Derivation of equivalent linear properties of Bouc-Wen hysteretic systems for seismic response spectrum analysis via statistical linearization

A newly proposed statistical linearization based formulation is used to derive effective linear properties (ELPs), namely damping ratio and natural frequency, for stochastically excited hysteretic oscillatorsinvolving the Bouc-Wen force-deformation phenomenological model. This is achieved by first using a frequency domain statistical linearization step to substitute a Bouc-Wen oscillator by a third order linear system. Next, this third order linear system is reduced to a second order linear oscillator characterized by a set of ELPs by enforcing equality of certain response statistics of the two linear systems. The proposed formulation is utilized in conjunction with quasi-stationary stochastic processes compatible with elastic response spectra commonly used to represent the input seismic action in earthquake resistant design of structures. Then, the derived ELPs are used to estimate the peak response of Bouc-Wen hysteretic oscillators without numerical integration of the nonlinear equation of motion; this is done in the context of linear response spectrum-based dynamic analysis. Numerical results pertaining to the elastic response spectrum of the current European aseismic code provisions (EC8) are presented to demonstrate the usefulness of the proposed approach. These results are supported by pertinent Monte Carlo simulations involving an ensemble of non-stationary EC8 spectrum compatible accelerograms. The proposed approach can hopefully be an effective tool in the preliminary aseismic design stages of yielding structures and structural members commonly represented by the Bouc-Wen hysteretic model within either a force-based or a displacement-based context

The bilinear method:a new stability-preserving order reduction approach

A new way of reducing the order of linear system transfer functions is presented. It guarantees stability in the approximation of stable systems and differs from existing stability-preserving methods by taking into account whole system parameter information when obtaining the approximate poles, not just that of the system poles. It uses a bilinear transformation in the process, which renders the method more flexible than traditional techniques. Examples are given to highlight the advantages of the new approach

Empirical balanced truncation of nonlinear systems

Novel constructions of empirical controllability and observability gramians for nonlinear systems for subsequent use in a balanced truncation style of model reduction are proposed. The new gramians are based on a generalisation of the fundamental solution for a Linear Time-Varying system. Relationships between the given gramians for nonlinear systems and the standard gramians for both Linear Time-Invariant and Linear Time-Varying systems are established as well as relationships to prior constructions proposed for empirical gramians. Application of the new gramians is illustrated through a sample test-system.Comment: LaTeX, 11 pages, 2 figure

A note on modeling some classes of nonlinear systems from data

We study the modeling of bilinear and quadratic systems from measured data. The measurements are given by samples of higher order frequency response functions. These values can be identified from the corresponding Volterra series of the underlying nonlinear system. We test the method for examples from structural dynamics and chemistry

Model structure detection and system identification of metal rubber devices

Metal rubber (MR) devices, a new wire mesh material, have been extensively used in recent years due to several unique properties especially in adverse environments. Although many practical studies have been completed, the related theoretical research on metal rubber is still in its infancy. In this paper, a semi-constitutive dynamic model that involves nonlinear elastic stiffness, nonlinear viscous damping and bilinear hysteresis Coulomb damping is adopted to model MR devices. After approximating the bilinear hysteresis damping using Chebyshev polynomials of the first kind, a very efficient procedure based on the orthogonal least squares (OLS) algorithm and the adjustable prediction error sum of squares (APRESS) criterion is proposed for model structure detection and parameter estimation of an MR device for the first time. The OLS algorithm provides a powerful tool to effectively select the significant model terms step by step, one at a time, by orthogonalizing the associated terms and maximizing the error reduction ratio, in a forward stepwise procedure. The APRESS statistic regularizes the OLS algorithm to facilitate the determination of the optimal number of model terms that should be included into the dynamic model. Because of the orthogonal property of the OLS algorithm, the approach leads to a parsimonious model. Numerical ill-conditioning problems confronted by the conventional least squares algorithm can also be avoided by the new approach. Finally by utilising the transient response of a MR specimen, it is shown how the model structure can be detected in a practical application. The identified model agrees with the experimental measurements very well

Effective linear damping and stiffness coefficients of nonlinear systems for design spectrum based analysis

A stochastic approach for obtaining reliable estimates of the peak response of nonlinear systems to excitations specified via a design seismic spectrum is proposed. This is achieved in an efficient manner without resorting to numerical integration of the governing nonlinear equations of motion. First, a numerical scheme is utilized to derive a power spectrum which is compatible in a stochastic sense with a given design spectrum. This power spectrum is then treated as the excitation spectrum to determine effective damping and stiffness coefficients corresponding to an equivalent linear system (ELS) via a statistical linearization scheme. Further, the obtained coefficients are used in conjunction with the (linear) design spectrum to estimate the peak response of the original nonlinear systems. The cases of systems with piecewise linear stiffness nonlinearity, along with bilinear hysteretic systems are considered. The seismic severity is specified by the elastic design spectrum prescribed by the European aseismic code provisions (EC8). Monte Carlo simulations pertaining to an ensemble of nonstationary EC8 design spectrum compatible accelerograms are conducted to confirm that the average peak response of the nonlinear systems compare reasonably well with that of the ELS, within the known level of accuracy furnished by the statistical linearization method. In this manner, the proposed approach yields ELS which can replace the original nonlinear systems in carrying out computationally efficient analyses in the initial stages of the aseismic design of structures under severe seismic excitations specified in terms of a design spectrum

Model reduction of weakly nonlinear systems

In general, model reduction techniques fall into two categories — moment —matching and Krylov techniques and balancing techniques. The present contribution is concerned with the former. The present contribution proposes the use of a perturbative representation as an alternative to the bilinear representation [4]. While for weakly nonlinear systems, either approximation is satisfactory, it will be seen that the perturbative method has several advantages over the bilinear representation. In this contribution, an improved reduction method is proposed. Illustrative examples are chosen, and the errors obtained from the different reduction strategies will be compared