0000000000604123

AUTHOR

Z Jiang

showing 2 related works from this author

Measurement of the Lund jet plane using charged particles in 13 TeV proton-proton collisions with the ATLAS detector

2020

The prevalence of hadronic jets at the LHC requires that a deep understanding of jet formation and structure is achieved in order to reach the highest levels of experimental and theoretical precision. There have been many measurements of jet substructure at the LHC and previous colliders, but the targeted observables mix physical effects from various origins. Based on a recent proposal to factorize physical effects, this Letter presents a double-differential cross-section measurement of the Lund jet plane using 139  fb−1 of √s=13  TeV proton-proton collision data collected with the ATLAS detector using jets with transverse momentum above 675 GeV. The measurement uses charged particles to ac…

:Kjerne- og elementærpartikkelfysikk: 431 [VDP]Protonshowers [parton]13000 GeV-cmsPhysics::Instrumentation and DetectorsHadronGeneral Physics and Astronomyjet: transverse momentumPhysical Effects01 natural sciencestransverse momentum [jet]High Energy Physics - ExperimentSubatomär fysikHigh Energy Physics - Experiment (hep-ex)Charged ParticlesSubatomic PhysicsComputingMilieux_COMPUTERSANDEDUCATIONscattering [p p][PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Parton showerNuclear ExperimentGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)PhysicsSettore FIS/01Jet (fluid)Large Hadron ColliderDouble Differential Cross SectionsDetectorhadronic [jet]Monte Carlo [numerical calculations]ATLASTransverse Momentacharged particleCharged particlemedicine.anatomical_structureCERN LHC Coll:Nuclear and elementary particle physics: 431 [VDP]colliding beams [p p]numerical calculations: Monte CarloParticle Physics - Experimentp p: scatteringCiências Naturais::Ciências Físicas530 Physicsformation [jet]Astrophysics::High Energy Astrophysical Phenomena:Ciências Físicas [Ciências Naturais]FOS: Physical sciencesMeasurements ofLHC ATLAS High Energy Physicsjet: formation530GeneralLiterature_MISCELLANEOUSMonte Carlo Modelparton: showersNuclear physicsdifferential cross section: measuredAtlas (anatomy)Fragmentationmeasured [differential cross section]0103 physical sciencesmedicineddc:530High Energy Physicsstructure010306 general physicsATLAS CollaborationScience & Technology010308 nuclear & particles physicsComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSFísicajet: hadronic530 Physikangular resolutionProton Proton CollisionsElementary Particles and FieldsHigh Energy Physics::ExperimentDetector EffectsHadron-hadron collisionsp p: colliding beamsMathematicsofComputing_DISCRETEMATHEMATICSacceptanceexperimental results
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Prediction of dynamic mooring responses of a floating wind turbine using an artificial neural network

2021

Abstract Numerical simulations in coupled aero-hydro-servo-elastic codes are known to be a challenge for design and analysis of offshore wind turbine systems because of the large number of design load cases involved in checking the ultimate and fatigue limit states. To alleviate the simulation burden, machine learning methods can be useful. This article investigates the effect of machine learning methods on predicting the mooring line tension of a spar floating wind turbine. The OC3 Hywind wind turbine with a spar-buoy foundation and three mooring lines is selected and simulated with SIMA. A total of 32 sea states with irregular waves are considered. Artificial neural works with different c…

VDP::Teknologi: 500Artificial neural networkComputer scienceFloating wind turbineMooringMarine engineeringIOP Conference Series: Materials Science and Engineering
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