# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2021 GEM Foundation
#
# OpenQuake is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# OpenQuake is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>.
"""
Module exports :class:`bahrampouriEtAl2021IA`,
class:`bahrampouriEtAl2021Asc`,
class:`bahrampouriEtAl2021SSlab`,
class:`bahrampouriEtAl2021SInter`,
"""
import numpy as np
from openquake.hazardlib.gsim.base import GMPE, CoeffsTable
from openquake.hazardlib import const
from openquake.hazardlib.imt import IA
def _compute_magnitude(ctx, C, trt):
"""
Compute the source term described in Eq. 7 for ASC and 9 for subduction
"""
if trt == const.TRT.ACTIVE_SHALLOW_CRUST:
fsource = (C['a1'] + C['a2'] * ctx.mag +
C['a3'] * np.maximum((ctx.mag - C['a4']), 0) +
C['a7'] * np.log((ctx.ztor) + 1))
else:
if trt == const.TRT.SUBDUCTION_INTERFACE:
Finter = 1
elif trt == const.TRT.SUBDUCTION_INTRASLAB:
Finter = 0
fsource = (C['a1'] + C['a2'] * ctx.mag +
C['a3'] * np.maximum((ctx.mag - C['a4']), 0) +
C['a5'] * np.maximum((ctx.mag - C['a6']), 0) +
C['a7'] * np.log((ctx.ztor) + 1) + C['a8'] * Finter)
return fsource
def _get_source_saturation_term(ctx, C):
"""
Compute the near source saturation as described in Eq. 11
"""
h = np.zeros_like(ctx.mag)
h = (C['b9'] + C['b10'] * (ctx.mag - C['b7']) +
C['b11'] * (ctx.mag - C['b7'])**2 +
C['b12'] * (ctx.mag - C['b7'])**3)
before = ctx.mag <= C['b7']
after = ctx.mag > C['b8']
h[before] = C['b5'] + C['b6'] * (ctx.mag[before] - C['b7'])
h[after] = C['b13'] + C['b14'] * (ctx.mag[after] - C['b8'])
return h
def _get_site_term(ctx, C):
"""
compute site scaling as described in Eq.12
Fsite = c1*ln(vs30)
"""
fsite = C['c1'] * np.log(ctx.vs30)
return fsite
def _get_stddevs(C):
sig = C['sig']
tau = C['tau']
phi = np.sqrt(C['phi_ss']**2 + C['phi_s2s']**2)
return sig, tau, phi
def _compute_distance(ctx, C, trt):
"""
Cm is 1 if the path from the source to the site crosses the volcanic
front in Honshu and Hokkaido and 0 otherwise;
CK is 1 if the path from the source to the site crosses the volcanic
front in Kyushu and 0 otherwise;
"""
cm = 0 # temporary
ck = 0 # temporary
rrup_b = ctx.xvf
rrup_f = ctx.rrup - abs(ctx.xvf)
sst = _get_source_saturation_term(ctx, C)
tmp = (10**sst)**2
if trt == const.TRT.ACTIVE_SHALLOW_CRUST:
fpath = (C['b1']*(np.log(np.sqrt((ctx.rrup**2) + tmp))) +
C['b3b'] * rrup_b + C['b3f'] * rrup_f +
C['b4m']*cm + C['b4k']*ck)
else:
if trt == const.TRT.SUBDUCTION_INTERFACE:
Finter = 1
elif trt == const.TRT.SUBDUCTION_INTRASLAB:
Finter = 0
fpath = ((C['b1'] +
C['b2']*Finter) * (np.log(np.sqrt((ctx.rrup**2) + tmp))) +
C['b3b'] * rrup_b + C['b3f'] * rrup_f +
C['b4m']*cm + C['b4k']*ck)
return fpath
def _get_arias_intensity_term(ctx, C, trt):
"""
Implementing Eq. 6
"""
ia_l = (_compute_magnitude(ctx, C, trt) +
_compute_distance(ctx, C, trt) +
_get_site_term(ctx, C))
return ia_l
def _get_arias_intensity_second_term(ctx, C, trt):
"""
This is the second term in Eq. 5
"""
t1 = []
for i, x in enumerate(ctx.vs30):
g = np.exp(C['c3']*(min(ctx.vs30[i], 1100)-280))
t1.append(g)
t2 = np.exp(C['c3']*(1100-280))
tmp = (np.exp(_get_arias_intensity_term(ctx, C, trt))+C['c4'])/C['c4']
t3 = np.log(tmp)
ia_2 = C['c2'] * (t1 - t2) * t3
return ia_2
[docs]class BahrampouriEtAl2021Asc(GMPE):
"""
Implements GMPE by Mahdi Bahrampouri, Adrian Rodriguez-Marek and Russell A
Green developed from the Kiban-Kyoshin network (KiK)-net database. This
GMPE is specifically derived for arias intensity. This GMPE is described in
a paper published in 2021 on Earthquake Spectra, Volume 37, Pg 428-448 and
titled 'Ground motion prediction equations for Arias Intensity using the
Kik-net database'.
"""
#: Supported tectonic region type is active shallow crust
DEFINED_FOR_TECTONIC_REGION_TYPE = const.TRT.ACTIVE_SHALLOW_CRUST
#: Supported intensity measure types are areas intensity
DEFINED_FOR_INTENSITY_MEASURE_TYPES = {IA}
#: Supported intensity measure component is geometric mean
DEFINED_FOR_INTENSITY_MEASURE_COMPONENT = const.IMC.GEOMETRIC_MEAN
#: Supported standard deviation types are inter-event, intra-event
#: and total, see paragraph "Equations for standard deviations", page
#: 1046.
DEFINED_FOR_STANDARD_DEVIATION_TYPES = {
const.StdDev.TOTAL, const.StdDev.INTER_EVENT, const.StdDev.INTRA_EVENT}
#: Required site parameters are Vs30 and xvf
REQUIRES_SITES_PARAMETERS = {'vs30', 'xvf'}
#: Required rupture parameters are magnitude,ztor
REQUIRES_RUPTURE_PARAMETERS = {'mag', 'ztor'}
#: Required distance measures are Rrup (see Table 2,
#: page 1031).
REQUIRES_DISTANCES = {'rrup'}
[docs] def compute(self, ctx: np.recarray, imts, mean, sig, tau, phi):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.compute>`
for spec of input and result values.
"""
trt = self.DEFINED_FOR_TECTONIC_REGION_TYPE
for m, imt in enumerate(imts):
C = self.COEFFS[imt]
# Implements mean model (equation 12)
mean[m] = (_get_arias_intensity_term(ctx, C, trt) +
_get_arias_intensity_second_term(ctx, C, trt))
sig[m], tau[m], phi[m] = _get_stddevs(C)
#: For Ia, coefficients are taken from table 3
COEFFS = CoeffsTable(sa_damping=5, table=""" IMT a1 a2 a3 a4 a7 b1 b3b b3f b4m b4k b5 b6 b7 b8 b9 b10 b11 b12 b13 b14 c1 c2 c3 c4 phi_ss tau phi_s2s sig
ia -4.2777 2.9352 -2.3986 7.0 0.7008 -2.8299 -0.0039 -0.0016 -0.6542 -0.2876 0.7497 0.43 5.744 7.744 0.7497 0.43 -0.0488 -0.08312 1.4147 0.235 -1.1076 -0.3607 -0.0077 0.35 0.761585 0.77617 0.840053 1.374096
""")
[docs]class BahrampouriEtAl2021SInter(GMPE):
"""
Implements GMPE by Mahdi Bahrampouri, Adrian Rodriguez-Marek and Russell A
Green developed from the Kiban-Kyoshin network (KiK)-net database. This
GMPE is specifically derived for arias intensity. This GMPE is described in
a paper published in 2021 on Earthquake Spectra, Volume 37, Pg 428-448 and
titled 'Ground motion prediction equations for Arias Intensity using the
Kik-net database'.
"""
#: Supported tectonic region type is SUBDUCTION INTERFACE, see title!
DEFINED_FOR_TECTONIC_REGION_TYPE = const.TRT.SUBDUCTION_INTERFACE
#: Supported intensity measure types are areas intensity
DEFINED_FOR_INTENSITY_MEASURE_TYPES = {IA}
#: Supported intensity measure component is geometric mean
DEFINED_FOR_INTENSITY_MEASURE_COMPONENT = const.IMC.GEOMETRIC_MEAN
#: Supported standard deviation types are inter-event, intra-event
#: and total, see paragraph "Equations for standard deviations", page
#: 1046.
DEFINED_FOR_STANDARD_DEVIATION_TYPES = {
const.StdDev.TOTAL, const.StdDev.INTER_EVENT, const.StdDev.INTRA_EVENT}
#: Required site parameters are Vs30 and xvf
REQUIRES_SITES_PARAMETERS = {'vs30', 'xvf'}
#: Required rupture parameters are magnitude,ztor
REQUIRES_RUPTURE_PARAMETERS = {'mag', 'ztor'}
#: Required distance measures are Rrup (see Table 2,
#: page 1031).
REQUIRES_DISTANCES = {'rrup'}
[docs] def compute(self, ctx: np.recarray, imts, mean, sig, tau, phi):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.compute>`
for spec of input and result values.
"""
trt = self.DEFINED_FOR_TECTONIC_REGION_TYPE
for m, imt in enumerate(imts):
C = self.COEFFS[imt]
# Implements mean model (equation 12)
mean[m] = (_get_arias_intensity_term(ctx, C, trt) +
_get_arias_intensity_second_term(ctx, C, trt))
sig[m], tau[m], phi[m] = _get_stddevs(C)
#: For Ia, coefficients are taken from table 3
COEFFS = CoeffsTable(sa_damping=5, table=""" IMT a1 a2 a3 a4 a5 a6 a7 a8 b1 b2 b3b b3f b4m b4k b5 b6 b7 b8 b9 b10 b11 b12 b13 b14 c1 c2 c3 c4 phi_ss tau phi_s2s sig
ia -0.6169 2.5269 1.531 6.5 -3.2923 7.5 0.5462 0.6249 -2.7534 -0.2816 -0.0044 -0.003 -1.2608 -0.2992 0.7497 0.43 5.744 7.744 0.7497 0.43 -0.0488 -0.08312 1.4147 0.235 -1.3763 -0.1003 -0.0069 0.356 0.73761 0.92179 1.12747 1.632469
""")
[docs]class BahrampouriEtAl2021SSlab(GMPE):
"""
Implements GMPE by Mahdi Bahrampouri, Adrian Rodriguez-Marek and Russell A
Green developed from the Kiban-Kyoshin network (KiK)-net database. This
GMPE is specifically derived for arias intensity. This GMPE is described in
a paper published in 2021 on Earthquake Spectra, Volume 37, Pg 428-448 and
titled 'Ground motion prediction equations for Arias Intensity using the
Kik-net database'.
"""
#: Supported tectonic region type is SUBDUCTION INTERSLAB, see title!
DEFINED_FOR_TECTONIC_REGION_TYPE = const.TRT.SUBDUCTION_INTRASLAB
#: Supported intensity measure types are areas intensity
DEFINED_FOR_INTENSITY_MEASURE_TYPES = {IA}
#: Supported intensity measure component is geometric mean
DEFINED_FOR_INTENSITY_MEASURE_COMPONENT = const.IMC.GEOMETRIC_MEAN
#: Supported standard deviation types are inter-event, intra-event
#: and total, see paragraph "Equations for standard deviations", page
#: 1046.
DEFINED_FOR_STANDARD_DEVIATION_TYPES = {
const.StdDev.TOTAL, const.StdDev.INTER_EVENT, const.StdDev.INTRA_EVENT}
#: Required site parameters are Vs30 and xvf
REQUIRES_SITES_PARAMETERS = {'vs30', 'xvf'}
#: Required rupture parameters are magnitude,ztor
REQUIRES_RUPTURE_PARAMETERS = {'mag', 'ztor'}
#: Required distance measures are Rrup (see Table 2,
#: page 1031).
REQUIRES_DISTANCES = {'rrup'}
[docs] def compute(self, ctx: np.recarray, imts, mean, sig, tau, phi):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.compute>`
for spec of input and result values.
"""
trt = self.DEFINED_FOR_TECTONIC_REGION_TYPE
for m, imt in enumerate(imts):
C = self.COEFFS[imt]
# Implements mean model (equation 12)
mean[m] = (_get_arias_intensity_term(ctx, C, trt) +
_get_arias_intensity_second_term(ctx, C, trt))
sig[m], tau[m], phi[m] = _get_stddevs(C)
#: For Ia, coefficients are taken from table 3
COEFFS = CoeffsTable(sa_damping=5, table=""" IMT a1 a2 a3 a4 a5 a6 a7 a8 b1 b2 b3b b3f b4m b4k b5 b6 b7 b8 b9 b10 b11 b12 b13 b14 c1 c2 c3 c4 phi_ss tau phi_s2s sig
ia -0.6169 2.5269 1.531 6.5 -3.2923 7.5 0.5462 0.6249 -2.7534 -0.2816 -0.0044 -0.003 -1.2608 -0.2992 0.7497 0.43 5.744 7.744 0.7497 0.43 -0.0488 -0.08312 1.4147 0.235 -1.3763 -0.1003 -0.0069 0.356 0.73761 0.92179 1.12747 1.632469
""")