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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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