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National Aeronautics And Space Administration·Texas

AETHER Data Modeling

Closes 11/21/2025$500k – $2MRequest for Information
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Description

This opportunity is a request for information (RFI) from NASA, seeking input from potential vendors for market research purposes. The goal is to develop a model that can accurately predict the risk of Spaceflight Decompression Sickness (DCS) based on evidence from operational data sources. The model should be able to predict the risk of both Type I and Type II DCS in nominal and off-nominal conditions, considering factors such as cabin and suit pressures, sex, cardiorespiratory fitness, and more. Some key points to consider include: * The model must be validated according to NASA's Standard for Models and Simulations. * Modeling teams will have 6 months to develop their model based on a representative training dataset provided by NASA. * NASA will hold a comparable dataset for model validation, which will occur within a 2-month period. * Proposers will receive an additional 2 months to revise and submit their revised model based on feedback from NASA. * The incorporation of other applicable datasets and results from ongoing data collection will be addressed in follow-on solicitations.

Attached files

Contact

Jadon Terry

[email protected]

Key dates

Opened
11/14/2025
Closes
11/21/2025
Duration
6 months

Last updated

Details

Type
Request for Information
Industry
Aerospace and Defense
NAICS
518210
Solicitation №
80JSC025DCS2

Budget estimate

$500,000 – $2,000,000

Given the complexity of the project and the fact that it involves research and development, the budget for this opportunity could be substantial. However, since the document does not provide a specific budget amount, it's difficult to estimate. Considering the scope of the project, which involves developing a model for predicting DCS risk for lunar and Mars exploration missions, the budget could be in the range of $500,000 to $2 million. This estimate is based on the assumption that the project will require significant resources and expertise in research and development.

AI estimate from the solicitation

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