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Enregistrement W6983489608

A methodology for the estimation of kappa (κ) for large datasets. Example application to rock sites in the NGA-East database

2016· report· en· W6983489608 sur OpenAlexaboutno aff

Notice bibliographique

RevueGreenwich Academic Literature Archive (University of Greenwich) · 2016
Typereport
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueDiverse Scientific and Economic Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDisplacement (psychology)EstimationStackingSpectral accelerationAccelerationMean squared errorStandard deviation
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

This report reviews four of the main approaches (two band-limited and two broadband) currently used for estimating the site κ0: the acceleration slope (AS) above the corner frequency, the displacement slope (DS) below the corner frequency, the broadband (BB) fit of the spectrum, and the response spectral shape (RESP) template. Using these four methods, estimates of κ0 for rock sites in Central Eastern North America (CENA) in the shallow crustal dataset from NGAEast are computed for distances less than 100 km.
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\nUsing all of the data within 100 km, the mean κ0 values are 8 msec for the AS approach and 27 msec for the DS approach. These mean values include negative κ estimates for some sites. If the negative κ values are removed, then the mean values are 25 msec and 42 msec, respectively. Stacking all spectra together led to mean κ0 values of 7 and 29 msec, respectively. Overall, the DS approach yields 2–3 times higher values than the AS, which agrees with previous observations, but the uncertainty of the estimates in each case is large. The AS approach seems consistent for magnitudes down to M3 but not below. 
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\nThere is large within-station variability of κ that may be related to differences in distance, Q, complexity along the path, or particular source characteristics, such as higher or lower stress drop. The station-to-station differences may be due to site-related factors. Because most sites have been assigned Vs30 = 2000 m/sec, it is not possible to correlate variations in κ0 with rock stiffness. 
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\nBased on the available profile, the individual spectra are corrected for crustal amplification and only affect results below 15 Hz. Since the AS and DS approaches are applied over different frequency ranges, we find that only the DS results are sensitive to the amplification correction. More detailed knowledge of individual near-surface profiles may have effects on AS results, too. Although κ is considered to be caused solely by damping in the shallow crust, measurement techniques often cannot separate the effects of damping and amplification, and yield the net effect of both phenomena. 
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\nThe two broadband approaches, BB and RESP, yield similar results. The mean κ0_BB is 5±0.5 msec across all NEHRP class A sites. The κ0_RESP for the two events examined is 5 and 6 msec. From literature, the average value of κ0 in CENA is 6 ± 2 msec. This typical value is similar to the broadband estimates of this study and to the mean κAS when all available recordings are used along with all flags. When only recordings with down-going FAS slope are selected from the dataset, the mean value of κAS increases by a factor of 2–3.
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\nTo evaluate the scaling of high-frequency ground motion with κ, we analyze residuals from ground motion prediction equations (GMPEs) versus κ estimates. Using the κ values from the AS approach, the average trend of the ln(PSA) residuals for hard-rock data do not show the expected strong dependence on κ, but when using κ values from the DS approach, there is a stronger correlation of the residuals, i.e., a κ that is more consistent with the commonly used analytically based scaling. The κDS estimates may better reflect the damping in the shallow crust, while the κAS estimates may reflect a net effect of damping and amplification that has not been decoupled. The κDS estimates are higher than the κAS estimates, so the expected effect on the high-frequency ground motion is smaller than that expected for the κAS estimates.
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\nAn empirical hard-rock site factor model is developed that represents the combined Vs-κ0 site factor relative to a 760 m/sec reference-site condition. At low frequencies (< 3 Hz), the empirical site factors are consistent with the scaling due to the change in the impedance contrast. At high frequencies (> 10 Hz), the residuals do not show the strong increase in the site factors as seen in the analytical model results. A second hard-rock dataset from British Columbia, Canada, is also used. This BC hard-rock residuals show an increase in the 15–50 Hz range that is consistent with the analytical κ0 scaling for a hard-rock κ0 of about 0.015 sec.
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\nThe variability of the PSA residuals is also used to evaluate the κ0 scaling for hard-rock sites from analytical modeling. The scatter in existing κ0 values found in literature is disproportionately large compared to the observed variability in high-frequency ground motions. We compared the predicted ground-motion variability based on analytical modeling to the observed variability in our residuals. While the hard-rock sites are more variable at high frequencies due to the additional κ0 variability, this additional variability is much less than the variability predicted by the analytical modeling using the variability from κ0-Vs30 correlations. This is consistent with weaker κ0 scaling compared to that predicted by the analytical modelling seen in the mean residuals.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,461
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0020,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,133
Tête enseignante GPT0,293
Écart entre enseignants0,161 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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