Search results for "Multilayer"

showing 10 items of 141 documents

High-fidelity analysis of multilayered shells with cut-outs via the discontinuous Galerkin method

2021

Abstract A novel numerical method for the analysis of multilayered shells with cut-outs is presented. In the proposed approach, the shell geometry is represented via either analytical functions or NURBS parametrizations , while generally-shaped cut-outs are defined implicitly within the shell modelling domain via a level set function . The multilayered shell problem is addressed via the Equivalent-Single-Layer approach whereby high-order polynomial functions are employed to approximate the covariant components of the displacement field throughout the shell thickness. The shell governing equations are then derived from the Principle of Virtual Displacements of three-dimensional elasticity an…

DiscretizationNumerical analysisMathematical analysisShell (structure)Finite element methodQuadrature (mathematics)Discontinuous Galerkin methodDisplacement fieldCeramics and CompositesCut-outs High-order modeling Implicit mesh Interior Penalty discontinuous Galerkin Multilayered shells NURBSSettore ING-IND/04 - Costruzioni E Strutture AerospazialiCivil and Structural EngineeringAnalytic functionMathematicsComposite Structures
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A multilayer anisotropic plate model with warping functions for the study of vibrations reformulated from Woodcock's work

2013

Abstract In this paper, a suitable model for static and dynamic analysis of inhomogeneous anisotropic multilayered plates is described. This model takes into account the variations of the transverse shear strains through the thickness of the plate by means of warping functions. Warping functions are determined by enforcing kinematic and static assumptions at the interfaces. This model leads to: a 10×10 stiffness matrix coupling to each other the membrane strains, the bending and torsion curvatures, and the x and y-derivatives of the transverse shear strains; and a classical 2×2 transverse shear stiffness matrix. This model has been proven to be very efficient, especially when high ratios be…

EngineeringAcoustics and Ultrasonics[ SPI.MECA.STRU ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of the structures [physics.class-ph]FOS: Physical sciencesKinematicsPhysics - Classical Physics[ PHYS.MECA.STRU ] Physics [physics]/Mechanics [physics]/Mechanics of the structures [physics.class-ph]Deflection (engineering)laminateImage warpingStiffness matrixMultilayeredmodelbusiness.industryMechanical EngineeringplateIsotropyMathematical analysiswarping functionsClassical Physics (physics.class-ph)Torsion (mechanics)Equations of motionStructural engineeringCondensed Matter PhysicsPACS : 46.40.-f ; 46.70.De[SPI.MECA.STRU]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of the structures [physics.class-ph]Mechanics of Materials[PHYS.MECA.STRU]Physics [physics]/Mechanics [physics]/Mechanics of the structures [physics.class-ph]Displacement fieldvibrationbusiness
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Structural Health Monitoring Procedure for Composite Structures through the use of Artificial Neural Networks

2015

In this paper different architectures of Artificial Neural Networks (ANNs) for structural damage detection are studied. The main objective is to investigate an ANN able to detect and localize damage without any prior knowledge on its characteristics so as to serve as a real-time data processor for Structural Health Monitoring (SHM) systems. Two different architectures are studied: the standard feed-forward Multi Layer Perceptron (MLP) and the Radial Basis Function (RBF) ANNs. The training data are given, in terms of a Damage Index ℑD, properly defined using a piezoelectric sensor signal output to obtain suitable information on the damage position and dimensions. The electromechanical respon…

EngineeringArtificial neural networkBasis (linear algebra)Piezoelectric sensorbusiness.industryComputer Science::Neural and Evolutionary ComputationPattern recognitionStructural engineeringData processing systemMultilayer perceptronPharmacology (medical)Radial basis functionArtificial intelligenceStructural health monitoringbusinessBoundary element methodAerotecnica Missili & Spazio
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Electronic noses: a review of signal processing techniques

1999

The field of electronic noses, electronic instruments capable of mimicking the human olfactory system, has developed rapidly in the past ten years. There are now at least 25 research groups working in this area and more than ten companies have developed commercial instruments, which are mainly employed in the food and cosmetics industries. Most of the work published to date, and commercial applications, relate to the use of well established static pattern analysis techniques, such as principal components analysis, discriminant function analysis, cluster analysis and multilayer perceptron based neural networks. The authors first review static techniques that have been applied to the steady-s…

EngineeringSignal processingArtificial neural networkElectronic nosebusiness.industrySystem identificationcomputer.software_genreField (computer science)Sensor arrayMultilayer perceptronArtificial intelligenceData miningElectrical and Electronic EngineeringbusinesscomputerLinear filterIEE Proceedings - Circuits, Devices and Systems
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Study of the reactive dynamics of nanometric metallic multilayers using Molecular Dynamics: the Al−Ni system

2012

A molecular dynamics study of a layered Ni-Al-Ni system is developed using an embedded atom method potential. The specific geometry is designed to model a Ni-Al nanometric metallic multilayer. The system is initially thermalized at the fixed temperature of 600 K. We first observe the interdiffusion of Ni and Al at the interfaces, which is followed by the spontaneous phase formation of B2-NiAl in the Al layer. The solid-state reaction is associated with a rapid system's heating which further enhances the diffusion processes. NiAl phase is organized in small regions separated by grain boundaries. This study confirms the hypothesis of a layer-by-layer development of the new phase. For longer t…

Exothermic reactionNialMaterials scienceDiffusionmultilayersIntermetallicnanometric metallic multilayersNanotechnology02 engineering and technology01 natural sciencesinterfacesMolecular dynamicsPhase (matter)0103 physical sciencesGeneral Materials Scienceintermetallics010306 general physicscomputer.programming_languageRadiationnanoscale effects[CHIM.MATE]Chemical Sciences/Material chemistry021001 nanoscience & nanotechnologyCondensed Matter PhysicsMicrostructuremolecular dynamics[ PHYS.PHYS.PHYS-CHEM-PH ] Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph]Chemical physics[ CHIM.MATE ] Chemical Sciences/Material chemistryGrain boundary[PHYS.PHYS.PHYS-CHEM-PH]Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph]0210 nano-technologycomputer
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Finite elements for nonlinear free vibrations analysis of smart laminates subjected to in-plane loadings

2015

Advanced composites, able to provide multi-functional capabilities besides the traditional structural functions, has been gaining attention in many technological fields. This inherent coupling of different physical fields can be exploited in transducer applications, structural health monitoring, vibration control, energy harvesting and other applications. Magneto-electro-elastic (MEE) composite materials are attracting increasing consideration as they couple mechanical, electrical and magnetic fields and this makes them particularly suitable for smart applications. Generally, single-phase materials exhibit either piezoelectric or piezomagnetic behavior and no direct magneto-electric couplin…

Finite elements multilayered structures smart structures magnetoelectroelastic laminatesSettore ING-IND/04 - Costruzioni E Strutture Aerospaziali
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An efficient data model for energy prediction using wireless sensors

2019

International audience; Energy prediction is in high importance for smart homes and smart cities, since it helps reduce power consumption and provides better energy and cost savings. Many algorithms have been used for predicting energy consumption using data collected from Internet of Things (IoT) devices and wireless sensors. In this paper, we propose a system based on Multilayer Perceptron (MLP) to predict energy consumption of a building using collected information (e.g., light energy, day of the week, humidity, temperature, etc.) from a Wireless Sensor Network (WSN). We compare our system against four other classification algorithms, namely: Linear Regression (LR), Support Vector Machin…

General Computer ScienceMean squared errorComputer scienceReal-time computing02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]7. Clean energy[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0202 electrical engineering electronic engineering information engineeringElectrical and Electronic Engineering020206 networking & telecommunicationsEnergy consumption[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationRandom forestSupport vector machineMean absolute percentage error13. Climate actionControl and Systems Engineering[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Multilayer perceptron020201 artificial intelligence & image processing[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Gradient boosting[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Wireless sensor network
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A Novel Systolic Parallel Hardware Architecture for the FPGA Acceleration of Feedforward Neural Networks

2019

New chips for machine learning applications appear, they are tuned for a specific topology, being efficient by using highly parallel designs at the cost of high power or large complex devices. However, the computational demands of deep neural networks require flexible and efficient hardware architectures able to fit different applications, neural network types, number of inputs, outputs, layers, and units in each layer, making the migration from software to hardware easy. This paper describes novel hardware implementing any feedforward neural network (FFNN): multilayer perceptron, autoencoder, and logistic regression. The architecture admits an arbitrary input and output number, units in la…

Hardware architectureFloating pointGeneral Computer ScienceArtificial neural networkComputer scienceClock rateActivation functionGeneral EngineeringSistemes informàticsAutoencoderArquitectura d'ordinadorsComputational scienceneural network accelerationFPGA implementationdeep neural networksMultilayer perceptronFeedforward neural networks - FFNNFeedforward neural networkXarxes neuronals (Informàtica)General Materials Sciencelcsh:Electrical engineering. Electronics. Nuclear engineeringlcsh:TK1-9971systolic hardware architectureIEEE Access
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Optimization of ZnO:Al/Ag/ZnO:Al structures for ultra-thin high-performance transparent conductive electrodes

2012

Al-doped ZnO (AZO)/Ag/AZO multilayer coatings (50-70 nm thick) were grown at room temperature on glass substrates with different silver layer thickness, from 3 to 19 nm, by using radio frequency magnetron sputtering. Thermal stability of the compositional, optical and electrical properties of the AZO/Ag/AZO structures were investigated up to 400 °C and as a function of Ag film thickness. An AZO film as thin as 20 nm is an excellent barrier to Ag diffusion. The inclusion of 9.5 nm thin silver layer within the transparent conductive oxide (TCO) material leads to a maximum enhancement of the electro-optical characteristics. The excellent measured properties of low resistance, high transmittanc…

High transmittanceDiffusionrf-Magnetron sputteringElectro-optical characteristicGlass substrateTransparent conductive oxide RF magnetron sputtering Optical properties Electrical resistivity Al-doped zinc oxide Silver MultilayersSettore ING-INF/01 - ElettronicaSUBSTRATE-TEMPERATUREAg diffusionAl-doped ZnOLow resistanceMultilayerZNOMaterials ChemistryVisible spectral rangeMULTILAYER FILMSAl-doped zinc oxideOptical propertiesMetals and AlloysAZO filmElectrical resistivityOPTICAL-PROPERTIESOXIDE-FILMSSurfaces and InterfacesZinc oxide AluminumRadio frequency magnetron sputteringSurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsOptical and electrical propertieElectrodeOptoelectronicsFilm preparationLayer (electronics)Magnetron sputteringUltra-thinRF magnetron sputteringMaterials scienceSilverThermodynamic stabilityOpticsTransparent conductive oxideElectrical resistivity and conductivityThermal stabilityElectrical conductorTransparent conducting filmRoom temperatureThin film solar cellbusiness.industryTransparent conductiveOptical propertieSilver layerHigh transmittanceMultilayersMulti-layer-coatingZnO Electric conductivityMeasured propertiebusinessSubstrate
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Polymer/metal hybrid multilayers modified Schottky devices

2013

Insulating, polymethylmethacrylate (PMMA), and semiconducting, poly(3-hexylthiophene) (P3HT), nanometer thick polymers/Au nanoparticles based hybrid multilayers (HyMLs) were fabricated on p-Si single-crystal substrate. An iterative method, which involves, respectively, spin-coating (PMMA and P3HT deposition) and sputtering (Au nanoparticles deposition) techniques to prepare Au/HyMLs/p-Si Schottky device, was used. The barrier height and the ideality factor of the Au/HyMLs/p-Si Schottky devices were investigated by current-voltage measurements in the thickness range of 1-5 bilayers. It was observed that the barrier height of such hybrid layered systems can be tuned as a function of bilayers …

Ideality factorMaterials sciencePhysics and Astronomy (miscellaneous)Layered systemNanoparticleSilicon GoldNanotechnologySingle-crystal substrates DepositionSubstrate (electronics)Poly-3-hexylthiopheneSettore ING-INF/01 - ElettronicaSettore FIS/03 - Fisica Della MateriaNanoparticleSputteringPolymer; Au nanoparticles; Schottky devicePolymerHybrid multilayerConductive polymerSpin coatingbusiness.industryBarrier heightSchottky diodeSputter depositionCurrent-voltage measurementSemiconducting siliconSchottky deviceOptoelectronicsSelf-assemblybusinessAu nanoparticles
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