A study on computational fluid dynamics modeling of a refrigerated container for COVID-19 vaccine distribution with experimental validation()

A key issue with the distribution of vaccines to prevent COVID-19 is the temperature level required during transport, storage, and distribution. Typical refrigerated transport containers can provide a temperature-controlled environment down to −30 °C. However, the Pfizer vaccine must be carefully transported and stored under a lower temperature between −80 °C and − 60 °C. One way to provide the required temperature is to pack the vaccine vials into small packages containing dry ice. Dry ice sublimates from a solid to a gas, which limits the allowable transport duration. This can be mitigated by transporting in a − 30 °C refrigerated container. Moreover, because the dry ice will sublimate and thereby release CO(2) gas into the transport container, monitoring the CO(2) concentration within the refrigerated container is also essential. In the present work, a 3D computational fluid dynamics model was developed based on a commercially available refrigerated container and validated with experimental data. The airflow, temperature distribution, and CO(2) concentration within the container were obtained from the simulations. The modeling results can provide guidance on preparing experimental setups, thus saving time and lowering cost, and also provide insight into safety precautions needed to avoid hazardous conditions associated with the release of CO(2) during vaccine distribution.