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First use of cognitive algorithms in investigations under compensated gravity
A Delgado1, H Nirschl, T h Becker
1Lehrstuhl fur Fluidmechanik und Prozessautomation, TU Munchen, Freising, Germany.
Microgravity Science and Technology
|January 1, 1996
Summary
Cognitive algorithms, including fuzzy logic and artificial neural networks, aid in predicting complex behaviors during compensated gravity experiments. These methods offer faster, accurate results compared to traditional simulations, enabling real-time analysis.
Area of Science:
- Fluid dynamics
- Computational physics
- Artificial intelligence
Background:
- Investigating complex processes under compensated gravity presents challenges due to unpredictable perturbations.
- Traditional methods struggle when underlying equations are unknown or computationally intractable.
- Cognitive computing offers a novel approach to model and optimize such systems.
Purpose of the Study:
- To propose and evaluate cognitive algorithms for problem-solving in compensated gravity research.
- To demonstrate the utility of fuzzy logic (FL) and artificial neural networks (ANN) in this domain.
- To showcase the application of cognitive computing to the flow field between coaxial rotating disks.
Main Methods:
- Discussion of fundamental cognitive algorithm concepts.
- Detailed explanation of FL and ANN algorithms for compensated gravity studies.
- Application of trained ANN to predict flow fields and comparison with Navier-Stokes solutions.
Main Results:
- Cognitive algorithms accurately describe and predict complex process behavior, even with perturbations.
- ANN models provide excellent agreement with direct numerical simulations for flow fields.
- ANN calculations are significantly faster than traditional numerical simulations, enabling real-time prediction.
Conclusions:
- Cognitive algorithms, particularly ANNs, are effective tools for compensated gravity research.
- These methods accelerate analysis and allow for real-time experimental monitoring.
- This study pioneers the use of cognitive computing in compensated gravity investigations.