Source code for openquake.hazardlib.gsim.akkar_2014

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
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"""
Module exports :class:`AkkarEtAlRjb2014`
               :class:`AkkarEtAlRepi2014`
               :class:`AkkarEtAlRhypo2014`.
"""
import numpy as np
from openquake.baselib.general import CallableDict
from openquake.hazardlib.gsim.base import GMPE, CoeffsTable
from openquake.hazardlib import const
from openquake.hazardlib.imt import PGA, PGV, SA


def _compute_faulting_style_term(C, rake):
    """
    Compute and return fifth and sixth terms in equations (2a)
    and (2b), pages 20.
    """
    Fn = (rake > -135.0) & (rake < -45.0)
    Fr = (rake > 45.0) & (rake < 135.0)

    return C['a8'] * Fn + C['a9'] * Fr


def _compute_linear_magnitude_term(C, c1, mag):
    """
    Compute and return second term in equations (2a)
    and (2b), page 20.
    """
    return np.where(mag <= c1, C['a2'] * (mag - c1), C['a7'] * (mag - c1))


_compute_logarithmic_distance_term = CallableDict()


@_compute_logarithmic_distance_term.add("rjb")
def _compute_logarithmic_distance_term_1(kind, C, c1, ctx):
    """
    Compute and return fourth term in equations (2a)
    and (2b), page 20.
    """
    return (C['a4'] + C['a5'] * (ctx.mag - c1)) * np.log(
        np.sqrt(ctx.rjb ** 2 + C['a6'] ** 2))


@_compute_logarithmic_distance_term.add("repi")
def _compute_logarithmic_distance_term_2(kind, C, c1, ctx):
    """
    Compute and return fourth term in equations (2a)
    and (2b), page 20.
    """
    return (C['a4'] + C['a5'] * (ctx.mag - c1)) * np.log(
        np.sqrt(ctx.repi ** 2 + C['a6'] ** 2))


@_compute_logarithmic_distance_term.add("rhypo")
def _compute_logarithmic_distance_term_3(kind, C, c1, ctx):
    """
    Compute and return fourth term in equations (2a)
    and (2b), page 20.
    """
    return (C['a4'] + C['a5'] * (ctx.mag - c1)) * np.log(
        np.sqrt(ctx.rhypo ** 2 + C['a6'] ** 2))


def _compute_mean(kind, C, c1, ctx):
    """
    Compute and return mean value without site conditions,
    that is equations (1a) and (1b), p.2981-2982.
    """
    mean = (C['a1'] +
            _compute_linear_magnitude_term(C, c1, ctx.mag) +
            _compute_quadratic_magnitude_term(C, ctx.mag) +
            _compute_logarithmic_distance_term(kind, C, c1, ctx) +
            _compute_faulting_style_term(C, ctx.rake))
    return mean


def _compute_non_linear_term(C, pga_only, ctx):
    """
    Compute non-linear term, equation (3a) to (3c), page 20.
    """
    Vref = 750.0
    Vcon = 1000.0
    lnS = np.zeros_like(ctx.vs30)

    # equation (3a)
    idx = ctx.vs30 < Vref
    lnS[idx] = (
        C['b1'] * np.log(ctx.vs30[idx] / Vref) +
        C['b2'] * np.log(
            (pga_only[idx] + C['c'] * (ctx.vs30[idx] / Vref) ** C['n']) /
            ((pga_only[idx] + C['c']) * (ctx.vs30[idx] / Vref) ** C['n'])
        ))

    # equation (3b)
    idx = (ctx.vs30 >= Vref) & (ctx.vs30 <= Vcon)
    lnS[idx] = C['b1'] * np.log(ctx.vs30[idx] / Vref)

    # equation (3c)
    idx = ctx.vs30 > Vcon
    lnS[idx] = C['b1'] * np.log(Vcon / Vref)

    return lnS


def _compute_quadratic_magnitude_term(C, mag):
    """
    Compute and return third term in equations (2a)
    and (2b), page  20.
    """
    return C['a3'] * (8.5 - mag) ** 2


[docs]class AkkarEtAlRjb2014(GMPE): """ Implements GMPE developed by S. Akkar, M. A. Sandikkaya, and J. J. Bommer as published in "Empirical Ground-Motion Models for Point- and Extended- Source Crustal Earthquake Scenarios in Europe and the Middle East", Bulletin of Earthquake Engineering (2014), 12(1): 359 - 387 The class implements the equations for Joyner-Boore distance and based on manuscript provided by the original authors. """ #: The supported tectonic region type is active shallow crust because #: the equations have been developed for "all seismically- active regions #: bordering the Mediterranean Sea and extending to the Middle East", see #: section 'A New Generation of European Ground-Motion Models', page 4. DEFINED_FOR_TECTONIC_REGION_TYPE = const.TRT.ACTIVE_SHALLOW_CRUST #: The supported intensity measure types are PGA, PGV, and SA, see table #: 4.a, pages 22-23 DEFINED_FOR_INTENSITY_MEASURE_TYPES = {PGA, PGV, SA} #: The supported intensity measure component is 'average horizontal', see #: section 'A New Generation of European Ground-Motion Models', page 8 DEFINED_FOR_INTENSITY_MEASURE_COMPONENT = const.IMC.AVERAGE_HORIZONTAL #: The supported standard deviations are total, inter and intra event, see #: table 4.a, pages 22-23 DEFINED_FOR_STANDARD_DEVIATION_TYPES = { const.StdDev.TOTAL, const.StdDev.INTER_EVENT, const.StdDev.INTRA_EVENT} #: The required site parameter is vs30, see equation 1, page 20. REQUIRES_SITES_PARAMETERS = {'vs30'} #: The required rupture parameters are rake and magnitude, see equation 1, #: page 20. REQUIRES_RUPTURE_PARAMETERS = {'rake', 'mag'} #: The required distance parameter is 'Joyner-Boore' distance, because #: coefficients in table 4.a, pages 22-23, are used. REQUIRES_DISTANCES = {'rjb'} DEFINED_FOR_REFERENCE_VELOCITY = 800 def __init__(self, adjustment_factor=1.0, **kwargs): super().__init__(adjustment_factor=adjustment_factor, **kwargs) [self.kind] = self.REQUIRES_DISTANCES self.adjustment_factor = np.log(adjustment_factor)
[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. Implement equation 1, page 20. """ # compute median PGA on rock, needed to compute non-linear site # amplification C_pga = self.COEFFS[PGA()] median_pga = np.exp(_compute_mean(self.kind, C_pga, self.c1, ctx)) for m, imt in enumerate(imts): # compute mean value by adding nonlinear site amplification terms C = self.COEFFS[imt] mean[m] = (_compute_mean(self.kind, C, self.c1, ctx) + _compute_non_linear_term(C, median_pga, ctx)) mean[m] += self.adjustment_factor sig[m] = np.sqrt(C['sigma'] ** 2 + C['tau'] ** 2) tau[m] = C['tau'] phi[m] = C['sigma']
#: c1 is the reference magnitude, fixed to 6.75Mw (which happens to be the #: same value used in Boore and Atkinson, 2008) #: see paragraph 'Functional Form of Predictive Equations and Regressions', #: page 21 c1 = 6.75 #: Coefficient table (from Table 3 and 4a, page 22) #: Table 4.a: Period-dependent regression coefficients of the RJB #: ground-motion model #: sigma is the 'intra-event' standard deviation, while tau is the #: 'inter-event' standard deviation COEFFS = CoeffsTable(sa_damping=5, table="""\ IMT a1 a2 a3 a4 a5 a6 a7 a8 a9 c1 Vcon Vref c n b1 b2 sigma tau pga 1.85329 0.0029 -0.02807 -1.23452 0.2529 7.5 -0.5096 -0.1091 0.0937 6.75 1000 750 2.5 3.2 -0.41997 -0.28846 0.6201 0.3501 0.010 1.87032 0.0029 -0.02740 -1.23698 0.2529 7.5 -0.5096 -0.1115 0.0953 6.75 1000 750 2.5 3.2 -0.41729 -0.28685 0.6215 0.3526 0.020 1.95279 0.0029 -0.02715 -1.25363 0.2529 7.5 -0.5096 -0.1040 0.1029 6.75 1000 750 2.5 3.2 -0.39998 -0.28241 0.6266 0.3555 0.030 2.07006 0.0029 -0.02403 -1.27525 0.2529 7.5 -0.5096 -0.0973 0.1148 6.75 1000 750 2.5 3.2 -0.34799 -0.26842 0.6410 0.3565 0.040 2.20452 0.0029 -0.01797 -1.30123 0.2529 7.5 -0.5096 -0.0884 0.1073 6.75 1000 750 2.5 3.2 -0.27572 -0.24759 0.6534 0.3484 0.050 2.35413 0.0029 -0.01248 -1.32632 0.2529 7.5 -0.5096 -0.0853 0.1052 6.75 1000 750 2.5 3.2 -0.21231 -0.22385 0.6622 0.3551 0.075 2.63078 0.0029 -0.00532 -1.35722 0.2529 7.5 -0.5096 -0.0779 0.0837 6.75 1000 750 2.5 3.2 -0.14427 -0.17525 0.6626 0.3759 0.100 2.85412 0.0029 -0.00925 -1.38182 0.2529 7.5 -0.5096 -0.0749 0.0761 6.75 1000 750 2.5 3.2 -0.27064 -0.29293 0.6670 0.4067 0.110 2.89772 0.0029 -0.01062 -1.38345 0.2529 7.5 -0.5096 -0.0704 0.0707 6.75 1000 750 2.5 3.2 -0.31025 -0.31837 0.6712 0.4059 0.120 2.92748 0.0029 -0.01291 -1.37997 0.2529 7.5 -0.5096 -0.0604 0.0653 6.75 1000 750 2.5 3.2 -0.34796 -0.33860 0.6768 0.4022 0.130 2.95162 0.0029 -0.01592 -1.37627 0.2529 7.5 -0.5096 -0.0490 0.0617 6.75 1000 750 2.5 3.2 -0.39668 -0.36646 0.6789 0.4017 0.140 2.96299 0.0029 -0.01866 -1.37155 0.2529 7.5 -0.5096 -0.0377 0.0581 6.75 1000 750 2.5 3.2 -0.43996 -0.38417 0.6822 0.3945 0.150 2.96622 0.0029 -0.02193 -1.36460 0.2529 7.5 -0.5096 -0.0265 0.0545 6.75 1000 750 2.5 3.2 -0.48313 -0.39551 0.6796 0.3893 0.160 2.93166 0.0029 -0.02429 -1.35074 0.2529 7.5 -0.5096 -0.0194 0.0509 6.75 1000 750 2.5 3.2 -0.52431 -0.40869 0.6762 0.3928 0.170 2.88988 0.0029 -0.02712 -1.33454 0.2529 7.5 -0.5096 -0.0125 0.0507 6.75 1000 750 2.5 3.2 -0.55680 -0.41528 0.6723 0.396 0.180 2.84627 0.0029 -0.03003 -1.31959 0.2529 7.5 -0.5096 -0.0056 0.0502 6.75 1000 750 2.5 3.2 -0.58922 -0.42717 0.6694 0.396 0.190 2.79778 0.0029 -0.03300 -1.30450 0.2529 7.5 -0.5096 0.00000 0.0497 6.75 1000 750 2.5 3.2 -0.62635 -0.44130 0.6647 0.3932 0.200 2.73872 0.0029 -0.03462 -1.28877 0.2529 7.5 -0.5096 0.00000 0.0493 6.75 1000 750 2.5 3.2 -0.65315 -0.44644 0.6645 0.3842 0.220 2.63479 0.0029 -0.03789 -1.26125 0.2529 7.5 -0.5096 0.00000 0.0488 6.75 1000 750 2.5 3.2 -0.68711 -0.44872 0.6600 0.3887 0.240 2.53886 0.0029 -0.04173 -1.23600 0.2529 7.5 -0.5096 0.00000 0.0483 6.75 1000 750 2.5 3.2 -0.72744 -0.46341 0.6651 0.3792 0.260 2.48747 0.0029 -0.04768 -1.21882 0.2529 7.5 -0.5096 0.00000 0.0478 6.75 1000 750 2.5 3.2 -0.77335 -0.48705 0.6650 0.3754 0.280 2.38739 0.0029 -0.05178 -1.19543 0.2529 7.5 -0.5096 0.00000 0.0474 6.75 1000 750 2.5 3.2 -0.80508 -0.47334 0.6590 0.3757 0.300 2.30150 0.0029 -0.05672 -1.17072 0.2529 7.5 -0.5096 0.00000 0.0469 6.75 1000 750 2.5 3.2 -0.82609 -0.45730 0.6599 0.3816 0.320 2.17298 0.0029 -0.06015 -1.13847 0.2529 7.5 -0.5096 0.00000 0.0464 6.75 1000 750 2.5 3.2 -0.84080 -0.44267 0.6654 0.3866 0.340 2.07474 0.0029 -0.06508 -1.11131 0.2529 7.5 -0.5096 0.00000 0.0459 6.75 1000 750 2.5 3.2 -0.86251 -0.43888 0.6651 0.3881 0.360 2.01953 0.0029 -0.06974 -1.09484 0.2529 7.5 -0.5096 0.00000 0.0459 6.75 1000 750 2.5 3.2 -0.87479 -0.43820 0.6662 0.3924 0.380 1.95078 0.0029 -0.07346 -1.07812 0.2529 7.5 -0.5096 0.00000 0.0429 6.75 1000 750 2.5 3.2 -0.88522 -0.43678 0.6698 0.3945 0.400 1.89372 0.0029 -0.07684 -1.06530 0.2529 7.5 -0.5096 0.00000 0.0400 6.75 1000 750 2.5 3.2 -0.89517 -0.43008 0.6697 0.3962 0.420 1.83717 0.0029 -0.08010 -1.05451 0.2529 7.5 -0.5096 0.00000 0.0374 6.75 1000 750 2.5 3.2 -0.90875 -0.42190 0.6696 0.389 0.440 1.77528 0.0029 -0.08296 -1.04332 0.2529 7.5 -0.5096 0.00000 0.0349 6.75 1000 750 2.5 3.2 -0.91922 -0.40903 0.6641 0.3929 0.460 1.73155 0.0029 -0.08623 -1.03572 0.2529 7.5 -0.5096 0.00000 0.0323 6.75 1000 750 2.5 3.2 -0.92670 -0.39442 0.6575 0.4009 0.480 1.70132 0.0029 -0.09070 -1.02724 0.2529 7.5 -0.5096 0.00000 0.0297 6.75 1000 750 2.5 3.2 -0.93720 -0.38462 0.6540 0.4022 0.500 1.67127 0.0029 -0.09490 -1.01909 0.2529 7.5 -0.5096 0.00000 0.0271 6.75 1000 750 2.5 3.2 -0.94614 -0.37408 0.6512 0.4021 0.550 1.53838 0.0029 -0.10275 -0.99351 0.2529 7.5 -0.5096 0.00000 0.0245 6.75 1000 750 2.5 3.2 -0.96564 -0.35582 0.6570 0.4057 0.600 1.37505 0.0029 -0.10747 -0.96429 0.2529 7.5 -0.5096 0.00000 0.0219 6.75 1000 750 2.5 3.2 -0.98499 -0.34053 0.6630 0.406 0.650 1.21156 0.0029 -0.11262 -0.93347 0.2529 7.5 -0.5096 0.00000 0.0193 6.75 1000 750 2.5 3.2 -0.99733 -0.30949 0.6652 0.4124 0.700 1.09262 0.0029 -0.11835 -0.91162 0.2529 7.5 -0.5096 0.00000 0.0167 6.75 1000 750 2.5 3.2 -1.00469 -0.28772 0.6696 0.4135 0.750 0.95211 0.0029 -0.12347 -0.88393 0.2529 7.5 -0.5096 0.00000 0.0141 6.75 1000 750 2.5 3.2 -1.00786 -0.28957 0.6744 0.4043 0.800 0.85227 0.0029 -0.12678 -0.86884 0.2529 7.5 -0.5096 0.00000 0.0115 6.75 1000 750 2.5 3.2 -1.00606 -0.28555 0.6716 0.3974 0.850 0.76564 0.0029 -0.13133 -0.85442 0.2529 7.5 -0.5096 0.00000 0.0089 6.75 1000 750 2.5 3.2 -1.01093 -0.28364 0.6713 0.3971 0.900 0.66856 0.0029 -0.13551 -0.83929 0.2529 7.5 -0.5096 0.00000 0.0062 6.75 1000 750 2.5 3.2 -1.01576 -0.28037 0.6738 0.3986 0.950 0.58739 0.0029 -0.13957 -0.82668 0.2529 7.5 -0.5096 0.00000 0.0016 6.75 1000 750 2.5 3.2 -1.01353 -0.28390 0.6767 0.3949 1.000 0.52349 0.0029 -0.14345 -0.81838 0.2529 7.5 -0.5096 0.00000 0.0000 6.75 1000 750 2.5 3.2 -1.01331 -0.28702 0.6787 0.3943 1.100 0.37680 0.0029 -0.15051 -0.79691 0.2529 7.5 -0.5096 0.00000 0.0000 6.75 1000 750 2.5 3.2 -1.01240 -0.27669 0.6912 0.3806 1.200 0.23251 0.0029 -0.15527 -0.77813 0.2529 7.5 -0.5096 0.00000 0.0000 6.75 1000 750 2.5 3.2 -1.00489 -0.27538 0.7015 0.3802 1.300 0.10481 0.0029 -0.16106 -0.75888 0.2529 7.5 -0.5096 0.00000 0.0000 6.75 1000 750 2.5 3.2 -0.98876 -0.25008 0.7017 0.3803 1.400 0.00887 0.0029 -0.16654 -0.74871 0.2529 7.5 -0.5096 0.00000 0.0000 6.75 1000 750 2.5 3.2 -0.97760 -0.23508 0.7141 0.3766 1.500 -0.01867 0.0029 -0.17187 -0.75751 0.2529 7.5 -0.5096 0.00000 0.0000 6.75 1000 750 2.5 3.2 -0.98071 -0.24695 0.7164 0.3799 1.600 -0.09960 0.0029 -0.17728 -0.74823 0.2529 7.5 -0.5096 0.00000 0.0000 6.75 1000 750 2.5 3.2 -0.96369 -0.22870 0.7198 0.3817 1.700 -0.21166 0.0029 -0.17908 -0.73766 0.2529 7.5 -0.5096 0.00000 0.0000 6.75 1000 750 2.5 3.2 -0.94634 -0.21655 0.7226 0.3724 1.800 -0.27300 0.0029 -0.18438 -0.72996 0.2529 7.5 -0.5096 0.00000 -0.003 6.75 1000 750 2.5 3.2 -0.93606 -0.20302 0.7241 0.371 1.900 -0.35366 0.0029 -0.18741 -0.72279 0.2529 7.5 -0.5096 0.00000 -0.006 6.75 1000 750 2.5 3.2 -0.91408 -0.18228 0.7266 0.3745 2.000 -0.42891 0.0029 -0.19029 -0.72033 0.2529 7.5 -0.5096 0.00000 -0.009 6.75 1000 750 2.5 3.2 -0.91007 -0.17336 0.7254 0.3717 2.200 -0.55307 0.0029 -0.19683 -0.71662 0.2529 7.5 -0.5096 0.00000 -0.0141 6.75 1000 750 2.5 3.2 -0.89376 -0.15463 0.7207 0.3758 2.400 -0.67806 0.0029 -0.20339 -0.70452 0.2529 7.5 -0.5096 0.00000 -0.0284 6.75 1000 750 2.5 3.2 -0.87052 -0.13181 0.7144 0.3973 2.600 -0.80494 0.0029 -0.20703 -0.69691 0.2529 7.5 -0.5096 0.00000 -0.0408 6.75 1000 750 2.5 3.2 -0.85889 -0.14066 0.7122 0.4001 2.800 -0.91278 0.0029 -0.21074 -0.69560 0.2529 7.5 -0.5096 0.00000 -0.0534 6.75 1000 750 2.5 3.2 -0.86106 -0.13882 0.7129 0.4025 3.000 -1.05642 0.0029 -0.21392 -0.69085 0.2529 7.5 -0.5096 0.00000 -0.0683 6.75 1000 750 2.5 3.2 -0.85793 -0.13336 0.6997 0.4046 3.200 -1.17715 0.0029 -0.21361 -0.67711 0.2529 7.5 -0.5096 0.00000 -0.078 6.75 1000 750 2.5 3.2 -0.82094 -0.13770 0.6820 0.4194 3.400 -1.22091 0.0029 -0.21951 -0.68177 0.2529 7.5 -0.5096 0.00000 -0.0943 6.75 1000 750 2.5 3.2 -0.84449 -0.15337 0.6682 0.3971 3.600 -1.34547 0.0029 -0.22724 -0.65918 0.2529 7.5 -0.5096 0.00000 -0.1278 6.75 1000 750 2.5 3.2 -0.83216 -0.10884 0.6508 0.4211 3.800 -1.39790 0.0029 -0.23180 -0.65298 0.2529 7.5 -0.5096 0.00000 -0.1744 6.75 1000 750 2.5 3.2 -0.79216 -0.08884 0.6389 0.415 4.000 -1.37536 0.0029 -0.23848 -0.66482 0.2529 7.5 -0.5096 0.00000 -0.2231 6.75 1000 750 2.5 3.2 -0.75645 -0.07749 0.6196 0.3566 pgv 5.61201 0.0029 -0.09980 -0.98388 0.2529 7.5 -0.5096 -0.0616 0.0630 6.75 1000 750 2.5 3.2 -0.72057 -0.19688 0.6014 0.3311 """)
[docs]class AkkarEtAlRepi2014(AkkarEtAlRjb2014): """ Implements GMPE developed by S. Akkar, M. A. Sandikkaya, and J. J. Bommer as published in "Empirical Ground-Motion Models for Point- and Extended- Source Crustal Earthquake Scenarios in Europe and the Middle East", Bullettin of Earthquake Engineering (2014). The class implements the equations for epicentral distance and based on manuscript provided by the original authors. """ REQUIRES_DISTANCES = {'repi'} COEFFS = CoeffsTable(sa_damping=5, table="""\ IMT a1 a2 a3 a4 a5 a6 a7 a8 a9 c1 Vcon Vref c n b1 b2 sigma tau pga 2.52977 0.0029 -0.05496 -1.31001 0.2529 7.5 -0.5096 -0.1091 0.0937 6.75 1000 750 2.5 3.2 -0.41997 -0.28846 0.6375 0.3581 pgv 6.13498 0.0029 -0.12091 -1.04013 0.2529 7.5 -0.5096 -0.0616 0.0630 6.75 1000 750 2.5 3.2 -0.72057 -0.19688 0.6143 0.3485 0.010 2.54832 0.0029 -0.05434 -1.31268 0.2529 7.5 -0.5096 -0.1115 0.0953 6.75 1000 750 2.5 3.2 -0.41729 -0.28685 0.6389 0.3607 0.020 2.64420 0.0029 -0.05452 -1.33135 0.2529 7.5 -0.5096 -0.1040 0.1029 6.75 1000 750 2.5 3.2 -0.39998 -0.28241 0.6434 0.3615 0.030 2.77723 0.0029 -0.05196 -1.35509 0.2529 7.5 -0.5096 -0.0973 0.1148 6.75 1000 750 2.5 3.2 -0.34799 -0.26842 0.6569 0.3617 0.040 2.92666 0.0029 -0.04657 -1.38259 0.2529 7.5 -0.5096 -0.0884 0.1073 6.75 1000 750 2.5 3.2 -0.27572 -0.24759 0.6693 0.3530 0.050 3.09355 0.0029 -0.04168 -1.41008 0.2529 7.5 -0.5096 -0.0853 0.1052 6.75 1000 750 2.5 3.2 -0.21231 -0.22385 0.6773 0.3612 0.075 3.38462 0.0029 -0.03506 -1.44268 0.2529 7.5 -0.5096 -0.0779 0.0837 6.75 1000 750 2.5 3.2 -0.14427 -0.17525 0.6791 0.3853 0.100 3.61906 0.0029 -0.03936 -1.46870 0.2529 7.5 -0.5096 -0.0749 0.0761 6.75 1000 750 2.5 3.2 -0.27064 -0.29293 0.6851 0.4160 0.110 3.66537 0.0029 -0.04081 -1.47079 0.2529 7.5 -0.5096 -0.0704 0.0707 6.75 1000 750 2.5 3.2 -0.31025 -0.31837 0.6884 0.4163 0.120 3.68544 0.0029 -0.04295 -1.46520 0.2529 7.5 -0.5096 -0.0604 0.0653 6.75 1000 750 2.5 3.2 -0.34796 -0.33860 0.6960 0.4118 0.130 3.70155 0.0029 -0.04581 -1.45986 0.2529 7.5 -0.5096 -0.0490 0.0617 6.75 1000 750 2.5 3.2 -0.39668 -0.36646 0.6997 0.4102 0.140 3.70871 0.0029 -0.04848 -1.45433 0.2529 7.5 -0.5096 -0.0377 0.0581 6.75 1000 750 2.5 3.2 -0.43996 -0.38417 0.7032 0.4028 0.150 3.70477 0.0029 -0.05156 -1.44613 0.2529 7.5 -0.5096 -0.0265 0.0545 6.75 1000 750 2.5 3.2 -0.48313 -0.39551 0.7011 0.3978 0.160 3.65565 0.0029 -0.05350 -1.42989 0.2529 7.5 -0.5096 -0.0194 0.0509 6.75 1000 750 2.5 3.2 -0.52431 -0.40869 0.6997 0.3989 0.170 3.59764 0.0029 -0.05583 -1.41110 0.2529 7.5 -0.5096 -0.0125 0.0507 6.75 1000 750 2.5 3.2 -0.55680 -0.41528 0.6970 0.4030 0.180 3.53732 0.0029 -0.05830 -1.39329 0.2529 7.5 -0.5096 -0.0056 0.0502 6.75 1000 750 2.5 3.2 -0.58922 -0.42717 0.6956 0.4041 0.190 3.47722 0.0029 -0.06090 -1.37648 0.2529 7.5 -0.5096 0.0000 0.0497 6.75 1000 750 2.5 3.2 -0.62635 -0.44130 0.6915 0.4017 0.200 3.40112 0.0029 -0.06210 -1.35770 0.2529 7.5 -0.5096 0.0000 0.0493 6.75 1000 750 2.5 3.2 -0.65315 -0.44644 0.6922 0.3965 0.220 3.27214 0.0029 -0.06461 -1.32624 0.2529 7.5 -0.5096 0.0000 0.0488 6.75 1000 750 2.5 3.2 -0.68711 -0.44872 0.6893 0.4005 0.240 3.15842 0.0029 -0.06791 -1.29833 0.2529 7.5 -0.5096 0.0000 0.0483 6.75 1000 750 2.5 3.2 -0.72744 -0.46341 0.6942 0.3919 0.260 3.09498 0.0029 -0.07344 -1.27945 0.2529 7.5 -0.5096 0.0000 0.0478 6.75 1000 750 2.5 3.2 -0.77335 -0.48705 0.6938 0.3898 0.280 2.98090 0.0029 -0.07698 -1.25442 0.2529 7.5 -0.5096 0.0000 0.0474 6.75 1000 750 2.5 3.2 -0.80508 -0.47334 0.6877 0.3883 0.300 2.87449 0.0029 -0.08126 -1.22665 0.2529 7.5 -0.5096 0.0000 0.0469 6.75 1000 750 2.5 3.2 -0.82609 -0.45730 0.6897 0.3894 0.320 2.72364 0.0029 -0.08387 -1.19143 0.2529 7.5 -0.5096 0.0000 0.0464 6.75 1000 750 2.5 3.2 -0.84080 -0.44267 0.6947 0.3941 0.340 2.60904 0.0029 -0.08816 -1.16231 0.2529 7.5 -0.5096 0.0000 0.0459 6.75 1000 750 2.5 3.2 -0.86251 -0.43888 0.6939 0.3937 0.360 2.54266 0.0029 -0.09239 -1.14444 0.2529 7.5 -0.5096 0.0000 0.0459 6.75 1000 750 2.5 3.2 -0.87479 -0.43820 0.6945 0.3997 0.380 2.46615 0.0029 -0.09576 -1.12700 0.2529 7.5 -0.5096 0.0000 0.0429 6.75 1000 750 2.5 3.2 -0.88522 -0.43678 0.6971 0.4012 0.400 2.40119 0.0029 -0.09885 -1.11318 0.2529 7.5 -0.5096 0.0000 0.0400 6.75 1000 750 2.5 3.2 -0.89517 -0.43008 0.6971 0.4012 0.420 2.34540 0.0029 -0.10198 -1.10318 0.2529 7.5 -0.5096 0.0000 0.0374 6.75 1000 750 2.5 3.2 -0.90875 -0.42190 0.6955 0.3946 0.440 2.28213 0.0029 -0.10464 -1.09241 0.2529 7.5 -0.5096 0.0000 0.0349 6.75 1000 750 2.5 3.2 -0.91922 -0.40903 0.6891 0.3985 0.460 2.23440 0.0029 -0.10771 -1.08445 0.2529 7.5 -0.5096 0.0000 0.0323 6.75 1000 750 2.5 3.2 -0.92670 -0.39442 0.6825 0.4056 0.480 2.20123 0.0029 -0.11199 -1.07592 0.2529 7.5 -0.5096 0.0000 0.0297 6.75 1000 750 2.5 3.2 -0.93720 -0.38462 0.6785 0.4068 0.500 2.16953 0.0029 -0.11604 -1.06795 0.2529 7.5 -0.5096 0.0000 0.0271 6.75 1000 750 2.5 3.2 -0.94614 -0.37408 0.6751 0.4065 0.550 2.03012 0.0029 -0.12344 -1.04242 0.2529 7.5 -0.5096 0.0000 0.0245 6.75 1000 750 2.5 3.2 -0.96564 -0.35582 0.6788 0.4087 0.600 1.84644 0.0029 -0.12745 -1.01046 0.2529 7.5 -0.5096 0.0000 0.0219 6.75 1000 750 2.5 3.2 -0.98499 -0.34053 0.6845 0.4085 0.650 1.66760 0.0029 -0.13195 -0.97801 0.2529 7.5 -0.5096 0.0000 0.0193 6.75 1000 750 2.5 3.2 -0.99733 -0.30949 0.6857 0.4128 0.700 1.53432 0.0029 -0.13715 -0.95428 0.2529 7.5 -0.5096 0.0000 0.0167 6.75 1000 750 2.5 3.2 -1.00469 -0.28772 0.6902 0.4101 0.750 1.38296 0.0029 -0.14169 -0.92585 0.2529 7.5 -0.5096 0.0000 0.0141 6.75 1000 750 2.5 3.2 -1.00786 -0.28957 0.6937 0.4011 0.800 1.28662 0.0029 -0.14485 -0.91241 0.2529 7.5 -0.5096 0.0000 0.0115 6.75 1000 750 2.5 3.2 -1.00606 -0.28555 0.6884 0.3962 0.850 1.20114 0.0029 -0.14922 -0.89909 0.2529 7.5 -0.5096 0.0000 0.0089 6.75 1000 750 2.5 3.2 -1.01093 -0.28364 0.6866 0.3951 0.900 1.09991 0.0029 -0.15320 -0.88377 0.2529 7.5 -0.5096 0.0000 0.0062 6.75 1000 750 2.5 3.2 -1.01576 -0.28037 0.6881 0.3979 0.950 1.01256 0.0029 -0.15700 -0.87050 0.2529 7.5 -0.5096 0.0000 0.0016 6.75 1000 750 2.5 3.2 -1.01353 -0.28390 0.6904 0.3955 1.000 0.94162 0.0029 -0.16069 -0.86109 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -1.01331 -0.28702 0.6922 0.3965 1.100 0.78017 0.0029 -0.16727 -0.83743 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -1.01240 -0.27669 0.7047 0.3819 1.200 0.63219 0.0029 -0.17174 -0.81877 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -1.00489 -0.27538 0.7138 0.3807 1.300 0.48905 0.0029 -0.17712 -0.79698 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -0.98876 -0.25008 0.7137 0.3827 1.400 0.38492 0.0029 -0.18237 -0.78548 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -0.97760 -0.23508 0.7263 0.3787 1.500 0.36315 0.0029 -0.18790 -0.79498 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -0.98071 -0.24695 0.7287 0.3821 1.600 0.28812 0.0029 -0.19363 -0.78665 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -0.96369 -0.22870 0.7307 0.3854 1.700 0.18172 0.0029 -0.19545 -0.77778 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -0.94634 -0.21655 0.7322 0.3751 1.800 0.13021 0.0029 -0.20069 -0.77282 0.2529 7.5 -0.5096 0.0000 -0.0030 6.75 1000 750 2.5 3.2 -0.93606 -0.20302 0.7316 0.3749 1.900 0.05074 0.0029 -0.20386 -0.76574 0.2529 7.5 -0.5096 0.0000 -0.0060 6.75 1000 750 2.5 3.2 -0.91408 -0.18228 0.7341 0.3761 2.000 -0.02806 0.0029 -0.20666 -0.76260 0.2529 7.5 -0.5096 0.0000 -0.0090 6.75 1000 750 2.5 3.2 -0.91007 -0.17336 0.7333 0.3734 2.200 -0.15016 0.0029 -0.21319 -0.75952 0.2529 7.5 -0.5096 0.0000 -0.0141 6.75 1000 750 2.5 3.2 -0.89376 -0.15463 0.7277 0.3794 2.400 -0.26608 0.0029 -0.21960 -0.75011 0.2529 7.5 -0.5096 0.0000 -0.0284 6.75 1000 750 2.5 3.2 -0.87052 -0.13181 0.7199 0.4025 2.600 -0.39025 0.0029 -0.22330 -0.74326 0.2529 7.5 -0.5096 0.0000 -0.0408 6.75 1000 750 2.5 3.2 -0.85889 -0.14066 0.7171 0.4049 2.800 -0.49742 0.0029 -0.22716 -0.74185 0.2529 7.5 -0.5096 0.0000 -0.0534 6.75 1000 750 2.5 3.2 -0.86106 -0.13882 0.7175 0.4090 3.000 -0.64241 0.0029 -0.23038 -0.73634 0.2529 7.5 -0.5096 0.0000 -0.0683 6.75 1000 750 2.5 3.2 -0.85793 -0.13336 0.7051 0.4115 3.200 -0.76670 0.0029 -0.23049 -0.72149 0.2529 7.5 -0.5096 0.0000 -0.0780 6.75 1000 750 2.5 3.2 -0.82094 -0.13770 0.6876 0.4280 3.400 -0.80566 0.0029 -0.23726 -0.72539 0.2529 7.5 -0.5096 0.0000 -0.0943 6.75 1000 750 2.5 3.2 -0.84449 -0.15337 0.6750 0.4029 3.600 -0.94500 0.0029 -0.24437 -0.70115 0.2529 7.5 -0.5096 0.0000 -0.1278 6.75 1000 750 2.5 3.2 -0.83216 -0.10884 0.6571 0.4252 3.800 -0.98457 0.0029 -0.24930 -0.69696 0.2529 7.5 -0.5096 0.0000 -0.1744 6.75 1000 750 2.5 3.2 -0.79216 -0.08884 0.6438 0.4243 4.000 -0.93329 0.0029 -0.25756 -0.71210 0.2529 7.5 -0.5096 0.0000 -0.2231 6.75 1000 750 2.5 3.2 -0.75645 -0.07749 0.6241 0.3659 """)
[docs]class AkkarEtAlRhyp2014(AkkarEtAlRjb2014): """ Implements GMPE developed by S. Akkar, M. A. Sandikkaya, and J. J. Bommer as published in "Empirical Ground-Motion Models for Point- and Extended- Source Crustal Earthquake Scenarios in Europe and the Middle East", Bullettin of Earthquake Engineering (2014). The class implements the equations for hypocentral distance and based on manuscript provided by the original authors. """ REQUIRES_DISTANCES = {'rhypo'} COEFFS = CoeffsTable(sa_damping=5, table="""\ IMT a1 a2 a3 a4 a5 a6 a7 a8 a9 c1 Vcon Vref c n b1 b2 sigma tau pga 3.26685 0.0029 -0.04846 -1.47905 0.2529 7.5 -0.5096 -0.1091 0.0937 6.75 1000 750 2.5 3.2 -0.41997 -0.28846 0.6475 0.3472 pgv 6.72743 0.0029 -0.11474 -1.17694 0.2529 7.5 -0.5096 -0.0616 0.0630 6.75 1000 750 2.5 3.2 -0.72057 -0.19688 0.6280 0.3312 0.010 3.28656 0.0029 -0.04784 -1.48197 0.2529 7.5 -0.5096 -0.1115 0.0953 6.75 1000 750 2.5 3.2 -0.41729 -0.28685 0.6492 0.3481 0.020 3.38936 0.0029 -0.04796 -1.50214 0.2529 7.5 -0.5096 -0.1040 0.1029 6.75 1000 750 2.5 3.2 -0.39998 -0.28241 0.6543 0.3508 0.030 3.53155 0.0029 -0.04537 -1.52781 0.2529 7.5 -0.5096 -0.0973 0.1148 6.75 1000 750 2.5 3.2 -0.34799 -0.26842 0.6685 0.3526 0.040 3.68895 0.0029 -0.03991 -1.55693 0.2529 7.5 -0.5096 -0.0884 0.1073 6.75 1000 750 2.5 3.2 -0.27572 -0.24759 0.6816 0.3513 0.050 3.86581 0.0029 -0.03490 -1.58672 0.2529 7.5 -0.5096 -0.0853 0.1052 6.75 1000 750 2.5 3.2 -0.21231 -0.22385 0.6899 0.3659 0.075 4.18224 0.0029 -0.02826 -1.62527 0.2529 7.5 -0.5096 -0.0779 0.0837 6.75 1000 750 2.5 3.2 -0.14427 -0.17525 0.6881 0.3942 0.100 4.43750 0.0029 -0.03256 -1.65601 0.2529 7.5 -0.5096 -0.0749 0.0761 6.75 1000 750 2.5 3.2 -0.27064 -0.29293 0.6936 0.4122 0.110 4.48828 0.0029 -0.03407 -1.65903 0.2529 7.5 -0.5096 -0.0704 0.0707 6.75 1000 750 2.5 3.2 -0.31025 -0.31837 0.6965 0.4065 0.120 4.51414 0.0029 -0.03635 -1.65470 0.2529 7.5 -0.5096 -0.0604 0.0653 6.75 1000 750 2.5 3.2 -0.34796 -0.33860 0.7022 0.3964 0.130 4.53290 0.0029 -0.03929 -1.64994 0.2529 7.5 -0.5096 -0.0490 0.0617 6.75 1000 750 2.5 3.2 -0.39668 -0.36646 0.7043 0.3937 0.140 4.53834 0.0029 -0.04200 -1.64398 0.2529 7.5 -0.5096 -0.0377 0.0581 6.75 1000 750 2.5 3.2 -0.43996 -0.38417 0.7071 0.3853 0.150 4.52949 0.0029 -0.04509 -1.63467 0.2529 7.5 -0.5096 -0.0265 0.0545 6.75 1000 750 2.5 3.2 -0.48313 -0.39551 0.7048 0.3779 0.160 4.47016 0.0029 -0.04701 -1.61626 0.2529 7.5 -0.5096 -0.0194 0.0509 6.75 1000 750 2.5 3.2 -0.52431 -0.40869 0.7032 0.3851 0.170 4.40011 0.0029 -0.04932 -1.59485 0.2529 7.5 -0.5096 -0.0125 0.0507 6.75 1000 750 2.5 3.2 -0.55680 -0.41528 0.7011 0.3900 0.180 4.33238 0.0029 -0.05181 -1.57545 0.2529 7.5 -0.5096 -0.0056 0.0502 6.75 1000 750 2.5 3.2 -0.58922 -0.42717 0.6992 0.3889 0.190 4.26395 0.0029 -0.05442 -1.55685 0.2529 7.5 -0.5096 0.0000 0.0497 6.75 1000 750 2.5 3.2 -0.62635 -0.44130 0.6947 0.3903 0.200 4.17750 0.0029 -0.05565 -1.53574 0.2529 7.5 -0.5096 0.0000 0.0493 6.75 1000 750 2.5 3.2 -0.65315 -0.44644 0.6954 0.3848 0.220 4.03111 0.0029 -0.05817 -1.50045 0.2529 7.5 -0.5096 0.0000 0.0488 6.75 1000 750 2.5 3.2 -0.68711 -0.44872 0.6925 0.3891 0.240 3.90131 0.0029 -0.06152 -1.46889 0.2529 7.5 -0.5096 0.0000 0.0483 6.75 1000 750 2.5 3.2 -0.72744 -0.46341 0.6973 0.3839 0.260 3.82611 0.0029 -0.06706 -1.44738 0.2529 7.5 -0.5096 0.0000 0.0478 6.75 1000 750 2.5 3.2 -0.77335 -0.48705 0.6973 0.3839 0.280 3.69780 0.0029 -0.07060 -1.41925 0.2529 7.5 -0.5096 0.0000 0.0474 6.75 1000 750 2.5 3.2 -0.80508 -0.47334 0.6914 0.3865 0.300 3.57698 0.0029 -0.07490 -1.38832 0.2529 7.5 -0.5096 0.0000 0.0469 6.75 1000 750 2.5 3.2 -0.82609 -0.45730 0.6934 0.3896 0.320 3.40759 0.0029 -0.07756 -1.34898 0.2529 7.5 -0.5096 0.0000 0.0464 6.75 1000 750 2.5 3.2 -0.84080 -0.44267 0.6992 0.3908 0.340 3.27580 0.0029 -0.08183 -1.31609 0.2529 7.5 -0.5096 0.0000 0.0459 6.75 1000 750 2.5 3.2 -0.86251 -0.43888 0.6990 0.3888 0.360 3.19725 0.0029 -0.08602 -1.29558 0.2529 7.5 -0.5096 0.0000 0.0459 6.75 1000 750 2.5 3.2 -0.87479 -0.43820 0.7006 0.3916 0.380 3.11035 0.0029 -0.08937 -1.27591 0.2529 7.5 -0.5096 0.0000 0.0429 6.75 1000 750 2.5 3.2 -0.88522 -0.43678 0.7036 0.3913 0.400 3.03752 0.0029 -0.09243 -1.26045 0.2529 7.5 -0.5096 0.0000 0.0400 6.75 1000 750 2.5 3.2 -0.89517 -0.43008 0.7037 0.3894 0.420 2.97485 0.0029 -0.09556 -1.24891 0.2529 7.5 -0.5096 0.0000 0.0374 6.75 1000 750 2.5 3.2 -0.90875 -0.42190 0.7023 0.3847 0.440 2.90617 0.0029 -0.09822 -1.23700 0.2529 7.5 -0.5096 0.0000 0.0349 6.75 1000 750 2.5 3.2 -0.91922 -0.40903 0.6956 0.3908 0.460 2.85484 0.0029 -0.10132 -1.22822 0.2529 7.5 -0.5096 0.0000 0.0323 6.75 1000 750 2.5 3.2 -0.92670 -0.39442 0.6893 0.3986 0.480 2.81720 0.0029 -0.10560 -1.21874 0.2529 7.5 -0.5096 0.0000 0.0297 6.75 1000 750 2.5 3.2 -0.93720 -0.38462 0.6852 0.4017 0.500 2.77997 0.0029 -0.10964 -1.20953 0.2529 7.5 -0.5096 0.0000 0.0271 6.75 1000 750 2.5 3.2 -0.94614 -0.37408 0.6821 0.4017 0.550 2.62299 0.0029 -0.11701 -1.18010 0.2529 7.5 -0.5096 0.0000 0.0245 6.75 1000 750 2.5 3.2 -0.96564 -0.35582 0.6866 0.4044 0.600 2.42234 0.0029 -0.12106 -1.14424 0.2529 7.5 -0.5096 0.0000 0.0219 6.75 1000 750 2.5 3.2 -0.98499 -0.34053 0.6926 0.4005 0.650 2.22770 0.0029 -0.12555 -1.10853 0.2529 7.5 -0.5096 0.0000 0.0193 6.75 1000 750 2.5 3.2 -0.99733 -0.30949 0.6949 0.3981 0.700 2.08102 0.0029 -0.13074 -1.08192 0.2529 7.5 -0.5096 0.0000 0.0167 6.75 1000 750 2.5 3.2 -1.00469 -0.28772 0.6993 0.3967 0.750 1.91625 0.0029 -0.13547 -1.05027 0.2529 7.5 -0.5096 0.0000 0.0141 6.75 1000 750 2.5 3.2 -1.00786 -0.28957 0.7028 0.3890 0.800 1.81167 0.0029 -0.13856 -1.03514 0.2529 7.5 -0.5096 0.0000 0.0115 6.75 1000 750 2.5 3.2 -1.00606 -0.28555 0.6981 0.3824 0.850 1.71853 0.0029 -0.14294 -1.02010 0.2529 7.5 -0.5096 0.0000 0.0089 6.75 1000 750 2.5 3.2 -1.01093 -0.28364 0.6959 0.3831 0.900 1.60822 0.0029 -0.14669 -1.00315 0.2529 7.5 -0.5096 0.0000 0.0062 6.75 1000 750 2.5 3.2 -1.01576 -0.28037 0.6983 0.3825 0.950 1.51532 0.0029 -0.15056 -0.98859 0.2529 7.5 -0.5096 0.0000 0.0016 6.75 1000 750 2.5 3.2 -1.01353 -0.28390 0.7006 0.3797 1.000 1.43982 0.0029 -0.15427 -0.97812 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -1.01331 -0.28702 0.7022 0.3826 1.100 1.26728 0.0029 -0.16107 -0.95163 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -1.01240 -0.27669 0.7137 0.3721 1.200 1.11475 0.0029 -0.16630 -0.93048 0.2529 7.5 -0.5096 0.0000 0.0000 6.75 1000 750 2.5 3.2 -1.00489 -0.27538 0.7224 0.3723 1.300 0.95965 0.0029 -0.17170 -0.90604 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