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Conditional Ground-Motion Model for Peak Ground Velocity for Active Crustal Regions

Authors: Norman Abrahamson; Sarabjot Bhasin;

Conditional Ground-Motion Model for Peak Ground Velocity for Active Crustal Regions

Abstract

Conditional models for the horizontal and vertical peak ground velocity (PGV), given the pseudospectral acceleration [PSA(T)] values, are developed for active crustal regions. The period of the PSA(T) used in the conditional model, TPGV , is magnitude dependent, which captures the effect of the magnitude dependence of the earthquake source corner frequency on the PGV. Conditional models can be used to estimate the PGV given a design spectrum and are applicable for magnitudes between 3.0 and 8.5, and for distances up to 200 km. The conditional PGV models can also be combined with appropriate GMMs for PSA(T) to develop traditional GMMs for PGV that are consistent with the more complex scaling included in the PSA(T) model. Unlike previous conditional PGV models, the slope on the ln[PSA(T)] term is allowed to be different from unity. With this feature, an appropriate aleatory standard deviation of the resulting In(PGV) can be computed, avoiding the over-prediction of the aleatory standard deviation of the PGV seen in previous conditional PGV models.

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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
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