorly understood in commercial hatcheries. Uneven distributions of temperature, humidity, and other air quality measures may affect hatching and promote spread of disease from one chick to another. The goal of this analysis was to use advanced numerical modeling techniques such as computational fluid dynamics to estimate and visualize airflow patterns within incubators to better understand internal conditions which may promote spread of disease. The model was successfully validated and illustrates this experimental approach can accurately predict airflow and heat transfer within a poultry incubator for use in predictive analyses.

Technical Abstract: Environmental conditions of a poultry incubator impact chick embryo development. The current practices of monitoring and control based on limited sensor locations inside an incubator gives incomplete knowledge of the overall spatiotemporal distributions of important environmental factors such as temperature, humidity, and carbon dioxide. Detailed knowledge of these factors can potentially provide insights into reducing pathogen spread. To better understand the environmental conditions inside an incubator, we have developed a computational fluid dynamics (CFD) model to predict air ventilation patterns and scalar transport in a laboratory-scale incubator with two egg racks (1620 eggs total) over an incubation period of 18 days. Various modeling approaches were investigated to identify a cost-effective numerical model to efficiently perform long time duration simulations that generate reliable environmental data distributions. The CFD model was validated using experimental sensors at four interior locations measuring temperature, humidity, and CO2 and showed reasonable agreement. This research demonstrates the potential of CFD to accurately predict complex biological spatiotemporal gradients of relevant environmental factors in a poultry incubator.