Search results for "Diagram"

showing 10 items of 795 documents

Phase error analysis of clipped waveforms in surface topography measurement using projected fringes

2021

Abstract When working with the method of projected fringes outside the optical laboratory one often encounters the problem of uncontrollable ambient light. This might cause saturation of the camera which in turn results in clipping of the fringes. Since standard theories describing phase-shifting techniques assume the projected fringes to be purely sinusoidal, such clipping will result in measurement error. In this paper a detailed analysis of this problem is given, and relations between phase errors, the amount of fringe clipping and the number of phase steps are found. Moreover, the phase difference between the clipped and the unclipped fringes is described. This investigation is based on…

Signal processingProjected fringesOptical metrology3-D measurementPhase (waves)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology01 natural sciencesGeneralLiterature_MISCELLANEOUS010309 opticssymbols.namesakeOpticsClipping (photography)0103 physical sciencesWaveformProfilometryElectrical and Electronic EngineeringPhysical and Theoretical ChemistryPhase shiftMathematicsSignal processingObservational errorbusiness.industryPhasorAstrophysics::Instrumentation and Methods for Astrophysics021001 nanoscience & nanotechnologyAtomic and Molecular Physics and OpticsFourier analysisPhasor diagramsElectronic Optical and Magnetic MaterialsVDP::Teknologi: 500Fourier transformFourier analysissymbols0210 nano-technologybusiness
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How to Comprehend Large and Complicated Systems

2002

The basic problem at early analysis stage of the development life cycle is how to quickly comprehend a large and complicated system. One of the ways to comprehend such a system is to build an object model, as it was suggested by the pioneers of object modelling approach such as J.Rumbaugh1 and J.Martin2. In up-to-date terminology it means building a UML class diagram. The authors have got convinced in their everyday practice on extreme efficiency of this type of modelling, though at the same time a significant experience for this job is also required. To make this job easier, a modelling methodology must be developed. The goal of this paper is, on the one hand, to give some methodological r…

Software development processComputer sciencebusiness.industryObject modelClass diagramType (model theory)Software engineeringbusinessTerminologyEarly analysis
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Nomograph for rapid technical and economic assessment of solar thermal systems for DHW production

2012

Abstract Different types of tools, software and empirical methods to size and assess the performance of solar thermal systems are available today. A quick and easy-to-use graphical tool is proposed here. It is based on a single diagram, called a nomograph, which embeds technical and economic information, allowing the optimisation of the size and performance of a solar thermal system starting from the main input parameters, such as the specific costs of the system and the auxiliary fuel. The optimal surfaces are calculated as a function of the fuel cost through several regressions made on data from the application of the F-Chart method for a set of system configurations. The authors have fou…

Solar thermal system for DHW Performance evaluation Graphical tool for technical and economic assessment and optimisationSolar thermal system for DHWSettore ING-IND/11 - Fisica Tecnica AmbientaleRenewable Energy Sustainability and the Environmentbusiness.industryComputer scienceTotal costDiagramSample (statistics)Set (abstract data type)Graphical tool for technical and economic assessment and optimisationSoftwareThermalSolar thermal system for DHW; Performance evaluation; Graphical tool for technical and economic assessment and optimisationPerformance evaluationProduction (economics)General Materials Sciencesolar thermal systems rapid assessmentMacrobusinessProcess engineeringSolar Energy
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First-order and tricritical wetting transitions in the two-dimensional Ising model caused by interfacial pinning at a defect line

2014

We present a study of the critical behavior of the Blume-Capel model with three spin states (S=±1,0) confined between parallel walls separated by a distance L where competitive surface magnetic fields act. By properly choosing the crystal field (D), which regulates the density of nonmagnetic species (S=0), such that those impurities are excluded from the bulk (where D=) except in the middle of the sample [where DM(L/2)≠], we are able to control the presence of a defect line in the middle of the sample and study its influence on the interface between domains of different spin orientations. So essentially we study an Ising model with a defect line but, unlike previous work where defect lines …

Spin statesCiencias FísicasMateriales confinadosInterfacesPhase Transition//purl.org/becyt/ford/1 [https]ImpurityComputer SimulationSimulaciones computacionalesPhase diagramPhysicsCondensed matter physics//purl.org/becyt/ford/1.3 [https]Models TheoreticalFirst orderMagnetic fieldHysteresisMagnetic FieldsWettabilityThermodynamicsTransiciones de mojadoIsing modelWettingMonte Carlo MethodCIENCIAS NATURALES Y EXACTASFísica de los Materiales CondensadosPhysical Review E
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Monte Carlo studies of polymer interdiffusion and spinodal decomposition: A review

1991

Abstract Putting a layer of polymer A on top of a layer of polymer B, the broadening of the interfacial profile is observed in the framework of a lattice model (‘bond fluctuation method’). The interdiffusion constant is studied as a function of chain length, vacancy concentration, and interaction energy between unlike monomers, and a comparison with pertinent theoretical predictions is made. A lattice model where polymers are represented as self-avoiding walks on a simple cubic lattice is used to model ‘spinodal decomposition’, i.e. phase separation by ‘uphill diffusion’ in the unstable part of the phase diagram of a polymer mixture. For chain lengths N ≤ 32, the linearized Cahn-like theory…

SpinodalCondensed matter physicsSpinodal decompositionChemistryMonte Carlo methodInteraction energyCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsCondensed Matter::Soft Condensed MatterVacancy defectMaterials ChemistryCeramics and CompositesPolymer blendLattice model (physics)Phase diagramJournal of Non-Crystalline Solids
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Order-disorder-and order-order-transitions in AB and ABC block copolymers: description by a simple model

1996

Based on the description of AB-block copolymers as micellar structures given by Semenov, the phase diagram of AB-diblock copolymers is calculated taking the homogeneously mixed system as a reference state. The predicted value (χN)c = 10.385 for a symmetric AB-diblock copolymer compares very well to the result of the original Random Phase Approximation theory (10.495). The simplicity of the model allows its extension to predict order-order transitions in ABC-triblock copolymers.

SpinodalMaterials sciencePolymers and PlasticsValue (computer science)ThermodynamicsGeneral ChemistryState (functional analysis)Condensed Matter PhysicsSimple (abstract algebra)Materials ChemistryCopolymerOrder (group theory)Random phase approximationPhase diagramPolymer Bulletin
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Self-assembly of a bioelastomeric structure: solution dynamics and the spinodal and coacervation lines.

1990

The stability, metastability, and instability regions of aqueous solutions of a representative synthetic bioelastomeric polymer, poly (Val-Pro-Gly-Val-Gly), were determined by a combined use of elastic and quasi-elastic light scattering experiments. The approach followed here offers the attractive advantage of singling out the relevant contributions to the total scattering even in the presence of traces of noninteracting larger sized impurities. Conclusions so reached were checked by means of independent experiments. The present results provide descriptions of the very early events in the physics of bioelastogenesis in terms of general polymer science and phase transitions, and in terms of …

SpinodalPhase transitionChemical PhenomenaLightStereochemistryMolecular Sequence DataBiophysicsBiochemistryInstabilityLight scatteringBiomaterialsMolecular dynamicsMetastabilityScattering RadiationAmino Acid SequencePhase diagramQuantitative Biology::BiomoleculesScatteringChemistryChemistry PhysicalOrganic ChemistryTemperatureGeneral MedicineSolutionsChemical physicsPeptidesBiopolymers
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Phase diagrams calculated for flowing polymer solutions: spinodal and three phase conditions

1998

Spinodal lines and critical points (CPs) are calculated for flowing solutions of polystyrene in trans-decalin. Three types of CPs can be distinguished: The first consists of stable CPs (ordinary critical line) and originates from the CP of the quiescent system. The other two CPs are bound to shear. Additional stable CPs (extraordinary critical line) result for higher polymer concentrations and unstable CPs for intermediate concentrations. Ordinary and unstable critical line merge in a heterogeneous double CP. The coexistence of three phases in the flowing system (eulytic points) comes to an end as two of them merge upon an increase in shear rate at a critical end point.

SpinodalPolymers and PlasticsChemistryThermodynamicsGeneral ChemistryEntropy of mixingCondensed Matter Physicscomplex mixturesCritical point (mathematics)carbohydrates (lipids)Shear ratestomatognathic diseasesstomatognathic systemThree-phaseCritical linePhenomenological modelMaterials ChemistryPhase diagramPolymer Bulletin
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EMERGENCE OF TRAVELLING WAVES IN SMOOTH NERVE FIBRES

2008

International audience; An approximate analytical solution characterizing initial condi- tions leading to action potential ¯ring in smooth nerve ¯bres is determined, using the bistable equation. In the ¯rst place, we present a non-trivial sta- tionary solution wave. Then, we extract the main features of this solution to obtain a frontier condition between the initiation of the travelling waves and a decay to the resting state. This frontier corresponds to a separatrix in the projected dynamics diagram depending on the width and the amplitude of the stationary wave.

StationarityBistability[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS][ MATH.MATH-DS ] Mathematics [math]/Dynamical Systems [math.DS][ NLIN.NLIN-CD ] Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD][MATH.MATH-DS] Mathematics [math]/Dynamical Systems [math.DS]01 natural sciencesNerve fibresStanding waveOptics[ MATH.MATH-AP ] Mathematics [math]/Analysis of PDEs [math.AP]0103 physical sciencesTraveling wave[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]Discrete Mathematics and Combinatorics[MATH.MATH-AP] Mathematics [math]/Analysis of PDEs [math.AP]0101 mathematics010306 general physicsProjected dynamicsPhysicsSeparatrixbusiness.industry[SCCO.NEUR]Cognitive science/NeuroscienceApplied Mathematics[SCCO.NEUR] Cognitive science/NeuroscienceDiagramDynamics (mechanics)Mechanics010101 applied mathematics[NLIN.NLIN-CD] Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]Amplitude[NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD][ SCCO.NEUR ] Cognitive science/NeuroscienceAction potential firingbusinessAnalysis
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Response functions in multicomponent Luttinger liquids

2012

We derive an analytic expression for the zero temperature Fourier transform of the density-density correlation function of a multicomponent Luttinger liquid with different velocities. By employing Schwinger identity and a generalized Feynman identity exact integral expressions are derived, and approximate analytical forms are given for frequencies close to each component singularity. We find power-like singularities and compute the corresponding exponents. Numerical results are shown for the case of three components.

Statistics and ProbabilityBosonizationFOS: Physical sciences01 natural sciences010305 fluids & plasmassymbols.namesakeIdentity (mathematics)Condensed Matter - Strongly Correlated ElectronsSingularityCorrelation functionLuttinger liquid0103 physical sciencesFeynman diagramLuttinger liquids (theory)010306 general physics71.10.Pm 02.30.Nw 02.30.UuMathematical physicsPhysicsStrongly Correlated Electrons (cond-mat.str-el)Statistical and Nonlinear PhysicsFourier transformsymbolsGravitational singularityStatistics Probability and Uncertaintybosonization[PHYS.COND.CM-SCE]Physics [physics]/Condensed Matter [cond-mat]/Strongly Correlated Electrons [cond-mat.str-el]
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