Dataset of ultralow temperature refrigeration for COVID 19 vaccine distribution solution
Most COVID-19 vaccines require temperature control for transportation and storage. Two types of vaccine have been developed by manufacturers (Pfizer and Moderna). Both vaccines are based on mRNA and lipid nanoparticles requiring low temperature storage. The Pfizer vaccine requires ultra-low temperature storage (−80 °C to −60 °C), while the Moderna vaccine requires −30 °C storage. However, the last stage of distribution is quite challenging, especially for rural or suburban areas, where local towns, pharmacy chains and hospitals may not have the infrastructure required to store the vaccine at the required temperature. In addition, there is limited data available to address ancillary challenges of the distribution framework for both transportation and storage stages, including safety concerns due to human exposure to large amounts of CO 2 from dry-ice sublimation, issues due to the pressure increase caused by dry-ice sublimation, and the potential issue caused by non-uniform cryogenic temperatures. As such, there is a need for test dataset to assist the development of a quick, effective, secure, and safe solution to mitigate the challenges faced by vaccine distribution logistics.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1847016
- Alternate ID(s):
- OSTI ID: 1855641
- Journal Information:
- Scientific Data, Journal Name: Scientific Data Journal Issue: 1 Vol. 9; ISSN 2052-4463
- Publisher:
- Nature Publishing GroupCopyright Statement
- Country of Publication:
- United Kingdom
- Language:
- English
A study on computational fluid dynamics modeling of a refrigerated container for COVID-19 vaccine distribution with experimental validation
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journal | January 2022 |
| Test Data of Ultralow Temperature Refrigeration for COVID 19 Vaccine Distribution Solution | dataset | January 2021 |
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A study on computational fluid dynamics modeling of a refrigerated container for COVID-19 vaccine distribution with experimental validation