116 resultados para Strong finite model property


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The technique of externally bonding fibre reinforced polymer (FRP) composites has been becoming popular worldwide for retrofitting existing reinforced concrete (RC) structures. A major failure mode in such strengthened structures is the debonding of FRP from the concrete substrate. The bond behaviour between FRP and concrete thus plays a crucial role in these structures. The FRP-to-concrete bond behaviour has been extensively investigated experimentally, commonly using the pull-off test of FRP-to-concrete bonded joint. Comparatively, much less research has been concerned with the numerical simulation of this bond behaviour, chiefly due to difficulties in accurately modelling the complex behaviour of concrete. This paper proposes a robust finite element (FE) model for simulating the bond behaviour in the entire loading process in the pull-off test. A concrete damage plasticity model based on the plastic degradation theory is proposed to overcome the weakness of the elastic degradation theory which has been commonly adopted in previous studies. The model produces results in very close agreement with test data. © Tsinghua University Press, Beijing and Springer-Verlag Berlin Heidelberg 2011.

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Tanpura string vibrations have been investigated previously using numerical models based on energy conserving schemes derived from a Hamiltonian description in one-dimensional form. Such time-domain models have the property that, for the lossless case, the numerical Hamiltonian (representing total energy of the system) can be proven to be constant from one time step
to the next, irrespective of any of the system parameters; in practice the Hamiltonian can be shown to be conserved within machine precision. Models of this kind can reproduce a jvari effect, which results from the bridge-string interaction. However the one-dimensional formulation has recently been shown to fail to replicate the jvaris strong dependence on the thread placement. As a first step towards simulations which accurately emulate this sensitivity to the thread placement, a twodimensional model is proposed, incorporating coupling of controllable level between the two string polarisations at the string termination opposite from the barrier. In addition, a friction force acting when the string slides across the bridge in horizontal direction is introduced, thus effecting a further damping mechanism. In this preliminary study, the string is terminated at the position of the thread. As in the one-dimensional model, an implicit scheme has to be used to solve the system, employing Newton's method to calculate the updated positions and momentums of each string segment. The two-dimensional model is proven to be energy conserving when the loss parameters are set to zero, irrespective of the coupling constant. Both frequency-dependent and independent losses are then added to the string, so that the model can be compared to analogous instruments. The influence of coupling and the bridge friction are investigated.

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This study presents a fully coupled temperature–displacement finite element modelling of the injection stretch-blow moulding (ISBM) process of polyethylene terephthalate (PET) bottles using ABAQUS with a view to optimising the process conditions. A physically-based material model (Buckley model) was used to predict the mechanical behaviour of PET at temperatures slightly above its glass transition temperature. A model incorporating heat transfer between the stretch rod, the preform and the mould was built using axisymmetric solid elements. Extensive finite element analyses were carried out to predict the deformation, the distribution and history of strain and temperature during ISBM of a 20 g–330 ml bottle, which was made in an in situ test on a Sidel SB06 machine. Comparisons of numerical results with the measurements demonstrate that the model can satisfactorily model the sidewall thickness and material distributions. It is also shown that significant non-linear differentials exist in temperature and strain in both bottle thickness and length directions during the process. This justifies the employment of a volume approach to accurately predict the final mechanical properties of the bottles governed by the orientation and crystallinity which are highly temperature and strain dependent.

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This paper describes the development of a two-dimensional transient catalyst model. Although designed primarily for two-stroke direct injection engines, the model is also applicable to four-stroke lean burn and diesel applications. The first section describes the geometries, properties and chemical processes simulated by the model and discusses the limitations and assumptions applied. A review of the modeling techniques adopted by other researchers is also included. The mathematical relationships which are used to represent the system are then described, together with the finite volume method used in the computer program. The need for a two-dimensional approach is explained and the methods used to model effects such as flow and temperature distribution are presented. The problems associated with developing surface reaction rates are discussed in detail and compared with published research. Validation and calibration of the model is achieved by comparing predictions with measurements from a flow reactor. While an extensive validation process, involving detailed measurements of gas composition and thermal gradients, has been completed, the analysis is too detailed for publication here and is the subject of a separate technical paper.

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The ultrasonic measurement and imaging of tissue elasticity is currently under wide investigation and development as a clinical tool for the assessment of a broad range of diseases, but little account in this field has yet been taken of the fact that soft tissue is porous and contains mobile fluid. The ability to squeeze fluid out of tissue may have implications for conventional elasticity imaging, and may present opportunities for new investigative tools. When a homogeneous, isotropic, fluid-saturated poroelastic material with a linearly elastic solid phase and incompressible solid and fluid constituents is subjected to stress, the behaviour of the induced internal strain field is influenced by three material constants: the Young's modulus (E(s)) and Poisson's ratio (nu(s)) of the solid matrix and the permeability (k) of the solid matrix to the pore fluid. New analytical expressions were derived and used to model the time-dependent behaviour of the strain field inside simulated homogeneous cylindrical samples of such a poroelastic material undergoing sustained unconfined compression. A model-based reconstruction technique was developed to produce images of parameters related to the poroelastic material constants (E(s), nu(s), k) from a comparison of the measured and predicted time-dependent spatially varying radial strain. Tests of the method using simulated noisy strain data showed that it is capable of producing three unique parametric images: an image of the Poisson's ratio of the solid matrix, an image of the axial strain (which was not time-dependent subsequent to the application of the compression) and an image representing the product of the aggregate modulus E(s)(1-nu(s))/(1+nu(s))(1-2nu(s)) of the solid matrix and the permeability of the solid matrix to the pore fluid. The analytical expressions were further used to numerically validate a finite element model and to clarify previous work on poroelastography.

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Electron energy distributions of singly and doubly ionized helium in an intense 390 nm laser field have been measured at two intensities (0.8 PW/cm(2) and 1.1 PW/cm(2), where PW equivalent to 10(15) W/cm(2)). Numerical solutions of the full-dimensional time-dependent helium Schrodinger equation show excellent agreement with the experimental measurements. The high-energy portion of the two-electron energy distributions reveals an unexpected 5U(p) cutoff for the double ionization (DI) process and leads to a proposed model for DI below the quasiclassical threshold.

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Heavy particle collisions, in particular low-energy ion-atom collisions, are amenable to semiclassical JWKB phase integral analysis in the complex plane of the internuclear separation. Analytic continuation in this plane requires due attention to the Stokes phenomenon which parametrizes the physical mechanisms of curve crossing, non-crossing, the hybrid Nikitin model, rotational coupling and predissociation. Complex transition points represent adiabatic degeneracies. In the case of two or more such points, the Stokes constants may only be completely determined by resort to the so-called comparison- equation method involving, in particular, parabolic cylinder functions or Whittaker functions and their strong-coupling asymptotics. In particular, the Nikitin model is a two transition-point one-double-pole problem in each half-plane corresponding to either ingoing or outgoing waves. When the four transition points are closely clustered, new techniques are required to determine Stokes constants. However, such investigations remain incomplete, A model problem is therefore solved exactly for scattering along a one-dimensional z-axis. The energy eigenvalue is b(2)-a(2) and the potential comprises -z(2)/2 (parabolic) and -a(2) + b(2)/2z(2) (centrifugal/centripetal) components. The square of the wavenumber has in the complex z-plane, four zeros each a transition point at z = +/-a +/- ib and has a double pole at z = 0. In cases (a) and (b), a and b are real and unitarity obtains. In case (a) the reflection and transition coefficients are parametrized by exponentials when a(2) + b(2) > 1/2. In case (b) they are parametrized by trigonometrics when a(2) + b(2) <1/2 and total reflection is achievable. In case (c) a and b are complex and in general unitarity is not achieved due to loss of flux to a continuum (O'Rourke and Crothers, 1992 Proc. R. Sec. 438 1). Nevertheless, case (c) coefficients reduce to (a) or (b) under appropriate limiting conditions. Setting z = ht, with h a real constant, an attempt is made to model a two-state collision problem modelled by a pair of coupled first-order impact parameter equations and an appropriate (T) over tilde-tau relation, where (T) over tilde is the Stueckelberg variable and tau is the reduced or scaled time. The attempt fails because (T) over tilde is an odd function of tau, which is unphysical in a real collision problem. However, it is pointed out that by applying the Kummer exponential model to each half-plane (O'Rourke and Crothers 1994 J. Phys. B: At. Mel. Opt. Phys. 27 2497) the current model is in effect extended to a collision problem with four transition points and a double pole in each half-plane. Moreover, the attempt in itself is not a complete failure since it is shown that the result is a perfect diabatic inelastic collision for a traceless Hamiltonian matrix, or at least when both diagonal elements are odd and the off-diagonal elements equal and even.

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We describe an empirical, self-consistent, orthogonal tight-binding model for zirconia, which allows for the polarizability of the anions at dipole and quadrupole levels and for crystal field splitting of the cation d orbitals, This is achieved by mixing the orbitals of different symmetry on a site with coupling coefficients driven by the Coulomb potentials up to octapole level. The additional forces on atoms due to the self-consistency and polarizabilities are exactly obtained by straightforward electrostatics, by analogy with the Hellmann-Feynman theorem as applied in first-principles calculations. The model correctly orders the zero temperature energies of all zirconia polymorphs. The Zr-O matrix elements of the Hamiltonian, which measure covalency, make a greater contribution than the polarizability to the energy differences between phases. Results for elastic constants of the cubic and tetragonal phases and phonon frequencies of the cubic phase are also presented and compared with some experimental data and first-principles calculations. We suggest that the model will be useful for studying finite temperature effects by means of molecular dynamics.

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The results of PVT measurements of the liquid phase within the temperature range of (298 to 393) K and up to 35 MPa are presented for some aliphatic esters. Measurements were made by means of a vibrating-tube densimeter, model DMA 512P from Anton Parr. The calibration of the densimeter was performed with water and n-heptane as reference fluids. The experimental PVT data have been correlated by a Tait equation. This equation gives excellent results when used to predict the density of the esters using the method proposed by Thomson et al. (AIChE J. 1982, 28, 671-676). Isothermal compressibilities, isobaric expansivities, thermal pressure coefficients, and changes in the isobaric heat capacity have been calculated from the volumetric data.

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The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

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This paper exposes the strengths and weaknesses of the recently proposed velocity-based local model (LM) network. The global dynamics of the velocity-based blended representation are directly related to the dynamics of the underlying local models, an important property in the design of local controller networks. Furthermore, the sub-models are continuous-time and linear providing continuity with established linear theory and methods. This is not true for the conventional LM framework, where the global dynamics are only weakly related to the affine sub-models. In this paper, a velocity-based multiple model network is identified for a highly nonlinear dynamical system. The results show excellent dynamical modelling performances, highlighting the value of the velocity-based approach for the design and analysis of LM based control. Three important practical issues are also addressed. These relate to the blending of the velocity-based local models, the use of normalised Gaussian basis functions and the requirement of an input derivative.

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Voltammetric studies of the reduction of oxygen in the room temperature ionic liquid [C(4)dmim][N(Tf)(2)] have revealed a significant positive shift in the back peak potential, relative to that expected for a simple electron transfer. This shift is thought to be due to the strong association of the electrogenerated superoxide anion with the solvent cation. In this work we quantitatively simulate the microdisc electrode voltammetry using a model based upon a one-electron reduction followed by a reversible chemical step, involving the formation of the [C(4)dmim](+)center dot center dot center dot O-2(center dot-) ion-pair, and in doing so we extract a set of parameters completely describing the system. We have simulated the voltammetry in the absence of a following chemical step and have shown that it is impossible to simultaneously fit both the forward and reverse peaks. To further support the parameters extracted from fitting the experimental voltammetry, we have used these parameters to independently simulate the double step chronoamperometric response and found excellent agreement. The parameters used to describe the association of the O-2(center dot-) with the [C(4)dmim](+) were k(f) = 1.4 x 10(3) s(-1) for the first-order rate constant and K-eq = 25 for the equilibrium constant.

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Voltammetry is reported for chlorine, Cl-2, dissolved in various room temperature ionic liquids using platinum microdisk electrodes. A single reductive voltammetric wave is seen and attributed to the two-electron reduction of chlorine to chloride. Studies of the effect of voltage scan rate reveal uniquely unusual behavior in which the magnitude of the currents decrease with increasing scan rates. A model for this is proposed and shown to indicate the presence of strongly adsorbed species in the electrode reaction mechanism, most likely chlorine atoms, Cl*((ads)).

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Thecamoebians were examined from 71 surface sediment samples collected from 21 lakes and ponds in the Greater Toronto Area to (1) elucidate the controls on faunal distribution in modern lake environments; and (2) to consider the utility of thecamoebians in quantitative studies of water quality change. This area was chosen because it includes a high density of kettle and other lakes which are threatened by urban development and where water quality has deteriorated locally as a result of contaminant inputs, particularly nutrients. Fifty-eight samples yielded statistically significant thecamoebian populations. The most diverse faunas (highest Shannon Diversity Index values) were recorded in lakes beyond the limits of urban development, although the faunas of all lakes showed signs of sub-optimal conditions. The assemblages were divided into five clusters using Q-mode cluster analysis, supported by Detrended Correspondence Analysis. Canonical Correspondence Analysis (CCA) was used to examine species-environment relationships and to explain the observed clusterings. Twenty-four measured environmental variables were considered, including water property attributes (e.g., pH, conductivity, dissolved oxygen), substrate characteristics, sediment-based phosphorus (Olsen P) and 11 environmentally available metals. The thecamoebian assemblages showed a strong association with phosphorus, reflecting the eutrophic status of many of the lakes, and locally to elevated conductivity measurements, which appear to reflect road salt inputs associated with winter de-icing operations. Substrate characteristics, total organic carbon and metal contaminants (particularly Cu and Mg) also influenced the faunas of some samples. A series of partial CCAs show that of the measured variables, sedimentary phosphorus has the largest influence on assemblage distribution, explaining 6.98% (P < 0.002) of the total variance. A transfer function was developed for sedimentary phosphorus (Olsen P) using 58 samples from 15 of the studied lakes. The best performing model was based on weighted averaging with inverse deshrinking (WA Inv, r jack 2= 0.33, RMSEP = 102.65 ppm). This model was applied to a small modern thecamoebian dataset from a eutrophic lake in northern Ontario to predict phosphorus and performed satisfactorily. This preliminary study confirms that thecamoebians have considerable potential as quantitative water quality indicators in urbanising regions, particularly in areas influenced by nutrient inputs and road salts.

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This study explores using artificial neural networks to predict the rheological and mechanical properties of underwater concrete (UWC) mixtures and to evaluate the sensitivity of such properties to variations in mixture ingredients. Artificial neural networks (ANN) mimic the structure and operation of biological neurons and have the unique ability of self-learning, mapping, and functional approximation. Details of the development of the proposed neural network model, its architecture, training, and validation are presented in this study. A database incorporating 175 UWC mixtures from nine different studies was developed to train and test the ANN model. The data are arranged in a patterned format. Each pattern contains an input vector that includes quantity values of the mixture variables influencing the behavior of UWC mixtures (that is, cement, silica fume, fly ash, slag, water, coarse and fine aggregates, and chemical admixtures) and a corresponding output vector that includes the rheological or mechanical property to be modeled. Results show that the ANN model thus developed is not only capable of accurately predicting the slump, slump-flow, washout resistance, and compressive strength of underwater concrete mixtures used in the training process, but it can also effectively predict the aforementioned properties for new mixtures designed within the practical range of the input parameters used in the training process with an absolute error of 4.6, 10.6, 10.6, and 4.4%, respectively.