4,096 research outputs found
Enhancing Energy Production with Exascale HPC Methods
High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose
processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale
simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of
Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and
from the Brazilian Ministry of Science, Technology and Innovation through Rede
Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the
Intel Corporation, which enabled us to obtain the presented experimental results in
uncertainty quantification in seismic imagingPostprint (author's final draft
QuantumATK: An integrated platform of electronic and atomic-scale modelling tools
QuantumATK is an integrated set of atomic-scale modelling tools developed
since 2003 by professional software engineers in collaboration with academic
researchers. While different aspects and individual modules of the platform
have been previously presented, the purpose of this paper is to give a general
overview of the platform. The QuantumATK simulation engines enable
electronic-structure calculations using density functional theory or
tight-binding model Hamiltonians, and also offers bonded or reactive empirical
force fields in many different parametrizations. Density functional theory is
implemented using either a plane-wave basis or expansion of electronic states
in a linear combination of atomic orbitals. The platform includes a long list
of advanced modules, including Green's-function methods for electron transport
simulations and surface calculations, first-principles electron-phonon and
electron-photon couplings, simulation of atomic-scale heat transport, ion
dynamics, spintronics, optical properties of materials, static polarization,
and more. Seamless integration of the different simulation engines into a
common platform allows for easy combination of different simulation methods
into complex workflows. Besides giving a general overview and presenting a
number of implementation details not previously published, we also present four
different application examples. These are calculations of the phonon-limited
mobility of Cu, Ag and Au, electron transport in a gated 2D device, multi-model
simulation of lithium ion drift through a battery cathode in an external
electric field, and electronic-structure calculations of the
composition-dependent band gap of SiGe alloys.Comment: Submitted to Journal of Physics: Condensed Matte
Energy preserving model order reduction of the nonlinear Schr\"odinger equation
An energy preserving reduced order model is developed for two dimensional
nonlinear Schr\"odinger equation (NLSE) with plane wave solutions and with an
external potential. The NLSE is discretized in space by the symmetric interior
penalty discontinuous Galerkin (SIPG) method. The resulting system of
Hamiltonian ordinary differential equations are integrated in time by the
energy preserving average vector field (AVF) method. The mass and energy
preserving reduced order model (ROM) is constructed by proper orthogonal
decomposition (POD) Galerkin projection. The nonlinearities are computed for
the ROM efficiently by discrete empirical interpolation method (DEIM) and
dynamic mode decomposition (DMD). Preservation of the semi-discrete energy and
mass are shown for the full order model (FOM) and for the ROM which ensures the
long term stability of the solutions. Numerical simulations illustrate the
preservation of the energy and mass in the reduced order model for the two
dimensional NLSE with and without the external potential. The POD-DMD makes a
remarkable improvement in computational speed-up over the POD-DEIM. Both
methods approximate accurately the FOM, whereas POD-DEIM is more accurate than
the POD-DMD
Some comments on Monte Carlo and molecular dynamics methods
We highlight some links between molecular dynamics and Monte Carlo algorithms used to simulate condensed matter systems. Special attention is paid to the question of sampling the desired statistical ensemble
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