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Dynamic analysis of steel frames with uncertain semi-rigid connections

conference contribution
posted on 2017-07-28, 10:41 authored by Stavros Kasinos, Alessandro Palmeri, S. Maheshwari, Mariateresa Lombardo
The paper addresses the dynamic analysis of linear steel frames with uncertain semi-rigid connections subjected to deterministic seismic excitation. The uncertainty is conveniently characterised in the reduced modal space using a recently proposed surrogate model, which requires only a reduced set of parameters. A procedure is presented in which the model parameters are identified over various configurations calibrating the probabilistic definition in the full geometrical space. It is found that the dynamic response can significantly be influenced by the level of connection flexibility and its random fluctuations around the nominal value. Comparisons with conventional analyses and Monte Carlo simulations evidence that the proposed model is an efficient alternative for accurately representing the response of structures with uncertainties.

History

School

  • Architecture, Building and Civil Engineering

Published in

12th International Conference on Structural Safety & Reliability

Citation

KASINOS, S. ...et al., 2017. Dynamic analysis of steel frames with uncertain semi-rigid connections. IN: Bucher, C., Ellingwood, B.R. and Frangopol, D.M. (eds.) Safety, Reliability, Risk, Resilience and Sustainability of Structures and Infrastructure. Herausgeber: TU Verlag.

Publisher

© the authors. Published by TU Verlag

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2017-05-05

Publication date

2017

Notes

This is a conference paper it was presented at the 12th International Conference on Structural Safety & Reliability (ICOSSAR 2017), Vienna, Austria, 6-10th Aug.

ISBN

9783903024281

ISSN

2523-9198

Language

  • en

Location

Vienna, Austria

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