Difference between revisions of "Goodness of Fit"
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The algorithm computes: | The algorithm computes: | ||
| − | # | + | #PGA, PGV, and PGD; |
#The response spectral acceleration averaged for periods between 0.1 and 10 s (RS) | #The response spectral acceleration averaged for periods between 0.1 and 10 s (RS) | ||
#Spectral acceleration at 16 individual periods used by recent NGA relations (SA16); | #Spectral acceleration at 16 individual periods used by recent NGA relations (SA16); | ||
Revision as of 19:20, 1 April 2011
SCEC computational scientists often need to compare simulation parameters against observed geophysical and seismic observations. We often need to define what parameters we compare and how to evaluate groups of comparisons. Examples of Goodness of Fit in SCEC research includes Broadband Platform development, in the SCEC CVM development, in CISN EEW evaluation, and CSEP short term earthquake forecast testing.
Mayhew and Olsen
Mayhew and Olsen have developed and published the following paper on goodness of fit for ground motion modeling groups.
- Olsen, K.B., and J.E. Mayhew (2010). Goodness-of-fit Criteria for Broadband Synthetic Seismograms, With Application to the 2008 Mw5.4 Chino Hills, CA, Earthquake, Seism. Res. Lett., revised.
- Kim Olsen's Site for Paper Download
The algorithm computes:
- PGA, PGV, and PGD;
- The response spectral acceleration averaged for periods between 0.1 and 10 s (RS)
- Spectral acceleration at 16 individual periods used by recent NGA relations (SA16);
- the Fourier spectrum (smoothed to reduce variance; FS, Equation S6),
- energy duration (DUR);
- cumulative energy (ENER);
- and cross-correlation (Xcor).
- IE ratio is the ratio between the maximum inelastic and elastic displacements plotted against the strength reduction factor R.
Broadband Platform
Broadband Platform has integrated a bias calculation comparing forecast peak ground motion amplitudes against observed peak amplitudes. These bias plots are calculated for validation events for different code bases.
CVM-T
SCEC CVM development involves improving the underlying earth structure model, adding new material databases like geotechnical layer information, and codes for meshing and populating large scale meshes.
