Data-Driven Material Models for Engineering Materials Subjected to Arbitrary Loading Paths: Influence of the Dimension of the Dataset

Burcu Tasdemir, Vito Tagarielli, Antonio Pellegrino

Research output: Chapter in Book/Report/Conference proceedingChapter in a book

Original languageEnglish
Title of host publicationAdditive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4
Pages91-95
Number of pages5
DOIs
Publication statusPublished - 2024

Bibliographical note

Publisher Copyright:
© The Society for Experimental Mechanics, Inc. 2024.

Keywords

  • Machine learning
  • Surrogate model
  • Experimental mechanics
  • Data-driven
  • Constitutive modelling

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