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Generation of Orientation-Independent Response Spectrum Matched Records Satisfying  Minimum Fourier Amplitude and Power Spectral Density Requirements

Generation of Orientation-Independent Response Spectrum Matched Records Satisfying Minimum Fourier Amplitude and Power Spectral Density Requirements

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Authors

Luis A Montejo 

Abstract

The seismic design and assessment of critical infrastructure, particularly within the nuclear industry, relies heavily on acceleration time histories compatible with a Design Response Spectrum (DRS). While current spectral matching algorithms effectively tune ground motions to match a target DRS, this process can inadvertently deplete the signal’s energy at specific frequencies, leading to unstable and unconservative In-Structure Response Spectra (ISRS). To mitigate this, the U.S. Nuclear Regulatory Commission (US-NRC) Standard Review Plan (SRP) 3.7.1 mandates a secondary check ensuring the motion satisfies a minimum Power Spectral Density (PSD) requirement. However, while modern seismic hazard definitions have shifted toward orientation-independent metrics (RotDnn), existing matching tools address PSD compliance only for single components. This article presents a unified algorithm that modifies bi-directional seed records to simultaneously match a target RotDnn response spectrum and satisfy minimum RotDnn Fourier Amplitude Spectrum (FAS) and PSD requirements. The methodology integrates the Continuous Wavelet Transform (CWT) with an iterative multi-stage scaling process—combining global frequency adjustments for FAS compliance with localized time-domain gains for PSD sufficiency. This approach allows for the generation of records that meet strict regulatory energy criteria while preserving most of the non-stationary characteristics and directionality of the seed motions.

DOI

https://doi.org/10.31223/X5Z49W

Subjects

Engineering

Keywords

Orientation-independent ground motion, bi-directional shaking, time-history analysis, seismic input selection, decision trees.

Dates

Published: 2026-06-02 16:07

Last Updated: 2026-06-02 16:07

License

No Creative Commons license

Additional Metadata

Conflict of interest statement:
None

Data Availability:
A Python implementation of the proposed algorithm is available from the author GitHub repository

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