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DTSTAMP:20210916T132530Z
LOCATION:Louis Favre
DTSTART;TZID=Europe/Stockholm:20210706T140000
DTEND;TZID=Europe/Stockholm:20210706T160000
UID:submissions.pasc-conference.org_PASC21_sess125@linklings.com
SUMMARY:Advances in Computational Geosciences, Part III
DESCRIPTION:Minisymposium\n\nComputational geosciences leverage advanced c
omputational methods to improve our understanding of the interiors of Ear
th and other planets. They combine numerical models to understand the curr
ent state of physical quantities describing a system, to predict their fut
ure states, and to infer unknown parameters of those models from data meas
urements. Such models produce highly nonlinear numerical systems with extr
emely large numbers of unknowns.\nThe ever-increasing power and availabili
ty of High Performance Computing (HPC) facilities offers researchers unpre
cedented opportunities to continually increase both the spatiotemporal res
olution and the physical complexity of their numerical models. However, th
is requires complex numerical methods and their implementations that can h
arness the HPC resources efficiently for problem sizes of billions of degr
ees of freedom.\nThe goal of this minisymposium is to bring scientists who
work in theory, numerical methods, algorithms and scientific software eng
ineering for scalable numerical modelling and inversion. Examples include,
but are not limited to, geodynamics, multi-phase geophysical flow modelli
ng, seismic wave propagation and imaging, seismic tomography and inversion
of large data sets, development of elaborate workflows including HPC for
imaging problems, ice-sheet modelling, and urgent computing for natural ha
zards.\n\nHigh Performance Computing for Probabilistic Tsunami Hazard Anal
ysis\n\nLøvholt, Gibbons, Lorito, Volpe, Selva...\n\nTsunamis represent a
hazard which strikes the population infrequently while involving potential
ly large consequences. Probabilistic Tsunami Hazard Analysis (PTHA) addres
ses the likelihood of a tsunami exceeding given metric within a given time
interval. Uncertainty quantification in PTHA sometimes n...\n\n----------
-----------\nChallenges and Solutions for Faster than Real-Time Tsunami Si
mulations\n\nde la Asunción, Castro, Macías, González, Sánchez\n\nTsunami-
HySEA is a numerical model for the simulation of tsunamis generated by ear
thquakes running on GPU architectures. These simulations require a great c
omputational demand due to the big sizes of spatial and temporal domains.
In addition, fast response times are required so that the local author...\
n\n---------------------\nVolcanic Ash: Coupling Three-Dimensional Multiph
ase Plume Simulations with Ash Dispersion Models\n\nCerminara, Pardini, Fo
lch, Mingari\n\nDuring an explosive volcanic eruption, a volcanic plume is
injected into the atmosphere. It is a compressible, turbulent, hot multip
hase mixture of volcanic gases and solid particles, the fragmented magma.
It forms umbrella clouds spreading downwind for hundreds to thousands of k
ilometers. Volcanic ...\n\n---------------------\nDispersive Tsunami-HySEA
Model for Faster Than Real Time Tsunami Simulations\n\nEscalante, Castro,
Macías\n\nThis work aims to develop and implement a numerical model, incl
uding dispersion suitable for tsunami simulations. Therefore, including mo
re physics but still computing much Faster than Real-time. The main proble
m is that state-of-the-art dispersive models do not have a hyperbolic char
acter, such as ...\n\n\nDomain: CS and Math, Solid Earth Dynamics
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