OMB Individually Reported
Near-Reality Slosh Model using AIML
Low riskExact public inventory row
Description
Liquid slosh for aircraft and spacecraft is a highly challenging topic; traditional slosh modeling & simulation approaches are very computationally expensive. This project seeks to use AIML techniques such as neural networks to create ML surrogate models to accurately approximate traditional techniques.
Detailed example
Outputs will include AIML-powered surrogate slosh models, to include accuracy and error measures.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Time saving for slosh model generation
Controls / human review
ATO: Not reported; PIA: Not published