Application of Interpolatory Methods of Model Reduction to an Elevated Railway Pier

Authors

  • Bertero, Santiago
  • Gugercin, Serkan
  • Sarlo, Rodrigo

DOI:

https://doi.org/10.18687/LACCEI2023.1.1.1614

Keywords:

Dynamics, Structures, Reduced Order Modeling, Interpolatory Methods, Seismic

Abstract

Be it due to time constraints or insufficient processing power – or a combination of both – the use of models with large numbers of Degrees of Freedom (DoF) may be unsuitable to provide a client with results in a timely manner. The use of physics-based reduced models – or proxy structures – are popular among practitioners to solve this issue, as they keep intact all the underlying properties of the 2nd Order Problem at a fraction of the cost. In this report, Interpolatory Methods of Model Reduction are explored as an alternative, and applied to a 3D Space Frame. The methods chosen allow for structure-preserving reduced models, and differ mainly on the selection of interpolation points. A comparison between the response of these reduced models and a proxy structure against two different types of inputs show that Interpolatory Methods are a viable, more flexible option when it comes to reducing the internal DoFs of a structural model, though engineering judgement is required to ensure it adequately captures the most relevant aspects of the response for the specific application.

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Published

2023-07-27

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Section

Articles

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Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

LACCEI retains copyright of all published articles under the terms of its copyright transfer agreement. As the copyright holder, LACCEI distributes the articles to the public under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).

How to Cite

Bertero, Santiago, Gugercin, Serkan, & Sarlo, Rodrigo. (2023). Application of Interpolatory Methods of Model Reduction to an Elevated Railway Pier. LACCEI, 1(8). https://doi.org/10.18687/LACCEI2023.1.1.1614