Preparation and nonlinear optical properties of ultrathin composite films containing both a polyoxometalate anion and a binuclear phthalocyanine

An ultrathin composite film containing both polyoxometalate anion [PMo12O40](3-) ( PMo12) and a planar binuclear phthalocyanine, bi-CoPc, has been prepared by the electrostatic layer-by-layer self-assembly method. UV-vis measurements revealed regular film growth with each four-layer {PMo12/bi-CoPc/PSS/PAH} adsorption. The lm structure was characterized by small-angle X-ray reflectivity measurements, X-ray photoelectron spectra, and AFM images. The nanothick film shows a third-order nonlinear optical response of chi((3)) = 4.21 x 10(-12) esu. Experimental investigations also indicate that the combination of polyoxometalate anions [PMo12O40](3-) with the phthalocyanine bi-CoPc in multilayer films can enhance the third-order NLO susceptibility and modify the third-order NLO absorption of bi-CoPc.

降雨触发滑坡的非线性模型与斜坡演化的混沌效应

This paper analyzes landsliding process by nonlinear theories, especially the influence mechanism of external factors (such as rainfall and groundwater) on slope evolution. The author investigates landslide as a consequence of the catastrophic slide of initially stationary or creeping slope triggered by a small perturbation. A fully catastrophe analysis is done for all possible scenarios when a continuous change is imposed to the control parameters. As the slip surface continues and erosion due to rainfall occurs, control parameters of the slip surface may evolve such that a previously stable slope may become unstable (e.g. catastrophe occurs), when a small perturbation is imposed. Thus the present analysis offers a plausible explanation to why slope failure occurs at a particular rainfall, which is not the largest in the history of the slope. It is found, by analysis on the nonlinear dynamical model of the evolution process of slope built, that the relationship between the action of external environment factors and the response of the slope system is complicatedly nonlinear. When the nonlinear action of slope itself is equivalent to the acting ability of external environment, the chaotic phenomenon appears in the evolution process of slope, and its route leading to chaos is realized with bifurcation of period-doublings. On the basis of displacement time series of the slope, a nonlinear dynamic model is set up by improved Backus generalized linear inversion theory in this paper. Due to the equivalence between autonomous gradient system and catastrophe model, a standard cusp catastrophe model can be obtained through variable substitution. The method is applied to displacement data of Huangci landslide and Wolongsi landslide, to show how slopes evolve before landsliding. There is convincing statistical evidence to believe that the nonlinear dynamic model can make satisfied prediction results. Most important of all, we find that there is a sudden fall of D, which indicates the occurrence of catastrophe (when D=0).

Nonlinear piezoelectricity in electroelastic energy harvesters: Modeling and experimental identification

We propose and experimentally validate a first-principles based model for the nonlinear piezoelectric response of an electroelastic energy harvester. The analysis herein highlights the importance of modeling inherent piezoelectric nonlinearities that are not limited to higher order elastic effects but also include nonlinear coupling to a power harvesting circuit. Furthermore, a nonlinear damping mechanism is shown to accurately restrict the amplitude and bandwidth of the frequency response. The linear piezoelectric modeling framework widely accepted for theoretical investigations is demonstrated to be a weak presumption for near-resonant excitation amplitudes as low as 0.5 g in a prefabricated bimorph whose oscillation amplitudes remain geometrically linear for the full range of experimental tests performed (never exceeding 0.25% of the cantilever overhang length). Nonlinear coefficients are identified via a nonlinear least-squares optimization algorithm that utilizes an approximate analytic solution obtained by the method of harmonic balance. For lead zirconate titanate (PZT-5H), we obtained a fourth order elastic tensor component of c1111p =-3.6673× 1017 N/m2 and a fourth order electroelastic tensor value of e3111 =1.7212× 108 m/V. © 2010 American Institute of Physics.

Predicting the frequency dispersion of electronic hyperpolarizabilities on the basis of absorption data and thomas-kuhn sum rules

Successfully predicting the frequency dispersion of electronic hyperpolarizabilities is an unresolved challenge in materials science and electronic structure theory. We show that the generalized Thomas-Kuhn sum rules, combined with linear absorption data and measured hyperpolarizability at one or two frequencies, may be used to predict the entire frequency-dependent electronic hyperpolarizability spectrum. This treatment includes two- and three-level contributions that arise from the lowest two or three excited electronic state manifolds, enabling us to describe the unusual observed frequency dispersion of the dynamic hyperpolarizability in high oscillator strength M-PZn chromophores, where (porphinato)zinc(II) (PZn) and metal(II)polypyridyl (M) units are connected via an ethyne unit that aligns the high oscillator strength transition dipoles of these components in a head-to-tail arrangement. We show that some of these structures can possess very similar linear absorption spectra yet manifest dramatically different frequency dependent hyperpolarizabilities, because of three-level contributions that result from excited state-to excited state transition dipoles among charge polarized states. Importantly, this approach provides a quantitative scheme to use linear optical absorption spectra and very limited individual hyperpolarizability measurements to predict the entire frequency-dependent nonlinear optical response. Copyright © 2010 American Chemical Society.

A Fast Nonlinear Model Identification Method

The identification of nonlinear dynamic systems using linear-in-the-parameters models is studied. A fast recursive algorithm (FRA) is proposed to select both the model structure and to estimate the model parameters. Unlike orthogonal least squares (OLS) method, FRA solves the least-squares problem recursively over the model order without requiring matrix decomposition. The computational complexity of both algorithms is analyzed, along with their numerical stability. The new method is shown to require much less computational effort and is also numerically more stable than OLS.

Neural network controlled three-phase four-wire shunt active powerfilter

A three-phase four-wire shunt active power filter for harmonic mitigation and reactive power compensation in power systems supplying nonlinear loads is presented. Three adaptive linear neurons are used to tackle the desired three-phase filter current templates. Another feedforward three-layer neural network is adopted to control the output filter compensating currents online. This is accomplished by producing the appropriate switching patterns of the converter's legs IGBTs. Adequate tracking of the filter current references is obtained by this method. The active filter injects the current required to compensate for the harmonic and reactive components of the line currents, Simulation results of the proposed active filter indicate a remarkable improvement in the source current waveforms. This is reflected in the enhancement of the unified power quality index defined. Also, the filter has exhibited quite a high dynamic response for step variations in the load current, assuring its potential for real-time applications

Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.

Automated nonlinear system modelling with multiple neural networks

This article discusses the identification of nonlinear dynamic systems using multi-layer perceptrons (MLPs). It focuses on both structure uncertainty and parameter uncertainty, which have been widely explored in the literature of nonlinear system identification. The main contribution is that an integrated analytic framework is proposed for automated neural network structure selection, parameter identification and hysteresis network switching with guaranteed neural identification performance. First, an automated network structure selection procedure is proposed within a fixed time interval for a given network construction criterion. Then, the network parameter updating algorithm is proposed with guaranteed bounded identification error. To cope with structure uncertainty, a hysteresis strategy is proposed to enable neural identifier switching with guaranteed network performance along the switching process. Both theoretic analysis and a simulation example show the efficacy of the proposed method.

An investigation into the acceleration response of a damaged beam-type structure to a moving force

In recent years there have been a growing number of publications on procedures for damage detection in beams from analysing their dynamic response to the passage of a moving force. Most of this research demonstrates their effectiveness by showing that a singularity that did not appear in the healthy structure is present in the response of the damaged structure. This paper elucidates from first principles how the acceleration response can be assumed to consist of ‘static’ and ‘dynamic’ components, and where the beam has experienced a localised loss in stiffness, an additional ‘damage’ component. The combination of these components establishes how the damage singularity will appear in the total response. For a given damage severity, the amplitude of the ‘damage’ component will depend on how close the damage location is to the sensor, and its frequency content will increase with higher velocities of the moving force. The latter has implications for damage detection because if the frequency content of the ‘damage’ component includes bridge and/or vehicle frequencies, it becomes more difficult to identify damage. The paper illustrates how a thorough understanding of the relationship between the ‘static‘ and ‘damage’ components contributes to establish if damage has occurred and to provide an estimation of its location and severity. The findings are corroborated using accelerations from a planar finite element simulation model where the effects of force velocity and bridge span are examined.

Forward and backward least angle regression for nonlinear system identification

A forward and backward least angle regression (LAR) algorithm is proposed to construct the nonlinear autoregressive model with exogenous inputs (NARX) that is widely used to describe a large class of nonlinear dynamic systems. The main objective of this paper is to improve model sparsity and generalization performance of the original forward LAR algorithm. This is achieved by introducing a replacement scheme using an additional backward LAR stage. The backward stage replaces insignificant model terms selected by forward LAR with more significant ones, leading to an improved model in terms of the model compactness and performance. A numerical example to construct four types of NARX models, namely polynomials, radial basis function (RBF) networks, neuro fuzzy and wavelet networks, is presented to illustrate the effectiveness of the proposed technique in comparison with some popular methods.

Optimal dynamic control of laminated adaptive structures using a higher order model and a genetic algorithm

This paper deals with a finite element formulation based on the classical laminated plate theory, for active control of thin plate laminated structures with integrated piezoelectric layers, acting as sensors and actuators. The control is initialized through a previous optimization of the core of the laminated structure, in order to minimize the vibration amplitude. Also the optimization of the patches position is performed to maximize the piezoelectric actuator efficiency. The genetic algorithm is used for these purposes. The finite element model is a single layer triangular plate/shell element with 24 degrees of freedom for the generalized displacements, and one electrical potential degree of freedom for each piezoelectric element layer, which can be surface bonded or embedded on the laminate. To achieve a mechanism of active control of the structure dynamic response, a feedback control algorithm is used, coupling the sensor and active piezoelectric layers. To calculate the dynamic response of the laminated structures the Newmark method is considered. The model is applied in the solution of an illustrative case and the results are presented and discussed.

Análise estática não linear de um edifício em betão armado

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil

Estimating Nonlinear DSGE Models by the Simulated Method of Moments

This paper studies the application of the simulated method of moments (SMM) for the estimation of nonlinear dynamic stochastic general equilibrium (DSGE) models. Monte Carlo analysis is employed to examine the small-sample properties of SMM in specifications with different curvature. Results show that SMM is computationally efficient and delivers accurate estimates, even when the simulated series are relatively short. However, asymptotic standard errors tend to overstate the actual variability of the estimates and, consequently, statistical inference is conservative. A simple strategy to incorporate priors in a method of moments context is proposed. An empirical application to the macroeconomic effects of rare events indicates that negatively skewed productivity shocks induce agents to accumulate additional capital and can endogenously generate asymmetric business cycles.

Spectral and Nonlinear Optical Characteristics of ZnO Nanocomposites

The spectral and nonlinear optical properties of ZnO based nanocomposites prepared by colloidal chemical synthesis are investigated. Very strong UV emissions are observed from ZnO–Ag, ZnO– Cu and ZnO–SiO2 nanocomposites. The strongest visible emission of a typical ZnO–Cu nanocomposite is over ten times stronger than that of pure Cu due to transition from deep donor level to the copper induced level. The optical band gap of ZnO–CdS and ZnO–TiO2 nanocomposites is tunable and emission peaks changes almost in proportion to changes in band gap. Nonlinear optical response of these nanocomposites is studied using nanosecond laser pulses from a tunable laser in the wavelength range of 450–650 nm at resonance and off-resonance wavelengths. The nonlinear response is wavelength dependent and switching from RSA to SA has been observed at resonant wavelengths. Such a change-over is related to the interplay of plasmon/exciton band bleach and optical limiting mechanisms. The observed nonlinear absorption is explained through two photon absorption followed by weak free carrier absoption, interband absorption and nonlinear scattering mechanisms. The nonlinearity of the silica colloid is low and its nonlinear response can be improved by making composites with ZnO and ZnO–TiO2. The increase of the third-order nonlinearity in the composites can be attributed to the enhancement of exciton oscillator strength. This study is important in identifying the spectral range and the composition over which the nonlinear material acts as an RSA based optical limiter. These nanocomposites can be used as optical limiters and are potential materials for the light emission and for the development of nonlinear optical devices with a relatively small limiting threshold.

Spectral and Nonlinear Optical Characteristics of ZnO Nanocomposites

The spectral and nonlinear optical properties of ZnO based nanocomposites prepared by colloidal chemical synthesis are investigated. Very strong UV emissions are observed from ZnO–Ag, ZnO– Cu and ZnO–SiO2 nanocomposites. The strongest visible emission of a typical ZnO–Cu nanocomposite is over ten times stronger than that of pure Cu due to transition from deep donor level to the copper induced level. The optical band gap of ZnO–CdS and ZnO–TiO2 nanocomposites is tunable and emission peaks changes almost in proportion to changes in band gap. Nonlinear optical response of these nanocomposites is studied using nanosecond laser pulses from a tunable laser in the wavelength range of 450–650 nm at resonance and off-resonance wavelengths. The nonlinear response is wavelength dependent and switching from RSA to SA has been observed at resonant wavelengths. Such a change-over is related to the interplay of plasmon/exciton band bleach and optical limiting mechanisms. The observed nonlinear absorption is explained through two photon absorption followed by weak free carrier absoption, interband absorption and nonlinear scattering mechanisms. The nonlinearity of the silica colloid is low and its nonlinear response can be improved by making composites with ZnO and ZnO–TiO2. The increase of the third-order nonlinearity in the composites can be attributed to the enhancement of exciton oscillator strength. This study is important in identifying the spectral range and the composition over which the nonlinear material acts as an RSA based optical limiter. These nanocomposites can be used as optical limiters and are potential materials for the light emission and for the development of nonlinear optical devices with a relatively small limiting threshold.