Probabilistic aftershock hazard analysis, two case studies in West and Northwest Iran

Ommi, S.; Zafarani, Hamid

doi:10.1007/s10950-017-9696-7

Cited by 9 publications

(2 citation statements)

References 47 publications

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“…Iervolino et al (2014) developed a sequence-based PSHA by combining the results of PSHA and APSHA. Ommi and Zafarani (2017) applied APSHA to analyze two instances in Iran. Xu et al (2023) conducted time-dependent PSHA based on hybrid renewal models.…”

Section: Introductionmentioning

confidence: 99%

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Aftershock probabilistic seismic hazard analysis based on enhanced Bayesian network considering frequency information

Liu,

2024

Computer aided Civil Eng

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Bayesian network (BN) is an important tool in probabilistic seismic risk analysis (PSRA) due to its holistic nature and powerful probabilistic inference capabilities. However, while the information that can be stored by BN includes variable values, probability distributions, and relationships between variables, it does not involve event quantities. The results obtained from PSRA and probabilistic seismic hazard analysis (PSHA) are commonly frequency‐related (the number of occurrences per unit time), fundamentally describing event numbers. BN assumes a fixed event number relationship between nodes, but the aftershock counts vary for different mainshock magnitudes. This limitation further restricts its effectiveness in lifespan PSRA for structures. Therefore, this study aims to propose an enhanced BN (EBN) for modeling aftershock PSHA (APSHA) considering frequency information. This paper first introduces the modeling method using BN, including PSHA and a simplified model of APSHA using Båth's law. Next, an EBN that can effectively address frequency issues between the mainshock and aftershocks is presented for modeling APSHA considering the modified Omori's law, while the mathematical principles of both forward and backward inferences for the EBN are elaborated in detail. Then, the article carefully analyzes the utilization of the EBN for APSHA modeling under different scenarios where the information regarding the mainshock is known to varying extents, followed by the extension of the EBN in a time domain to obtain time‐dependent aftershock hazard. Finally, an example of APSHA in a specific location in China is illustrated.

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Section: Introductionmentioning

confidence: 99%

“…(2014) developed a sequence‐based PSHA by combining the results of PSHA and APSHA. Ommi and Zafarani (2017) applied APSHA to analyze two instances in Iran. Xu et al.…”

Section: Introductionmentioning

confidence: 99%

Aftershock probabilistic seismic hazard analysis based on enhanced Bayesian network considering frequency information

Liu,

2024

Computer aided Civil Eng

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Effects of imparted Coulomb stress changes in the seismicity and cluster of the December 2017 Hojedk (SE Iran) triplet

Asayesh

Zarei

Zafarani

2020

Int J Earth Sci (Geol Rundsch)

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A Monte Carlo simulation approach to Aftershock Probabilistic Seismic Hazard Analysis (APSHA): methodology and verification

Kavand,

Saghatforoush

2024

Bull Earthquake Eng

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Probabilistic aftershock hazard analysis, two case studies in West and Northwest Iran

Cited by 9 publications

References 47 publications

Aftershock probabilistic seismic hazard analysis based on enhanced Bayesian network considering frequency information

Aftershock probabilistic seismic hazard analysis based on enhanced Bayesian network considering frequency information

Effects of imparted Coulomb stress changes in the seismicity and cluster of the December 2017 Hojedk (SE Iran) triplet

A Monte Carlo simulation approach to Aftershock Probabilistic Seismic Hazard Analysis (APSHA): methodology and verification

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