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<p>In earthquake engineering, the precise characterization of long-period ground motion in the form of surface waves (Love and Rayleigh type) is crucial for designing resilient structures, particularly in complex environments such as sedimentary basins. This study evaluates the efficacy of the Normalized Inner Product (NIP) method for estimating surface wave parameters using limited input data within seismic analyses conducted based on numerical simulations. The method is benchmarked against two established techniques–Six Degrees-of-Freedom Polarization Analysis (6C-Pol) and Multiple Signal Classification (MUSIC)–to evaluate its precision in parameter identification. As an example, the methodologies are first applied to analyze surface waves from synthetically generated signals and then from basin-induced surface waves coming from a simplified basin with known characteristics, employing the the spectral element code SEM3D for 3D wave propagation simulation. The results revealed that the NIP method efficiently estimated surface wave characteristics using minimal information, demonstrating its efficiency. Furthermore, due to its capacity to rapidly process large datasets, the NIP method effectively quantified basin-induced surface waves across the basin surface, offering a robust framework for a more comprehensive understanding of 3D basin effects.</p>

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Basin-induced surface wave parameter identification for enhanced seismic hazard assessment

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月31日

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  • Valeria Soto-Moncada,
  • Fernando Lopez-Caballero

摘要

In earthquake engineering, the precise characterization of long-period ground motion in the form of surface waves (Love and Rayleigh type) is crucial for designing resilient structures, particularly in complex environments such as sedimentary basins. This study evaluates the efficacy of the Normalized Inner Product (NIP) method for estimating surface wave parameters using limited input data within seismic analyses conducted based on numerical simulations. The method is benchmarked against two established techniques–Six Degrees-of-Freedom Polarization Analysis (6C-Pol) and Multiple Signal Classification (MUSIC)–to evaluate its precision in parameter identification. As an example, the methodologies are first applied to analyze surface waves from synthetically generated signals and then from basin-induced surface waves coming from a simplified basin with known characteristics, employing the the spectral element code SEM3D for 3D wave propagation simulation. The results revealed that the NIP method efficiently estimated surface wave characteristics using minimal information, demonstrating its efficiency. Furthermore, due to its capacity to rapidly process large datasets, the NIP method effectively quantified basin-induced surface waves across the basin surface, offering a robust framework for a more comprehensive understanding of 3D basin effects.