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<p>Velocity pulses in near-fault areas have a significant impact on long-span engineering structures, necessitating the accurate estimation of parameters for seismic hazard analysis and design. Moreover, the limited availability of near-fault records hinders the incorporation of source characteristics into pulse predictions. Therefore, a deterministic physics-based method based on a kinematic model is used to construct a simulated ground motion dataset in near-fault areas, considering diverse earthquake scenarios. Using Baker’s wavelet method, velocity pulses are identified, and the pulse parameters (pulse amplitude, pulse period, number of oscillations, phase angle, and epoch of the envelope’s peak) are extracted with an equivalent velocity model optimized via the artificial bee colony algorithm. Statistical analysis yielded predictive models that closely align with measured records for pulse period, amplitude, and distribution characteristics. These models, which incorporate fault dip, rupture distance, and other geometric parameters, provide reliable predictions for seismic design in near-fault areas, offering a robust framework for future earthquake scenarios.</p>

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Prediction equations for pulse parameters based on physics-based ground motion simulation

  • 期刊论文

  • 发表日期：

    2025年11月17日

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  • Xiaodan Sun,
  • Qianqi Xu,
  • Zihan Yin,
  • Henok Asfaw Melaku,
  • Yu Liu,
  • Canhui Zhao,
  • Huaiguang Li,
  • Wei Xu

摘要

Velocity pulses in near-fault areas have a significant impact on long-span engineering structures, necessitating the accurate estimation of parameters for seismic hazard analysis and design. Moreover, the limited availability of near-fault records hinders the incorporation of source characteristics into pulse predictions. Therefore, a deterministic physics-based method based on a kinematic model is used to construct a simulated ground motion dataset in near-fault areas, considering diverse earthquake scenarios. Using Baker’s wavelet method, velocity pulses are identified, and the pulse parameters (pulse amplitude, pulse period, number of oscillations, phase angle, and epoch of the envelope’s peak) are extracted with an equivalent velocity model optimized via the artificial bee colony algorithm. Statistical analysis yielded predictive models that closely align with measured records for pulse period, amplitude, and distribution characteristics. These models, which incorporate fault dip, rupture distance, and other geometric parameters, provide reliable predictions for seismic design in near-fault areas, offering a robust framework for future earthquake scenarios.