Search results for " PREDICTION"

showing 10 items of 366 documents

Determination of lifetime probabilities of carbon fibre composite plates and pressure vessels for hydrogen storage

2011

International audience; It is shown that an analogy can be made between the failure of unidirectional carbon fibre reinforced epoxy plates and filament wound carbon fibre composite pressure vessels and that their strengths and failure probabilities can be determined. Fibres in filament wound composite structures are placed on geodesic paths around the mandrel, which becomes the liner; so that when the structure is pressurised the fibres are only subjected to tensile forces, as in a unidirectional composite. Multiscale modelling reveals that composite failure is controlled by fibre breakage and that clustering of fibre breaks determines ultimate reliability of the structure. Time dependent r…

Materials scienceFibre failureComposite number[ SPI.MAT ] Engineering Sciences [physics]/MaterialsEnergy Engineering and Power TechnologyLife prediction02 engineering and technology010402 general chemistry01 natural sciencesViscoelastic matrix[SPI.MAT]Engineering Sciences [physics]/MaterialsProtein filamentMultiscale modellingBreakageUltimate tensile strengthComposite materialRenewable Energy Sustainability and the EnvironmentEpoxy021001 nanoscience & nanotechnologyCondensed Matter PhysicsPressure vesselFailure probability0104 chemical sciencesMandrelFuel TechnologyComposite pressure vesselvisual_artvisual_art.visual_art_mediumRelaxation (physics)0210 nano-technology
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Visual indicator for the detection of end-of-life criterion for composite high pressure vessels for hydrogen storage

2012

International audience; A model to predict the accumulation of fibre breaks in advanced composites, that takes into account all physical phenomena implicated in fibre failure (i.e. the random nature, stress transfer due to breaks, fibre debonding and viscosity of the matrix) shows clearly that the failure of a unidirectional composite structure results in the formation of random fibre breaks which at higher loads coalesce into clusters of broken fibres. This stage of development is followed almost immediately by failure. This has direct application to filament wound pressure vessels of the type used to store hydrogen under high pressure. A novel, cost effective, method of revealing developi…

Materials scienceFibre failureHydrogen[ SPI.MAT ] Engineering Sciences [physics]/MaterialsComposite numberFailureEnergy Engineering and Power Technologychemistry.chemical_elementLife prediction02 engineering and technology[SPI.MAT]Engineering Sciences [physics]/MaterialsProtein filamentStress (mechanics)Hydrogen storageViscosityMultiscale modellingComposite materialRenewable Energy Sustainability and the Environment020502 materials021001 nanoscience & nanotechnologyCondensed Matter PhysicsPressure vesselFuel Technology0205 materials engineeringchemistryComposite pressure vesselAdvanced composite materials0210 nano-technology
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Influence of geometrical ratios in forgeability of complex shapes during hot forging of Ti-6Al-4V titanium alloy

2014

Abstract Titanium alloys are considered desirable materials when both mechanical properties and weight reduction are requested at the same time. This class of materials is widely used in application fields, like aeronautical, in which common steels and light-weight materials, like aluminum alloys, are not able to satisfy all operative service conditions. Most of manufacturing processes of titanium alloy components are based on machining operations, which allow obtaining very accurate final shapes but, at the same time, are affected by several disadvantage like material waste and general production costs. During the last decade, the forging processes for titanium alloys have attracted greate…

Materials sciencebusiness.industryMetallurgyMechanical engineeringTitanium alloyF.E.M.General MedicinePhase predictionMicrostructureHot forgingForgingMaterial flowMachiningThermomechanical processingTi-6Al-4VFillet (mechanics)AerospacebusinessEngineering(all)
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Soft Sensor Transferability between Lines of a Sulfur Recovery Unit

2021

Abstract Soft Sensors (SSs) are mathematical models that allow real-time estimation of hard-to-measure variables as a function of easy-to-measure ones in an industrial process, emulating the behavior of existing sensors when they are, for instance, taken off for maintenance. The Sulfur Recovery Unit (SRU) from a refinery is taken in exam. Recurrent Neural Networks (RNN) can capture the nonlinearity of such process but present a high complexity training and a very time-consuming structure optimization. For this reason, strategies to use pre-existing models are here examined by testing the transferability of the SSs between two parallel lines of the process.

Mathematical modelComputer sciencemedia_common.quotation_subjectProcess (computing)transferable soft sensor; nonlinear model; recurrent neural network; monitoring; prediction; inferential modelControl engineeringpredictionSoft sensorParallelRefineryNonlinear systemmonitoringRecurrent neural networkinferential modelControl and Systems Engineeringnonlinear modelrecurrent neural networkFunction (engineering)media_commontransferable soft sensor
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Unbiased Branches: An Open Problem

2007

The majority of currently available dynamic branch predictors base their prediction accuracy on the previous k branch outcomes. Such predictors sustain high prediction accuracy but they do not consider the impact of unbiased branches, which are difficult-to-predict. In this paper, we evaluate the impact of unbiased branches in terms of prediction accuracy on a range of branch difference predictors using prediction by partial matching, multiple Markov prediction and neural-based prediction. Since our focus is on the impact that unbiased branches have on processor performance, timing issues and hardware costs are out of scope of this investigation. Our simulation results, with the SPEC2000 in…

Mathematical optimizationMarkov chainComputer sciencebusiness.industryOpen problemPrediction by partial matchingBest linear unbiased predictionMachine learningcomputer.software_genreBranch predictorBenchmark (computing)Range (statistics)Artificial intelligenceHardware_CONTROLSTRUCTURESANDMICROPROGRAMMINGbusinesscomputerInteger (computer science)
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A geo-statistical predictive approach to the Habitat mapping of Vulnerable Marine Ecosystems along the northern Sicily inner continental shelf (south…

2016

The main aim of this work is to statistically predict the distribution of Vulnerable Marine Ecosystems (VMEs) along the continental shelf regions of the northern Sicilian margin (southern Mediterranean). The considered habitats, already mapped in the area on a qualitative base, are the Posidonia oceanica and Cymodocea nodosa seagrasses and the Coralligenous biocenosis. Posidonia oceanica and Coralligenous are considered as VMEs owing to their value as environmental indicators and biodiversity hotspots in coastal marine areas. For this reason, several actions were aimed in recent years to their complete characterization and mapping. The study area is located in the continental shelf of the n…

MaxEnt geostatistical prediction Habitat mapping Vulnerable Marine EcosystemSettore GEO/02 - Geologia Stratigrafica E Sedimentologica
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Impact of Initial Soil Temperature Derived from Remote Sensing and Numerical Weather Prediction Datasets on the Simulation of Extreme Heat Events

2016

Extreme heat weather events have received increasing attention and has become of special importance as they can remarkably affect sectors as diverse as public health, energy consumption, water resources, natural biodiversity and agricultural production. In this regard, summer temperatures have become a parameter of essential interest under a framework of a hypothetical increase in the number of intense-heat conditions. Thus, their forecast is a crucial aspect bearing in mind a mitigation of the effects and impacts that these intense-heat situations could produce. The current work tries to reach a better understanding of these sorts of situations that are really common over the Western Medit…

Mediterranean climatesummer temperaturessoil temperature010504 meteorology & atmospheric sciencesMeteorologyNumerical weather prediction/forecasting0208 environmental biotechnology02 engineering and technology01 natural sciencesMesoscale modellingSea breezeSoil temperaturelcsh:ScienceSummer temperaturesExtreme heat0105 earth and related environmental sciencesRemote sensingLSTnumerical weather prediction/forecastingAdvectionextreme heatFísica de la TierraOrographyNumerical weather prediction020801 environmental engineeringWater resourcesCurrent (stream)ClimatologyRegional Atmospheric Modeling SystemRAMS model; extreme heat; LST; soil temperature; summer temperatures; mesoscale modelling; numerical weather prediction/forecastingRAMS modelGeneral Earth and Planetary SciencesEnvironmental sciencelcsh:Qmesoscale modelling
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A Dopaminergic Basis for Fear Extinction.

2019

It is a joyous relief when an event we dread fails to materialize. In fear extinction, the appetitive nature of an omitted aversive event is not a mere epiphenomenon but drives the reduction of fear responses and the formation of long-term extinction memories. Dopamine emerges as key neurobiological mediator of these related processes.

Memory Long-TermCognitive NeuroscienceEvent (relativity)Mean squared prediction errorDopamine05 social sciencesDopaminergicExperimental and Cognitive PsychologyEpiphenomenonsocial sciencesExtinction (psychology)Fearhumanities050105 experimental psychologyExtinction Psychological03 medical and health sciences0302 clinical medicineNeuropsychology and Physiological PsychologyAnimalsHumans0501 psychology and cognitive sciencesFear conditioningPsychologyNeuroscience030217 neurology & neurosurgeryTrends in cognitive sciences
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Implementation of non-local boundary layer schemes in the Regional Atmospheric Modeling System and its impact on simulated mesoscale circulations

2016

This paper proposes the implementation of different non-local Planetary Boundary Layer schemes within the Regional Atmospheric Modeling System (RAMS) model. The two selected PBL parameterizations are the Medium-Range Forecast (MRF) PBL and its updated version, known as the Yonsei University (YSU) PBL. YSU is a first-order scheme that uses non-local eddy diffusivity coefficients to compute turbulent fluxes. It is based on the MRF, and improves it with an explicit treatment of the entrainment. With the aim of evaluating the RAMS results for these PBL parameterizations, a series of numerical simulations have been performed and contrasted with the results obtained using the Mellor and Yamada (M…

Meteorologie en LuchtkwaliteitAtmospheric ScienceMeteorology and Air Quality010504 meteorology & atmospheric sciencesMeteorologyNumerical weather prediction/forecastingPlanetary boundary layer0208 environmental biotechnologyMesoscale meteorologyTerrain02 engineering and technology01 natural sciencesWind speedEddy diffusionMesoscale modelling0105 earth and related environmental sciencesNon-local schemesWIMEKFísica de la TierraEntrainment (meteorology)020801 environmental engineeringPBL parameterizationBoundary layerBoundary layerRegional Atmospheric Modeling SystemRAMS modelEnvironmental science
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Protein structure prediction assisted with sparse NMR data in CASP13

2019

CASP13 has investigated the impact of sparse NMR data on the accuracy of protein structure prediction. NOESY and 15 N-1 H residual dipolar coupling data, typical of that obtained for 15 N,13 C-enriched, perdeuterated proteins up to about 40 kDa, were simulated for 11 CASP13 targets ranging in size from 80 to 326 residues. For several targets, two prediction groups generated models that are more accurate than those produced using baseline methods. Real NMR data collected for a de novo designed protein were also provided to predictors, including one data set in which only backbone resonance assignments were available. Some NMR-assisted prediction groups also did very well with these data. CAS…

Models MolecularProtein FoldingMagnetic Resonance SpectroscopyProtein ConformationComputer scienceCrystallography X-RayBiochemistryArticle03 medical and health sciencesProtein structureStructural BiologyComputer SimulationCASPMolecular Biology030304 developmental biology0303 health sciences030302 biochemistry & molecular biologyProteinsReproducibility of ResultsRangingProtein structure predictionNmr dataData setResidual dipolar couplingTwo-dimensional nuclear magnetic resonance spectroscopyAlgorithmAlgorithmsProteins: Structure, Function, and Bioinformatics
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