Search results for "Computational Science"

showing 10 items of 124 documents

geomIO: An Open‐Source MATLAB Toolbox to Create the Initial Configuration of 2‐D/3‐D Thermo‐Mechanical Simulations From 2‐D Vector Drawings

2019

Creating the initial geometry and temperature configuration of 3D numerical simulations is a challenging task. Professional tools are expensive. They often have a steep learning curve and do mostly not interface with the numerical simulation software used by the geodynamics and tectonics academic community. There, we developed geomIO (geometry Input/Output), a MATLAB toolbox to create the initial configuration of geological models regarding model geometry and temperature structure. geomIO allows users to create a geo-referenced 3D volume by drawing multiple 2D cross-sections in a standard vector graphics editor. The volume is then used to assign material properties and set up initial temper…

Data processingSource lines of code010504 meteorology & atmospheric sciencesbusiness.industryInterface (Java)010502 geochemistry & geophysicsFile format01 natural sciencesToolboxComputational scienceVector graphicsGeophysicsSoftwareGeochemistry and PetrologyTriangle meshbusinessGeology0105 earth and related environmental sciencesGeochemistry, Geophysics, Geosystems
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Interactive Terrain Simulation and Force Distribution Models in Sand Piles

2006

This paper presents an application of Cellular Automata in the field of dry Granular Systems modelling While the study of granular systems is not a recent field, no efficient models exist, from a computational point of view, in classical methodologies Some previous works showed that the use of Cellular Automata is suitable for the development of models that can be used in real time applications This paper extends the existing Cellular Automata models in order to make them interactive A model for the reaction to external forces and a pressure distribution model are presented and analyzed, with numerical examples and simulations.

Development (topology)Distribution (mathematics)Computer scienceTerrainPoint (geometry)Nonlinear Sciences::Cellular Automata and Lattice GasesAlgorithmCellular automatonField (computer science)Computational science
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Advances in automated diffraction tomography

2009

Crystal structure solution by means of electron diffraction or investigation of special structural features needs high quality data acquisition followed by data processing which delivers cell parameters, space group and in the end a 3D data set. The final step is the structure analysis itself including structure solution and subsequent refinement.

Diffraction tomographyData setData processingMaterials scienceElectron diffractionbusiness.industryData qualityTomographyCrystal structurebusinessAutomationComputational science
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The on-line coupled atmospheric chemistry model system MECO(n) – Part 5: Expanding the Multi-Model-Driver (MMD v2.0) for 2-way data exchange includin…

2018

Abstract. As part of the Modular Earth Submodel System (MESSy), the Multi-Model-Driver (MMD v1.0) was developed to couple online the regional Consortium for Small-scale Modeling (COSMO) model into a driving model, which can be either the regional COSMO model or the global European Centre Hamburg general circulation model (ECHAM) (see Part 2 of the model documentation). The coupled system is called MECO(n), i.e., MESSy-fied ECHAM and COSMO models nested n times. In this article, which is part of the model documentation of the MECO(n) system, the second generation of MMD is introduced. MMD comprises the message-passing infrastructure required for the parallel execution (multiple programme mul…

ECHAMatmospheric chemistryTheoretical computer science010504 meteorology & atmospheric sciencesComputer science0208 environmental biotechnology02 engineering and technology01 natural sciencesComputational scienceMESSyMECO(n)Erdsystem-Modellierungddc:550multi-scale modelling0105 earth and related environmental sciencesEMACtwo-way-nestinCOSMObusiness.industrylcsh:QE1-996.5grid transformationModular designGrid020801 environmental engineeringlcsh:GeologyEarth sciencesTransformation (function)Modular Earth Submodel SystemData exchangeLine (geometry)dustGRIDbusinessMulti-Model-DriverremappingInterpolationData transmissionGeoscientific Model Development
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Alg: a Toolbox for the Generation of Look-Up tables Based on Atmospheric Radiative Transfer Models

2018

Atmospheric radiative transfer models (RTMs) are software tools describing the radiation processes occurring on the Earth’s atmosphere. While the evolution of these tools have achieved better representations of the light-atmosphere interactions, the increase of complexity, interpretability and computation time bears implications towards practical applications in Earth observation. Despite of existing RTM-specific graphical user interfaces, none of these tools allow common streamlining model setup for a wide variety of atmospheric RTMs. In addition, the automatic generation of atmospheric look-up tables (LUTs) can hardly be done with the use of these graphical tools. This paper presents the …

Earth observation010504 meteorology & atmospheric sciencesbusiness.industryMODTRANComputer science0211 other engineering and technologies02 engineering and technology01 natural sciencesDomain (software engineering)Computational scienceSoftwareLookup tableRadiative transferTable (database)business021101 geological & geomatics engineering0105 earth and related environmental sciencesGraphical user interface2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)
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A Geant4 simulation package for the sage spectrometer

2012

International audience; A comprehensive Geant4 simulation was built for the SAGE spectrometer. The simulation package includes the silicon and germanium detectors, the mechanical structure and the electromagnetic fields present in SAGE. This simulation can be used for making predictions through simulating experiments and for comparing simulated and experimental data to better understand the underlying physics.

Electromagnetic fieldHistorySiliconSpectrometer010308 nuclear & particles physicsComputer sciencePhysics::Instrumentation and DetectorsDetectorchemistry.chemical_elementExperimental dataGermaniumComputerApplications_COMPUTERSINOTHERSYSTEMS[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]01 natural sciencesComputer Science ApplicationsEducationComputational scienceKokeellinen ydinfysiikkachemistry0103 physical sciencesComputer Science::Mathematical Software29.40.Wk Solid-state detectors 29.30.Kv X- and gamma-ray spectroscopy 07.85.Nc X-ray and gamma-ray spectrometers 29.30.Dn Electron spectroscopyExperimental nuclear physics010306 general physics
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A commercial EM solver using the BI-RME method

2014

Electronic engineeringSolverComputational scienceMathematics2014 International Conference on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO)
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Array programming with NumPy.

2020

Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programmi…

FOS: Computer and information sciences/639/705/1042Computer science/639/705/794Interoperability/639/705/117Review ArticleStatistics - Computationohjelmointikielet01 natural sciences03 medical and health sciencesSoftwareSoftware Designlaskennallinen tiede0103 physical sciencesFOS: Mathematics010303 astronomy & astrophysicsComputation (stat.CO)030304 developmental biologycomputer.programming_languageSolar physics0303 health sciencesMultidisciplinaryApplication programming interfacebusiness.industryNumPyComputational sciencereview-articleComputational BiologyPython (programming language)Computer science/704/525/870Computational neuroscienceProgramming paradigmSoftware designComputer Science - Mathematical Software/631/378/116/139Programming LanguagesArray programmingohjelmistokirjastotSoftware engineeringbusinessMathematical Software (cs.MS)computerMathematicsSoftwarePythonNature
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A novel approach to integration by parts reduction

2015

Integration by parts reduction is a standard component of most modern multi-loop calculations in quantum field theory. We present a novel strategy constructed to overcome the limitations of currently available reduction programs based on Laporta's algorithm. The key idea is to construct algebraic identities from numerical samples obtained from reductions over finite fields. We expect the method to be highly amenable to parallelization, show a low memory footprint during the reduction step, and allow for significantly better run-times.

FOS: Computer and information sciencesComputer Science - Symbolic ComputationHigh Energy Physics - TheoryPhysicsNuclear and High Energy Physics010308 nuclear & particles physicsFOS: Physical sciencesConstruct (python library)Symbolic Computation (cs.SC)01 natural scienceslcsh:QC1-999Computational scienceReduction (complexity)High Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)Finite fieldHigh Energy Physics - Theory (hep-th)Component (UML)0103 physical sciencesKey (cryptography)Memory footprintIntegration by partsAlgebraic number010306 general physicslcsh:PhysicsPhysics Letters B
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Multi-GPU Accelerated Multi-Spin Monte Carlo Simulations of the 2D Ising Model

2010

A Modern Graphics Processing unit (GPU) is able to perform massively parallel scientific computations at low cost. We extend our implementation of the checkerboard algorithm for the two-dimensional Ising model [T. Preis et al., Journal of Chemical Physics 228 (2009) 4468–4477] in order to overcome the memory limitations of a single GPU which enables us to simulate significantly larger systems. Using multi-spin coding techniques, we are able to accelerate simulations on a single GPU by factors up to 35 compared to an optimized single Central Processor Unit (CPU) core implementation which employs multi-spin coding. By combining the Compute Unified Device Architecture (CUDA) with the Message P…

FOS: Computer and information sciencesComputer scienceMonte Carlo methodGraphics processing unitFOS: Physical sciencesGeneral Physics and AstronomyMathematical Physics (math-ph)Parallel computingGPU clusterComputational Physics (physics.comp-ph)Graphics (cs.GR)Computational scienceCUDAComputer Science - GraphicsHardware and ArchitectureIsing modelCentral processing unitGeneral-purpose computing on graphics processing unitsMassively parallelPhysics - Computational PhysicsMathematical Physics
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