Source code for openquake.hazardlib.gsim.atkinson_2015

# -*- coding: utf-8 -*-
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"""
Module exports :class:'Atkinson2015'
"""
import numpy as np
# standard acceleration of gravity in m/s**2
from scipy.constants import g


from openquake.hazardlib.gsim.base import GMPE, CoeffsTable
from openquake.hazardlib import const
from openquake.hazardlib.imt import PGA, PGV, SA


[docs]class Atkinson2015(GMPE): """ Implements the Induced Seismicity GMPE of Atkinson (2015) Atkinson, G. A. (2015) Ground-Motion Prediction Equation for Small-to- Moderate Events at Short Hypocentral Distances, with Application to Induced-Seismicity Hazards. Bulletin of the Seismological Society of America. 105(2). """ #: The GMPE is derived from induced earthquakes DEFINED_FOR_TECTONIC_REGION_TYPE = const.TRT.INDUCED #: Supported intensity measure types are peak ground acceleration DEFINED_FOR_INTENSITY_MEASURE_TYPES = set([ PGA, PGV, SA ]) #: Supported intensity measure component is the larger of two components DEFINED_FOR_INTENSITY_MEASURE_COMPONENT = const.IMC.RotD50 #: Supported standard deviation types is total. DEFINED_FOR_STANDARD_DEVIATION_TYPES = set([ const.StdDev.TOTAL, const.StdDev.INTER_EVENT, const.StdDev.INTRA_EVENT ]) #: No required site parameters, the GMPE is derived for B/C site #: amplification factors REQUIRES_SITES_PARAMETERS = set() #: Required rupture parameters are magnitude REQUIRES_RUPTURE_PARAMETERS = {'mag'} #: Required distance measure is hypocentral distance REQUIRES_DISTANCES = {'rhypo'} #: GMPE not tested against independent implementation so raise #: not verified warning non_verified = True
[docs] def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types): """ See :meth:`superclass method <.base.GroundShakingIntensityModel.get_mean_and_stddevs>` for spec of input and result values. """ C = self.COEFFS[imt] imean = (self._get_magnitude_term(C, rup.mag) + self._get_distance_term(C, dists.rhypo, rup.mag)) # Convert mean from cm/s and cm/s/s if imt.name in "SA PGA": mean = np.log((10.0 ** (imean - 2.0)) / g) else: mean = np.log(10.0 ** imean) stddevs = self._get_stddevs(C, len(dists.rhypo), stddev_types) return mean, stddevs
def _get_magnitude_term(self, C, mag): """ Returns the magnitude scaling term """ return C["c0"] + (C["c1"] * mag) + (C["c2"] * (mag ** 2.0)) def _get_distance_term(self, C, rhypo, mag): """ Returns the distance scaling term """ h_eff = self._get_effective_distance(mag) r_val = np.sqrt(rhypo ** 2.0 + h_eff ** 2.0) return C["c3"] * np.log10(r_val) def _get_effective_distance(self, mag): """ Returns the effective distance term in equation 3. This may be overwritten in sub-classes """ h_eff = 10.0 ** (-1.72 + 0.43 * mag) if h_eff > 1.0: return h_eff else: return 1.0 def _get_stddevs(self, C, num_sites, stddev_types): """ Return standard deviations, converting from log10 to log """ stddevs = [] for stddev_type in stddev_types: assert stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES if stddev_type == const.StdDev.TOTAL: stddevs.append( np.log(10.0 ** C["sigma"]) + np.zeros(num_sites)) elif stddev_type == const.StdDev.INTER_EVENT: stddevs.append(np.log(10.0 ** C["tau"]) + np.zeros(num_sites)) elif stddev_type == const.StdDev.INTRA_EVENT: stddevs.append(np.log(10.0 ** C["phi"]) + np.zeros(num_sites)) return stddevs COEFFS = CoeffsTable(sa_damping=5, table=""" IMT c0 c1 c2 c3 phi tau sigma pgv -4.151 1.762 -0.09509 -1.669 0.27 0.19 0.33 pga -2.376 1.818 -0.1153 -1.752 0.28 0.24 0.37 0.0303 -2.283 1.842 -0.1189 -1.785 0.28 0.27 0.39 0.0500 -2.018 1.826 -0.1192 -1.831 0.28 0.30 0.41 0.1000 -1.954 1.830 -0.1185 -1.774 0.29 0.25 0.39 0.2000 -2.266 1.785 -0.1061 -1.657 0.30 0.21 0.37 0.3000 -2.794 1.852 -0.1078 -1.608 0.30 0.19 0.36 0.5000 -3.873 2.060 -0.1212 -1.544 0.29 0.20 0.35 1.0000 -4.081 1.742 -0.07381 -1.481 0.26 0.22 0.34 2.0000 -4.462 1.485 -0.03815 -1.361 0.24 0.23 0.33 3.0303 -3.827 1.060 0.009086 -1.398 0.24 0.22 0.32 5.0000 -4.321 1.080 0.009376 -1.378 0.25 0.18 0.31 """)