Robust Data-Driven Turbulence Modeling for RANS Closures Using a SciML Approach for Validation
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Each step in the scientific process generates contextual information about the data that is important to consider when performing data integration, developing models of biological process, or training AI models. We will develop a flexible, template-driven tool that will log biological samples, capture metadata about those samples, and track the type(s) of analysis being performed by researchers providing samples for analysis by mass spectrometry.
Our collaborators at Texas A&M will be presenting this work.
Minitutorial at SIAM CSE25, see https://www.siam.org/conferences-events/siam-conferences/cse25/program/minitutorials/.
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Our collaborators at Texas A&M will be presenting this work.
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Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.