Search results for "monte carlo"

showing 10 items of 1587 documents

Ab initio modelling of the Y, O, and Ti solute interaction in fcc-Fe matrix

2018

Abstract Strengthening of the ODS steels by Y2O3 precipitates permits to increase their operation temperature and radiation resistance, which is important in construction materials for future fusion and advanced fission reactors. Both size and spatial distribution of oxide particles significantly affect mechanical properties and radiation resistance of ODS steels. Addition of the Ti species (present also as a natural impurity atoms in iron lattice) in the particles of Y2O3 powder before their mechanical alloying leads to the formation of YTiO3, Y2TiO5, and Y2Ti2O7 nanoparticles in ODS steels. Modelling of these nanoparticle formation needs detailed knowledge of the energetic interactions be…

010302 applied physicsNuclear and High Energy PhysicsMaterials scienceFissionAb initioOxideNanoparticleThermodynamics02 engineering and technology021001 nanoscience & nanotechnology01 natural sciences7. Clean energyIonchemistry.chemical_compoundchemistryImpurity0103 physical sciencesKinetic Monte Carlo0210 nano-technologyInstrumentationRadiation resistanceNuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms
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Simulation and optimization of the implantation of holmium atoms into metallic magnetic microcalorimeters for neutrino mass determination experiments

2017

Abstract Several novel experiments designed to investigate the electron neutrino mass in the sub-eV region are based on the calorimetric measurement of the 163Ho electron capture spectrum. For this the 163Ho source, with a required activity of the order of 1 to 100 Bq , needs to be enclosed in the detector, having a volume smaller than 10 − 3 mm 3 . Ion implantation is presently considered to be the most reliable method to enclose this source in the detector homogeneously distributed in a well defined volume. We have investigated the distribution of implanted holmium ions in different target materials and for different implantation energies by means of Monte Carlo simulations based on the S…

010302 applied physicsPhysicsNuclear and High Energy PhysicsElectron captureMonte Carlo methodDetectorchemistry.chemical_element01 natural sciencesIonIon implantationchemistry0103 physical sciencesAtomic physicsNeutrino010306 general physicsHolmiumInstrumentationElectron neutrinoNuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
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Simulations on time-of-flight ERDA spectrometer performance

2016

The performance of a time-of-flight spectrometer consisting of two timing detectors and an ionization chamber energy detector has been studied using Monte Carlo simulations for the recoil creation and ion transport in the sample and detectors. The ionization chamber pulses have been calculated using Shockley-Ramo theorem and the pulse processing of a digitizing data acquisition setup has been modeled. Complete time-of-flight–energy histograms were simulated under realistic experimental conditions. The simulations were used to study instrumentation related effects in coincidence timing and position sensitivity, such as background in time-of-flight–energy histograms. Corresponding measurement…

010302 applied physicsPhysicsta114SpectrometerPhysics::Instrumentation and Detectorsbusiness.industryInstrumentationMonte Carlo methodDetector7. Clean energy01 natural sciencesMonte Carlo simulationsNuclear physicsTime of flightRecoilOpticsData acquisitiontime-of-flight spectrometers0103 physical sciencesIonization chambersimulations010306 general physicsbusinessInstrumentationReview of Scientific Instruments
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Simulation of IQE tuning of individual cells for DC-balancing multijunction tandem cells

2016

In the present work, the performance of stacks of cells connected in series is examined at different levels of internal quantum efficiency (IQE). Incident photons, generated by employing the ASTM G173-03 data set, are accounted for individually as they interact with the stack of cells. The efficiencies of the devices studied are dependent upon the DC balance throughout the stack of cells. It is demonstrated that reducing the internal quantum efficiency of upper cells can lead to a better DC balance and thereby higher efficiency.

010302 applied physicsWork (thermodynamics)Materials sciencePhotonTandembusiness.industryMonte Carlo methodElectrical engineering02 engineering and technology021001 nanoscience & nanotechnology01 natural sciencesStack (abstract data type)0103 physical sciencesOptoelectronicsQuantum efficiencyPhotonics0210 nano-technologybusinessPhotonic crystal2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC)
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Simulations of the effect of the contact energy levels on a simple model of a hot carrier cell

2016

In the present work, the performance of a simplified model of a hot carrier cell is examined at different energy levels of carrier collection. Incident photons, Monte Carlo generated by employing the ASTM G173-03 data set, are accounted for individually as they interact with the cell. It is assumed that the carriers can be collected ultra-fast, thus avoiding considering hot carrier thermalisation effects. Although the model is preliminary and lacking some mechanisms of hot carrier cells, it has been demonstrated that the present approach to modelling hot carrier solar cells can be developed into fully working models. Some effects of the absorption energy levels in the valence band have been…

010302 applied physicsWork (thermodynamics)SIMPLE (dark matter experiment)PhotonMaterials sciencebusiness.industryMonte Carlo methodElectrical engineering02 engineering and technology021001 nanoscience & nanotechnology01 natural sciencesComputational physicsThermalisationEnergy absorbing0103 physical sciencesValence band0210 nano-technologybusinessEnergy (signal processing)2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC)
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The ensemble switch method and related approaches to obtain interfacial free energies between coexisting phases from simulations: a brief review

2015

The accurate estimation of the excess free energy due to an interface between coexisting phases of a model system by computer simulation often is a challenging task. We review here two methods, whi...

010304 chemical physicsChemistryAccurate estimationGeneral Chemical EngineeringMonte Carlo methodModel systemGeneral ChemistryCondensed Matter Physics01 natural sciencesSurface tensionModeling and Simulation0103 physical sciencesGeneral Materials ScienceFree energiesStatistical physics010306 general physicsInformation SystemsMolecular Simulation
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Monte Carlo Simulations of Au38(SCH3)24 Nanocluster Using Distance-Based Machine Learning Methods

2020

We present an implementation of distance-based machine learning (ML) methods to create a realistic atomistic interaction potential to be used in Monte Carlo simulations of thermal dynamics of thiol...

010304 chemical physicsbusiness.industryChemistryMonte Carlo methodThermal dynamics010402 general chemistryMachine learningcomputer.software_genre01 natural sciences0104 chemical sciencesInteraction potential0103 physical sciencesCluster (physics)Artificial intelligencePhysical and Theoretical ChemistrybusinesscomputerDistance basedThe Journal of Physical Chemistry A
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Supporting group decision makers to locate temporary relief distribution centres after sudden-onset disasters

2020

International audience; In the humanitarian response, multiple decision-makers (DMs) need to collaborate in various problems, such as locating temporary relief distribution centres (RDCs). Several studies have argued that maximising demand coverage, reducing logistics costs and minimising response time are among the critical objectives when locating RDCs after a sudden-onset disaster. However, these objectives are often conflicting and the trade-offs can considerably complicate the situation for finding a consensus.To address the challenge and support the DMs, we suggest investigating the stability of non-dominated alternatives derived from a multi-objective model based on Monte Carlo Simul…

010504 meteorology & atmospheric sciencesComputer sciencemedicine.medical_treatment0211 other engineering and technologiesStability (learning theory)Distribution (economics)02 engineering and technology01 natural sciencesHumanitarian responseNATURAL DISASTERSupport groupINFORMATION-MANAGEMENT[SPI]Engineering Sciences [physics]NETWORK DESIGNGroup decision-making2015 Nepal earthquakemedicineOPTIMIZATIONVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Monte Carlo simulation0105 earth and related environmental sciences021110 strategic defence & security studiesCOORDINATIONCOMPLEXDISTRIBUTION MODELbusiness.industrySTOCHASTIC-MODELHumanitarian responseGeologyGeotechnical Engineering and Engineering GeologyRisk analysis (engineering)Multiobjective facility locationPARETO SETbusinessSafety ResearchHUMANITARIAN LOGISTICSSudden onsetInternational Journal of Disaster Risk Reduction
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GIGJ: a crustal gravity model of the Guangdong Province for predicting the geoneutrino signal at the JUNO experiment

2019

Gravimetric methods are expected to play a decisive role in geophysical modeling of the regional crustal structure applied to geoneutrino studies. GIGJ (GOCE Inversion for Geoneutrinos at JUNO) is a 3D numerical model constituted by ~46 x 10$^{3}$ voxels of 50 x 50 x 0.1 km, built by inverting gravimetric data over the 6{\deg} x 4{\deg} area centered at the Jiangmen Underground Neutrino Observatory (JUNO) experiment, currently under construction in the Guangdong Province (China). The a-priori modeling is based on the adoption of deep seismic sounding profiles, receiver functions, teleseismic P-wave velocity models and Moho depth maps, according to their own accuracy and spatial resolution. …

010504 meteorology & atmospheric sciencesGeoneutrinogeophysical uncertaintieInverse transform samplingFOS: Physical sciences01 natural sciencesBayesian methodUpper middle and lower crustStandard deviationNOSouth China BlockmiddlePhysics - GeophysicsMonte Carlo stochastic optimizationGOCE data gravimetric inversionGeophysical uncertaintiesGeochemistry and PetrologyEarth and Planetary Sciences (miscellaneous)Bayesian method; geophysical uncertainties; GOCE data gravimetric inversion; Monte Carlo stochastic optimization; South China Block; upper middle and lower crustImage resolution0105 earth and related environmental sciencesSubdivisionJiangmen Underground Neutrino Observatoryupper and middle and lower crustbusiness.industrySettore FIS/01 - Fisica SperimentaleCrustupperGeodesy[PHYS.PHYS.PHYS-GEN-PH]Physics [physics]/Physics [physics]/General Physics [physics.gen-ph]Geophysics (physics.geo-ph)and lower crustDepth soundingGeophysics13. Climate actionSpace and Planetary SciencebusinessGeologyBayesian method geophysical uncertainties GOCE data gravimetric inversion Monte Carlo stochastic optimization South China Blockupper and middle and lower crust
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Quantifying geological uncertainty in metamorphic phase equilibria modelling; a Monte Carlo assessment and implications for tectonic interpretations

2016

AbstractPseudosection modelling is rapidly becoming an essential part of a petrologist's toolkit and often forms the basis of interpreting the tectonothermal evolution of a rock sample, outcrop, or geological region. Of the several factors that can affect the accuracy and precision of such calculated phase diagrams, “geological” uncertainty related to natural petrographic variation at the hand sample- and/or thin section-scale is rarely considered. Such uncertainty influences the sample's bulk composition, which is the primary control on its equilibrium phase relationships and thus the interpreted pressure–temperature (P–T) conditions of formation. Two case study examples—a garnet–cordierit…

010504 meteorology & atmospheric sciencesMetamorphic rockMonte Carlo methodMineralogyPseudosectionEarth and Planetary Sciences(all)3705 Geologysub-05010502 geochemistry & geophysics01 natural sciencesKyaniteGeological uncertaintyMatrix (geology)ErrorPetrographyMonte Carlo0105 earth and related environmental sciencesMnNCKFMASHTOlcsh:QE1-996.5Schist37 Earth Scienceslcsh:GeologyTectonicsvisual_artStaurolitevisual_art.visual_art_mediumGeneral Earth and Planetary Sciences3706 GeophysicsGeologyGeoscience Frontiers
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