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Gaussian process regression-based surrogate modelling for direct loss-based seismic design of low-rise base-isolated structures

Suarez, D; Rubini, G; Gentile, R; Galasso, C; (2022) Gaussian process regression-based surrogate modelling for direct loss-based seismic design of low-rise base-isolated structures. In: Procedia Structural Integrity. (pp. pp. 1728-1735). Elsevier Green open access

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Abstract

Seismic base isolation has gained popularity in the last decades. As a result, many structures are now equipped with base isolation systems to offer enhanced seismic performance and meet the needs of risk-aware stakeholders. However, a robust performance-based seismic design of these types of structures is generally not carried out due to the iterative nature of common design approaches and the time/computational resources required for such iterations, which are incompatible with the preliminary design phase. Indeed, seismic risk/loss is often just assessed at the end of the design process as a final verification step. This paper offers an overview of a simplified methodology for the seismic design of low-rise structures equipped with a base isolation system to achieve a predefined level of earthquake-induced economic loss while complying with a predefined minimum level of structural reliability. The main advantage of the proposed methodology is that it requires no design iterations. The procedure is enabled by Gaussian-process-regression-based surrogate probabilistic seismic demand modelling of equivalent single degree of freedom systems (i.e., the probability distribution of peak horizontal displacements and accelerations on top of the isolation layer conditional on different ground-motion intensity levels). Combined with simplified loss models for the base isolation system and the structural and non-structural components of the superstructure, this approach allows mapping a range of structural configurations to their resulting seismic loss. A designer can then select one of the identified combinations of the strength of the superstructure and properties of the isolation system conforming with the loss target, and reliability requirements, and consequently detail the superstructure and isolation system accordingly. This paper introduces the implemented surrogate probabilistic seismic demand models and provides an overview of a tentative Direct Loss-based Design procedure for low-rise base-isolated structures.

Type: Proceedings paper
Title: Gaussian process regression-based surrogate modelling for direct loss-based seismic design of low-rise base-isolated structures
Event: XIX ANIDIS Conference, Seismic Engineering in Italy
ISBN-13: 9781713870418
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.prostr.2023.01.221
Publisher version: https://doi.org/10.1016/j.prostr.2023.01.221
Language: English
Additional information: © 2023 The Author(s). Published by Elsevier B.V. under a Creative Commons license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Inst for Risk and Disaster Reduction
URI: https://discovery.ucl.ac.uk/id/eprint/10171403
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