Evaluation of Evidence for Inhibition of Very Strong Ground Motions in the Abrahamson and Silva Next Generation Attenuation Ground-Motion Model

Abrahamson, Norman A.; Wooddell, K. E.

doi:10.1785/0120080278

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Abrahamson and Silva [12] M w R S, N, R -Abrahamson and Silva [13] M R RUP RO, S/N V S , HW Ambraseys [14] M w R --Ambraseys [15] M w R JB T, N, S -Campbell [18] M w R SEIS --Campbell [19] M w R SEIS R, T, RO, TO -Campbell and Bozorgnia [20] M w R SEIS S, R, T V S,30 Campbell and Bozorgnia [21] M w R JB , R RUP S, N/NO, R/RO V S,30 , Z TOR , Z 1.0 Cornell et al [22] M L R HYPO --Donovan [23] M R HYPO --Faccioli [24] M R HYPO --Faccioli [25] M R HYPO --Joyner and Boore [26] M R JB --Joyner and Boore [27] M R JB --McGuire [28] M R HYPO --Orphal and Lahoud [29] M R HYPO --TERACorporation [42] M w R RUP --Zare and Sabzali [31] M w R HYPO R, R/S, S V S,30 Laouami [32] M R HYPO -V S,30 Podili and Raghukanth [33] M R RUP --Bajaj and Anbazhagan [34] M w R HYPO --…”

Section: Gmpe (Reference) Magnitude Distance Fault Mechanism Other Va...mentioning

confidence: 99%

“…For magnitude-frequency distribution, it follows the exponential magnitude distribution model proposed by Youngs and Coppersmith [10] and the probability density function of earthquake magnitude of Pailoplee and Palasri [11]. This tool supports the earthquake hazard determination for 21 attenuation models by default and these are taken from Abrahamson and Silva [12], Abrahamson and Silva [13], Ambraseys [14], Ambraseys [15], Boore et al [16], Campbell [17], Campbell [18], Campbell [19], Campbell and Bozorgnia [20], Campbell and Bozorgnia [21], Cornell et al [22], Donovan [23], Faccioli [24], Faccioli [25], Joyner and Boore [26], Joyner and Boore [27], McGuire [28], Orphal and Lahoud [29], Sadigh et al [30], Zare and Sabzali [31], Laouami [32], Podili and Raghukanth [33] and Bajaj and Anbazhagan [34]. There are more than 500 attenuation models in the past literature [35].…”

Section: Introductionmentioning

confidence: 99%

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RETRACTED: PSHRisk-Tool: A Python-Based Computational Tool for Developing Site Seismic Hazard Analysis and Failure Risk Assessment of Infrastructure

2020

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To quantify the annual probability of earthquake ground motion (GM) exceeding a given threshold, the extensively used method named by probabilistic seismic hazard analysis (PSHA) can be adopted. The PSHA software made this method more effortless for estimating earthquake hazards for a seismic site. The main motivation of the PSHRisk-tool is to evaluate the PSHA by a user-friendly graphical interface as well as identify the intensities of GM, which will contribute to the most vulnerable condition for the infrastructure. This python-code based tool can demonstrate the source identification, probability distribution plot of magnitude and distance, formulate the hazard curve according to almost all ground motion prediction equations (GMPEs). The deaggregation for each intensity measure (IM) and the effect of seismic parameters in each GMPE can also be determined. Alongside this, the combination of the failure frequency and the hazard analysis for identifying risk assessment separates this tool from the other existing PSHA software. Accurate verification with analytical and existing test models and a case study inspires its acceptance rate. However, with the quickest and easiest way users can determine the seismic hazard analysis for any location. Failure risk analysis can be evaluated simply based on the structural failure parameters.

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Section: Gmpe (Reference) Magnitude Distance Fault Mechanism Other Va...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

RETRACTED: PSHRisk-Tool: A Python-Based Computational Tool for Developing Site Seismic Hazard Analysis and Failure Risk Assessment of Infrastructure

2020

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Multivariate Bayesian hypothesis testing for ground motion model selection

Shahidzadeh¹,

Yazdani

Eftekhari

2020

J Seismol

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Empirical Evaluation of Hierarchical Ground‐Motion Models: Score Uncertainty and Model Weighting

Mak

Clements

Schorlemmer

2017

Bulletin of the Seismological Society of America

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Using a score to generalize the model performance into one numeric value has been one of the most popular approaches to empirically evaluate groundmotion models (GMMs). This approach has an advantage of simplifying model comparison. We study the effects of data correlation and score variability on the evaluation of GMMs. Most modern GMMs are hierarchical, in which ground motions from the same earthquake are modeled as correlated. We demonstrate, with examples, that incorrect results could occur if such hierarchical GMMs are evaluated by a score that does not duly address the data correlation. We propose to use the multivariate logarithmic score, a natural extension of the widely used univariate logarithmic score (referred to as LLH in the seismological literature), to correctly score hierarchical GMMs. The score variability affects the interpretation of model ranking. We demonstrate that the cluster bootstrap is a better bootstrap strategy, compared with other strategies proposed in the literature, to study the score variability. The bootstrap allows computing two useful quantities: the distinctness index that indicates if two models are truly different given the score variability and the frequency weight, a data-driven weighting scheme that represents the frequentist's interpretation of the weight of a logic-tree branch. The frequency weight has a direct link to the current practice of using multiple GMMs in a probabilistic seismic hazard assessment.Electronic Supplement: Python script to compute the multivariate logarithmic score for a hierarchical lognormal ground-motion model.

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Evaluation of Evidence for Inhibition of Very Strong Ground Motions in the Abrahamson and Silva Next Generation Attenuation Ground-Motion Model

Cited by 3 publications

References 8 publications

RETRACTED: PSHRisk-Tool: A Python-Based Computational Tool for Developing Site Seismic Hazard Analysis and Failure Risk Assessment of Infrastructure

RETRACTED: PSHRisk-Tool: A Python-Based Computational Tool for Developing Site Seismic Hazard Analysis and Failure Risk Assessment of Infrastructure

Multivariate Bayesian hypothesis testing for ground motion model selection

Empirical Evaluation of Hierarchical Ground‐Motion Models: Score Uncertainty and Model Weighting

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