Rather, Abira and Manohar, CS (2023) Probabilistic Model Reduction in the Analysis of Building Frames Subject to Sudden Loss of Columns. In: Advances in Reliability and Safety Assessment for Critical Systems - Proceedings of the 5th National Conference on Reliability and Safety NCRS 2022, 10-12 March 2022, Chennai, pp. 257-269.
Full text not available from this repository.Abstract
The problem of uncertainty propagation and global response sensitivity analysis (GRSA) in the broad context of structural robustness modeling is considered. A combination of nonlinear finite element modeling, Monte Carlo simulations, and factor mapping method is employed to tackle this problem. The structure under study is modeled on the OpenSEES platform using distributed plasticity beam-column elements. The response of the structure, triggered by the sudden removal of a column, is analyzed using nonlinear transient dynamic analysis procedures. Various quantities, namely, yield strength, Young�s modulus, ultimate strength, ultimate strain, Poisson�s ratio, dead and live loads, and inertial and damping properties, are modeled as a set of non-Gaussian and dependent random variables. An ensemble of system response time histories following the sudden loss of column is generated using Monte Carlo simulations. The data is further processed using the factor mapping method to study the influence of various random variables on the variability of specified response variables. This, in turn, is shown to form the basis for achieving probabilistic reduced-order models for the system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Item Type: | Conference Paper |
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Publication: | Lecture Notes in Mechanical Engineering |
Publisher: | Springer Science and Business Media Deutschland GmbH |
Additional Information: | The copyright for this article belongs to the Springer Science and Business Media Deutschland GmbH. |
Keywords: | Disproportionate collapse; Global response sensitivity analysis; Probabilistic model reduction; Statistical distances |
Department/Centre: | Division of Mechanical Sciences > Civil Engineering |
Date Deposited: | 15 Feb 2024 12:12 |
Last Modified: | 15 Feb 2024 12:12 |
URI: | https://eprints.iisc.ac.in/id/eprint/83553 |
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