AETHER Data Modeling

NASA's Johnson Space Center has issued a Request for Information seeking contractor capabilities to develop a predictive modeling tool for Spaceflight Decompression Sickness (DCS) risk assessment during extravehicular activities for lunar and Mars exploration missions. The agency requires development of a comprehensive model that can accurately predict both Type I and Type II DCS risks under varying conditions including cabin and suit pressures, physiological parameters, and environmental factors specific to partial gravity environments. Contractors must demonstrate capability to work with NASA-provided training datasets containing approximately 1,500 trial records with subject demographics, decompression stress details, and pre-breathe protocol information. The model must be validated according to NASA-STD-7009 standards and deliverables include executable modeling tools with source code, comprehensive reports, user guides, and publication plans. Interested parties must submit capability statements by October 10, 2025, as this market research effort does not constitute a solicitation commitment from the government.

This procurement opportunity carries no set-aside designation and is open to all qualified contractors. The development timeline requires completion of the predictive modeling tool within six months, followed by two demonstration sessions to NASA personnel and an additional two-month revision period based on initial feedback. No current incumbent contractors or specific budget ranges are identified in this pre-solicitation notice. The scope emphasizes developing enhanced modeling capabilities that can account for multiple EVAs, diverse astronaut populations, and various atmospheric conditions not addressed in previous studies. NASA will provide the substantial dataset of 1,500 trials to support model development and validation efforts. The ultimate objective focuses on creating a risk prediction tool that balances DCS risk mitigation with EVA performance optimization and resource efficiency for future deep space exploration missions.