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Meeting TMS Specialty Congress 2024
Symposium 2nd World Congress on Artificial Intelligence in Materials & Manufacturing (AIM 2024)
Presentation Title Intrinsic Dimensionality Estimates for Microstructural Data
Author(s) Veera Sundararaghavan, Megna Shah, Jeff Simmons
On-Site Speaker (Planned) Megna Shah
Abstract Scope We hypothesize that there are regions of processing space that are homeomoprhic to microstructure space. That is, the domains are continuous, invertible and one-to-one. The continuity assumption implies that small changes in the processing domain result in small changes in the microstructure domain, and vice-versa. The invertibility assumption means that microstructure can be inverted to find the process. And both of these assumptions mean the mapping is one-to-one. We know that not all microstructures are homeomorphic to processing, but finding regions where this is true will enable autonomous materials design. A key property of homeomorphism that both domains have the same intrinsic dimensionality. Here we use an approach for non-linear data, to measure the intrinsic dimensionality of microstructure data. The approach, its modifications and the results will be described here.
Proceedings Inclusion? Definite: Other

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