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 = set(('mag', )) #: Required distance measure is hypocentral distance REQUIRES_DISTANCES = set(('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 isinstance(imt, (PGA, SA)): 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 -4.198 1.818 -0.1009 -1.721 0.28 0.18 0.33 pga -2.427 1.877 -0.1214 -1.806 0.29 0.24 0.37 0.0303 -2.313 1.840 -0.1119 -1.708 0.29 0.26 0.39 0.0500 -2.337 1.902 -0.1252 -1.838 0.29 0.29 0.41 0.1000 -2.839 1.905 -0.1134 -1.658 0.30 0.25 0.39 0.2000 -3.918 2.112 -0.1266 -1.591 0.31 0.20 0.37 0.3000 -2.076 1.889 -0.1257 -1.886 0.31 0.18 0.36 0.5000 -4.128 1.792 -0.0791 -1.526 0.30 0.19 0.35 1.0000 -2.009 1.890 -0.1248 -1.828 0.27 0.21 0.34 2.0000 -4.503 1.532 -0.0430 -1.404 0.25 0.22 0.33 3.0303 -3.869 1.110 0.0039 -1.447 0.25 0.21 0.33 5.0000 -4.374 1.134 0.0038 -1.426 0.26 0.17 0.31 """)