Technical Papers
Mar 29, 2022

Development of a Generalized Cross-Building Structural Response Reconstruction Model Using Strong Motion Data

Publication: Journal of Structural Engineering
Volume 148, Issue 6

Abstract

Models for reconstructing seismic response demands across multiple buildings can aid in cluster-level rapid postearthquake damage assessment. Response demands from 188 buildings affected by 25 earthquakes were used to develop a cross-building response reconstruction model. A structural response prediction model (SRPM) was developed, which is based on a modern ground motion model with added “building response” terms. A kriging algorithm is used to interpolate the within-event residuals which, together with the SRPM, form a generalized cross-building response reconstruction (CBRR) model. Given the recorded responses for a subset of instrumented buildings in a cluster, the demands in the uninstrumented buildings can be reconstructed by combining the median values generated from the SRPM and estimated within-event residuals for a given site obtained from the kriging model.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The research presented in this paper was supported by the National Science Foundation CMMI research Grant No. 1538866.

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Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 148Issue 6June 2022

History

Received: Sep 13, 2021
Accepted: Jan 11, 2022
Published online: Mar 29, 2022
Published in print: Jun 1, 2022
Discussion open until: Aug 29, 2022

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Machine Learning Engineer, Pinterest Inc., Palo Alto, CA 94306 (corresponding author). ORCID: https://orcid.org/0000-0003-1626-3561. Email: [email protected]
Henry V. Burton, M.ASCE [email protected]
Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of California Los Angeles, CA 90095. Email: [email protected]
Professor, Dept. of Civil and Environmental Engineering, Univ. of California Los Angeles, CA 90095. ORCID: https://orcid.org/0000-0003-3602-3629. Email: [email protected]
John W. Wallace, F.ASCE [email protected]
Professor, Dept. of Civil and Environmental Engineering, Univ. of California Los Angeles, CA 90095. Email: [email protected]

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Cited by

  • Advances in Data-Driven Risk-Based Performance Assessment of Structures and Infrastructure Systems, Journal of Structural Engineering, 10.1061/JSENDH.STENG-12434, 149, 5, (2023).
  • Rapid seismic fragility curves assessment of eccentrically braced frames through an output-only nonmodel-based procedure and machine learning techniques, Engineering Structures, 10.1016/j.engstruct.2022.115290, 278, (115290), (2023).
  • A dual Kriging-XGBoost model for reconstructing building seismic responses using strong motion data, Bulletin of Earthquake Engineering, 10.1007/s10518-023-01624-y, (2023).

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