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Training of a Classifier for Structural Component Failure Based on Hybrid Simulation and Kriging

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  • Giuseppe Abbiati
  • Stefano Marelli, Institute of Structural Engineering
  • ,
  • Connor Ligeikis, University of Michigan, Ann Arbor
  • ,
  • Richard Christenson, Southern Connecticut State University
  • ,
  • Bozidar Stojadinović, Institute of Structural Engineering

Hybrid simulation is a tool for investigating the dynamic response of a structural prototype subjected to realistic loading. Hybrid simulation is conducted using a hybrid model that combines physical and numerical substructures interacting with each other in a feedback loop. As a result, the tested substructure interacts with a realistic assembly subjected to a credible loading scenario. In the current practice, experimental results obtained via hybrid simulation support conceptualization and calibration of computational models for structural analysis. Instead, this paper extends the scope of hybrid simulation in constructing a safe/failure state classifier for the tested substructure by adaptively designing a sequence of parametrized hybrid simulations. Such a classifier is intended to compute the state of any physical-substructure-like component within system-level numerical simulations. It follows that the main contribution of this paper lies in the way experimental results are aggregated and integrated with structural analysis. The proposed procedure is experimentally validated for a three-degrees-of-freedom hybrid model subjected to Euler buckling.

Original languageEnglish
Article number04021137
JournalJournal of Engineering Mechanics
Number of pages8
Publication statusPublished - Jan 2022

    Research areas

  • Active learning, Buckling, Classifier, FRAME, Hybrid simulation, Kriging, Metamodeling

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