Explore the words cloud of the ExaQUte project. It provides you a very rough idea of what is the project "ExaQUte" about.
The following table provides information about the project.
CENTRE INTERNACIONAL DE METODES NUMERICS EN ENGINYERIA
|Coordinator Country||Spain [ES]|
|Total cost||3˙124˙255 €|
|EC max contribution||3˙124˙255 € (100%)|
1. H2020-EU.1.2.2. (FET Proactive)
|Duration (year-month-day)||from 2018-06-01 to 2021-05-31|
Take a look of project's partnership.
|1||CENTRE INTERNACIONAL DE METODES NUMERICS EN ENGINYERIA||ES (BARCELONA)||coordinator||698˙500.00|
|2||TECHNISCHE UNIVERSITAET MUENCHEN||DE (MUENCHEN)||participant||628˙125.00|
|3||ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE||CH (LAUSANNE)||participant||523˙500.00|
|4||VYSOKA SKOLA BANSKA - TECHNICKA UNIVERZITA OSTRAVA||CZ (OSTRAVA PORUBA)||participant||320˙000.00|
|5||BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION||ES (BARCELONA)||participant||316˙000.00|
|6||INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE||FR (LE CHESNAY CEDEX)||participant||298˙630.00|
|7||UNIVERSITAT POLITECNICA DE CATALUNYA||ES (BARCELONA)||participant||257˙000.00|
|8||str.ucture GmbH||DE (STUTTGART)||participant||82˙500.00|
The ExaQUte project aims at constructing a framework to enable Uncertainty Quantification (UQ) and Optimization Under Uncertainties (OUU) in complex engineering problems using computational simulations on Exascale systems. The stochastic problem of quantifying uncertainties will be tackled by using a Multi Level MonteCarlo (MLMC) approach that allows a high number of stochastic variables. New theoretical developments will be carried out to enable its combination with adaptive mesh refinement, considering both, octree-based and anisotropic mesh adaptation. Gradient-based optimization techniques will be extended to consider uncertainties by developing methods to compute stochastic sensitivities, This requires new theoretical and computational developments. With a proper definition of risk measures and constraints, these methods allow high-performance robust designs, also maximizing the solution reliability. The description of complex geometries will be possible by employing embedded methods, which guarantee a high robustness in the mesh generation and adaptation steps, while allowing preserving the exact geometry representation. The efficient exploitation of Exascale system will be addressed by combining State-of-the-Art dynamic task-scheduling technologies with space-time accelerated solution methods, where parallelism is harvested both in space and time. The methods and tools developed in ExaQUte will be applicable to many fields of science and technology. The chosen application focuses on wind engineering, a field of notable industrial interest for which currently no reliable solution exists. This will include the quantification of uncertainties in the response of civil engineering structures to the wind action, and the shape optimization taking into account uncertainties related to wind loading, structural shape and material behavior. All developments in ExaQUte will be open-source and will follow a modular approach, thus maximizing future impact.
|Profiling report of the partnerâ€™s tools||Other||2020-04-09 20:08:54|
|API and runtime for IO using persistent storage||Other||2020-04-09 20:09:01|
|Report on nonlinear domain decomisition preconditioners and release of the solvers||Documents, reports||2020-04-09 20:08:49|
|Report on the calculation of stochastic sensitivities||Documents, reports||2020-04-09 20:09:22|
|Release of ExaQUte MLMC python engine||Other||2020-04-09 20:09:14|
|Release of ExaQUte API for MLMC||Other||2020-04-09 20:09:07|
|Data Management Plan||Open Research Data Pilot||2020-04-09 20:09:28|
|Exploitation plan (M18)||Documents, reports||2020-04-09 20:10:30|
|Report on dissemination activities (M18)||Documents, reports||2020-04-09 20:10:24|
|Meshing â€œstubâ€ implementation of the capabilities to be delivered||Other||2020-04-09 20:10:36|
Take a look to the deliverables list in detail: detailed list of ExaQUte deliverables.
|year||authors and title||journal||last update|
Santiago Badia, Alberto F. MartÃn, Hieu Nguyen
Balancing domain decomposition by constraints associated with subobjects
published pages: 93-100, ISSN: 0893-9659, DOI: 10.1016/j.aml.2018.07.033
|Applied Mathematics Letters 87||2020-02-05|
Daniel Drzisga, Brendan Keith, Barbara Wohlmuth
The Surrogate Matrix Methodology: A Priori Error Estimation
published pages: A3806-A3838, ISSN: 1064-8275, DOI: 10.1137/18m1226580
|SIAM Journal on Scientific Computing 41/6||2020-01-30|
Daniel Drzisga, Brendan Keith, Barbara Wohlmuth
The surrogate matrix methodology: Low-cost assembly for isogeometric analysis
published pages: 112776, ISSN: 0045-7825, DOI: 10.1016/j.cma.2019.112776
|Computer Methods in Applied Mechanics and Engineering 361||2020-01-30|
R. Zorrilla, A. Larese, R. Rossi
A modified Finite Element formulation for the imposition of the slip boundary condition over embedded volumeless geometries
published pages: 123-157, ISSN: 0045-7825, DOI: 10.1016/j.cma.2019.05.007
|Computer Methods in Applied Mechanics and Engineering 353||2020-01-30|
Francesc Verdugo, Alberto F. MartÃn, Santiago Badia
Distributed-memory parallelization of the aggregated unfitted finite element method
published pages: 112583, ISSN: 0045-7825, DOI: 10.1016/j.cma.2019.112583
|Computer Methods in Applied Mechanics and Engineering 357||2020-01-30|
Luca Cirrottola, Algiane Froehly
Parallel unstructured mesh adaptation using iterative remeshing and repartitioning
published pages: , ISSN: , DOI:
|INRIA Research Report 9307, november 2019||2020-01-30|
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