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DTSTAMP:20210916T132455Z
LOCATION:Louis Favre
DTSTART;TZID=Europe/Stockholm:20210709T150000
DTEND;TZID=Europe/Stockholm:20210709T153000
UID:submissions.pasc-conference.org_PASC21_sess134_msa268@linklings.com
SUMMARY:Stochastic Modeling for Earthquakes, an Alternative Method for Und
erstanding the Seismic Process
DESCRIPTION:Minisymposium\n\nStochastic Modeling for Earthquakes, an Alter
native Method for Understanding the Seismic Process\n\nMonterrubio, Zúñiga
, de la Puente, Aguilar-Melendez, Carrasco-Jimenez...\n\nIn general terms,
earthquakes are the result of brittle failure within the heterogeneous cr
ust of the Earth. However, the rupture process of a heterogeneous ma
terial is a complex physical problem that is difficult to model deter
ministically due to numerous parameters and physical conditions, which are
largely unknown. Seismology employs two simplified representations o
f earthquakes, namely earthquakes as point sources in stochastic nons
tationary processes or earthquakes as seismic waves radiating from finite&
nbsp;sources. Usually seismic models are based on continuum mechanics, alt
hough many aspects of the rupture processes follow a nonlinear comple
x or fractal behaviour. Many seismological studies show statistical self-s
imilar nature over a broad range of scales. We study earthquake pheno
mena via numerical simulations using the sTochastic Rupture Earthquak
e MOdeL, TREMOL, that is based on the Fiber Bundle Model (FBM). The FBM is
a discrete model developed to study the rupture process in heterogen
eous materials from a stochastic rather than a deterministic perspect
ive. The FBM describes the interactions of individual cells, featurin
g particular transfer load rules and a probability distribution function&n
bsp;describing the intrinsic cell properties. The TREMOL model generates s
eismic synthetic catalogs that show many statistical features of real
events, observed in different seismic stages, such as mainshocks and
aftershocks. The synthetic catalogs generated with TREMOL strongly d
epend on the input model parameters. As a means to establish simpler
input/output relations for our stochastic models, Machine Learning te
chniques have been developed, on top of TREMOL, in order to produce simula
tions that reproduce real statistical features of earthquakes.\n\nDom
ain: CS and Math, Physics, Solid Earth Dynamics
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