An AI-Based Approach to Optimize Stress in Shrink Fits

The present analytical design of shrink fits typically results in an uneven stress condition that can lead to failure in a variety of manners. With increasing loads and the use of brittle materials, the optimization of the stresses in the shrink fit hence becomes increasingly necessary. Currently ex...

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Bibliographic Details
Main Authors: Dausch, V., Kröger, J., Kreimeyer, M.
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
Optimization techniques
Stress state
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Summary:The present analytical design of shrink fits typically results in an uneven stress condition that can lead to failure in a variety of manners. With increasing loads and the use of brittle materials, the optimization of the stresses in the shrink fit hence becomes increasingly necessary. Currently existing approaches do not solve the problem satisfactorily or increase the manufacturing and design effort. This paper therefore considers the implementation of an AI-based stress optimization using reinforcement learning, which performs stress optimization by geometrically contouring the interstice.
ISSN:2732-527X
2732-527X
DOI:10.1017/pds.2022.157