Evaluating the Impact of Spectrum-Matched Time Histories on Biased FRS Estimates: Part 2-Adequacy Analysis Using Enhanced Spectrum-Matched Time Histories

ABSTRACT Floor response spectra (FRS) are critical for the seismic analysis of the nuclear secondary system as per American Society of Civil Engineers Standard 4-16. Despite the use of spectrum-matched time histories, significant variations in FRS estimates can lead to inaccuracies in seismic analysis and system design. Our companion article explored the influences of ground-motion parameters modification due to spectral matching on FRS accuracy using machine learning, revealing that changes in spectral acceleration and damping scaling factor index IDSF for damping ratios ξ=7%, ξ=2%, and ξ=10%, significantly contributed to biased FRS estimates. Building on these insights, we propose enhanced spectrum-matched time histories that include additional IDSF values for different damping ratios. Using a nuclear service building as a case study, we demonstrate that these enhanced time histories significantly improve FRS accuracy, benefiting seismic safety practices in the nuclear industry.

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Publication Details

Journal
Bulletin of the Seismological Society of America
Published
2025-02-06
DOI
https://doi.org/10.1785/0120240109
Primary Topic
Seismic Performance and Analysis
Type
article
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article

Evaluating the Impact of Spectrum-Matched Time Histories on Biased FRS Estimates: Part 2-Adequacy Analysis Using Enhanced Spectrum-Matched Time Histories

X. Wu, Bo Li, Xiaoying Sun
Bulletin of the Seismological Society of America
Seismic Performance and Analysis
article

Evaluating the Impact of Spectrum-Matched Time Histories on Biased FRS Estimates: Part 2-Adequacy Analysis Using Enhanced Spectrum-Matched Time Histories

X. Wu, Bo Li, Xiaoying Sun
article en

Abstract

ABSTRACT Floor response spectra (FRS) are critical for the seismic analysis of the nuclear secondary system as per American Society of Civil Engineers Standard 4-16. Despite the use of spectrum-matched time histories, significant variations in FRS estimates can lead to inaccuracies in seismic analysis and system design. Our companion article explored the influences of ground-motion parameters modification due to spectral matching on FRS accuracy using machine learning, revealing that changes in spectral acceleration and damping scaling factor index IDSF for damping ratios ξ=7%, ξ=2%, and ξ=10%, significantly contributed to biased FRS estimates. Building on these insights, we propose enhanced spectrum-matched time histories that include additional IDSF values for different damping ratios. Using a nuclear service building as a case study, we demonstrate that these enhanced time histories significantly improve FRS accuracy, benefiting seismic safety practices in the nuclear industry.

Bulletin of the Seismological Society of AmericaVol. 115(2)
Harbin Institute of Technology (CN), China Earthquake Administration (CN)
Openalex Percentile: Top 97%
Seismic Performance and Analysis
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