ML24355A118
| ML24355A118 | |
| Person / Time | |
|---|---|
| Issue date: | 10/30/2024 |
| From: | Vladimir Graizer, Scott Stovall NRC/RES/DE/SGSEB |
| To: | |
| Thomas Weaver 301-415-2383 | |
| Shared Package | |
| ML24355A102 | List: |
| References | |
| Download: ML24355A118 (19) | |
Text
Global GS24 Ground Motion Models for the Active Crustal Regions based on a Non-Traditional Modeling Approach Vladimir Graizer and Scott Stovall U. S. Nuclear Regulatory Commission Office of Nuclear Regulatory Research DOE/NRC Natural Phenomena Hazards Meeting October 29-30, 2024
Introduction
- The new GS24b and GS24 models are based on Pacific Earthquake Engineering Research (PEER)
Center Next Generation Attenuation Phase 2 (NGA-West2) database expanded with recordings from the three 2023 Turkish earthquakes with moment magnitudes of 6.3, 7.5 and 7.8.
The ground motion database is compiled from shallow crustal earthquakes in active crustal regions (ACRs) to develop a Ground Motion Model (GMM) for the average RotD50 (50th percentile or median response) horizontal components of peak ground acceleration (), peak ground velocity () and 5% damped elastic pseudo-absolute acceleration response spectral ordinates () at 21 oscillator periods (T) ranging from 0.01 to 10 sec.
- The number of predictors used in the current model is limited to a few measurable parameters: moment magnitude (), closest distance to the fault rupture plane (), time-averaged shear wave velocity in the upper 30 m of the geological profile (), depth to the shear wave velocity horizon of 2.5 km/s (2.5), style of faulting () and apparent (intrinsic and scattering) attenuation factor ((, )) of 5%
damped spectral acceleration.
- We limited the dataset by earthquakes with 4.0 7.9 and rupture distances 400 km. The dataset includes recordings from California, Alaska (crustal events), Taiwan, Turkey, Italy, Greece, New Zealand and Northwest China ACRs. It did not include data from Japan because most of the sites in Japan are characterized by a subsurface geology significantly different from the site conditions in other ACRs. The GS24b and GS24 should be considered to be global models since they include recordings from multiple ACRs.
2
Distribution of recordings with respect to M,, PGA and 3
The dataset is created based on the NGA-West2 flat file previously used for developing GK17 model (Graizer, 2018) enhanced by the recordings from the three 2023 Turkish earthquakes with 6.3, 7.5 and 7.8.
NGA-West2 data are shown with open circles and additional Turkish data with red circles.
The dataset consists of 13,241 recordings from the NGA-West2 database with the addition of 685 Turkish recordings with the total number of 401 earthquakes.
Datasets used to create GS24 GMMs 4
0 1000 2000 3000 4000 5000 6000 7000 M4_400 M5_150 M4_250 Datasets M4_5 M5_6 M6_7 M7_7.9 The 1st dataset of 4 7.9 and distances 400 km that includes 13,926 called M4_R400.
The 2nd dataset (subset of the 1st dataset) includes 5,063 data points for 5.0 and 150 km (M5_150).
The 3rd dataset (also subset of the 1st dataset) includes 6,046 data points covering the range of 4 7.9 and 250 km (M4_R250).
PGA Magnitude Scaling 5
0.1 1
3.5 4.5 5.5 6.5 7.5 8.5 Mw Magnitude Scaling GS24 MagScale GK17 MagScale 1, = 21 (22 ]
4 < 5.0 1 ( + 2 + 3]
5.0 Where F1(M, kscale) is magnitude scaling function. PGA magnitude scaling function has a linear scaling in logarithmic space for small magnitudes and the same style of saturation approximation function as in our previous model for larger magnitudes (Graizer and Kalkan, 2016):
where cn are coefficients, kscale is a scaling factor. In the current GS24 models we modified the turning point on scaling from magnitude 5.5 to 5.0 effectively increasing the scaling for M < 5.5.
[
]
2 2
2 2
2 2
1
~
1
~
2 2
[(1
)
4
)]
1
(
)
4
(
/
)
1 1 (
)
4
(
/
)
[1
]
4
(
)
M corn corn geom rup trans trans trans corn trans corn trans rup trans rup R
R rup rup corn rup corn rup rup corn rup corn R
R D
R R
R R
D R
R R
R R
R D R R
w R
R R
R D
R R
w G
R
+
=
+
+
+
=
Geometric Attenuation where Rcorn is the corner distance in the near-source defining the plateau without significant attenuation of ground-motion and parameter D controls the bump at short distances. Parameter w is a factor scaling second part of equation 2 to avoid step in slope. Parameter Rcorn is directly proportional to the moment magnitude (M) of an earthquake; the larger is M, the wider is the plateau defined by Rcorn (Graizer and Kalkan, 2007; 2011). Rtrans is a transition distance between body and surface waves dominance. Rtrans = 50 km for the WUS.
6 We are assuming bilinear attenuation slope reflecting geometric spreading of shear and surface waves:
Rtrans = 50 km for the WUS
Generic spectral shape,0 model, and controlling parameters 7
For modeling spectral shape, we are using the approximation function developed by Graizer and Kalkan (2009).
This function is a combination of a single-degree-of-freedom (SDF) oscillator and a modified log-normal probability density function (PDF).
The updated spectral shape model
() is a continuous function of spectral period (or frequency) and is formulated as shown in the Figure.
Apparent Anelastic Attenuation QSA(f)
This filter in GS24 adjusts the distance attenuation rate by including the apparent attenuation of the response spectra given as:
f is frequency, QSA(f) is apparent attenuation quality factor of RS amplitudes, and is apparent wave velocity (probably close to the surface wave velocity). QSA(f) is different from the seismological Q(f) measured using Fourier amplitude spectra (FAS) of S-, Lg-or coda-waves.
To estimate apparent (anelastic) attenuation of response spectra QSA(f) I performed inversions using the same approach as that applied to the FAS (e.g., Chapman and Conn, 2016), but replacing the FAS with 5% damped SAs (Graizer, 2017):
A(f) are recorded and SA(f) are predicted SAs without correction for apparent attenuation. I assigned a value of =3.5 km/s, but in principle it can be period dependent.
8 3(
)
exp(
)
( )
rup SA SA f R G Q f
Q f
=
[
]
( )
ln
( )
( )
( )
ln
( )
( )
rup rup SA SA R
f R
f A f Q
f SA f Q
f A f SA f
=
=
y = 120.25x0.9581 R² = 0.9952 1.0E+01 1.0E+02 1.0E+03 1.0E+04 0.1 1
10 100 Qsa Frequency, Hz Western US QSA factor Average Qsa Malagnini 2007, N. California Erickson 2004, S. California Erickson 2004, N. California Power (Average Qsa) y = 186.35x0.9933 1.0E+01 1.0E+02 1.0E+03 1.0E+04 0.1 1
10 100 QSA-factor Frequency, Hz CENA QSA - factor Average Q, Pasyanos, 2015 Q, Erickson et al. 2004 Power (Average)
Apparent (Anelastic) Attenuation of Spectral Accelerations 9
Apparent attenuation QSA-quality factor is different from the classical seismological Q(f) determined from FAS of S-, Lg-or coda-waves. From physical point of view, QSA represents the diminution of amplitude in the 5%-damped response spectral amplitudes at certain frequency not necessary associated with one wave, while the seismological Q represents the fraction of energy lost per cycle in a specific wave.
Backbone GS24b 10 Backbone model is a combination of the generic spectral shape, PGA, site amplification and apparent anelastic attenuation functions.
GS24 Site Amplification 11 30site amplification (upper panels)
Additional deep sediments thickness 2.5 correction (middle panels)
Combined 30 and 2.5 site amplification (lower panels)
GS24 12 As compared to the GS24b backbone model, the final GS24 model includes application of style of faulting (3), sediment thickness corrections (4) and also magnitude M, 30 and rupture distance Rrup residual corrections.
Comparing GMM predictions with recordings for M=6.06 13 Comparison of the recorded spectral accelerations (open circles) from earthquakes in a magnitude range of 5.7 to 6.24 and calculated using the GS24, GS24b and GK17 ground motion models SA for the average earthquake of M = 6.06 and average 30 = 414 m/s.
Comparing GMM predictions with recordings for M=7.64 14 Comparison of the recorded spectral accelerations (open circles) from earthquakes in a magnitude range of 7.28 to 7.9 and calculated using the GS24, GS24b and GK17 ground motion models SA for the average earthquake of M = 7.64 and average 30 = 451 m/s.
Final Distance Residuals 15
GS24b, GS24 and GK17 Sigma 16 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 0.01 0.1 1
10 Sigma, log-natural Period, s Sigma GS24_M4_R250 GS24 Within Event PHI GS24 Between Event TAU GK17_M4_R250 GS24b_M4_R250 PGV GS24 PGV within-event PGV between-event PGV GS24b Comparison of the GS24 total (),
within-event (), and between-event
() log-natural sigma to the GK17 and GS24b (backbone) sigma for the third dataset with 4.0 M 7.9 and rupture distances of 0Rrup250 km.
sigma are shown separately beyond 10 s and connected with dash lines.
Results
- The new GS24b backbone and GS24 models are developed for the average RotD50 horizontal component of ground motion from shallow crustal earthquakes in active crustal regions. The models are derived based on a subset of the NGA-West2 dataset enhanced by the data from the three recent 2023 Turkish earthquakes with moment magnitudes 6.3, 7.5 and 7.8 with a total of 13926 data points. We did not use data from earthquakes with magnitudes < 4.0 and we limited the rupture distance range to 400 km.
- We consider the subset of 4 7.9 and Rrup 250 km (M4_R250) of 6046 data points to be the most important from the engineering application point of view since it was created based on the recordings of earthquakes and distances that can potentially create structural damage.
- Similar to GK17, the new models have a bilinear attenuation slope of Rrup
-1 representing geometrical spreading of body waves for the closest 50 km from the fault, and Rrup
-0.5 at larger distances representing geometrical spreading of surface waves. The 50 km fault distance shift in the geometrical spreading is supported by the NGA-West2 data.
- The number of input predictors in the GS24b and GS24 models are limited to a few measurable parameters: moment magnitude, closest distance to fault rupture plane Rrup, time-averaged shear wave velocity in the upper 30 m of the profile 30, style of faulting, apparent anelastic attenuation quality factor,, and sediment thickness depth 2.5.
17
Results (continued)
- The new GS24b global backbone model uses the closed form approximation of the spectral acceleration as a multiplication of the and spectral shape functions. This model can be later adjusted to the specific active crustal region creating partially non-ergodic models.
- The new new ergodic GS24 model is adjusted to best fit NGA-West2 data combined with the three strong 2023 Turkish earthquakes. As compared to the GS24b backbone model, the final GS24 model includes application of style of faulting SoF, sediment thickness corrections (4(2.5)) and also magnitude (),
average shear wave velocity in the upper 30 meters (30 ), and rupture distance (Rrup) residual corrections.
- The GMMs are applicable for earthquakes with 4.0 8.5, at rupture distances from 0 < Rrup 400 km, at sites having 30 in the range from 150 ms to 1500 ms, and for spectral periods of 0.01 10 sec.
- As expected, the GS24 final model performs better than the GS24b and GK17 demonstrating lower standard error and residuals.
- The GS24b and GS24 ground motion models for spectral acceleration and peak ground velocity are developed using MATLAB software.
- We tested the GK17 model against the same set of data and demonstrated acceptable performance with standard error slightly higher than that of the new GS24 model.
18
Reference 19 Technical Letter Report
[TLR-RES-DE-SGSEB-2024-01]
Global GS24 Ground Motion Models for Active Crustal Regions based on Non-Traditional Modeling Approach Date:
September 9, 2024 Prepared by NRC staff:
Vladimir Graizer Scott Stovall Laurel Bauer Structural, Geotechnical, and Seismic Engineering Branch Division of Engineering Office of Nuclear Regulatory Research U.S. Nuclear Regulatory Commission Washington, DC 20555-0001