Thermodynamics of pairing transition in hot nuclei

The pairing correlations in hot nuclei $^{162}$Dy are investigated in terms of the thermodynamical properties by covariant density functional theory. The heat capacities $C_V$ are evaluated in the canonical ensemble theory and the paring correlations are treated by a shell-model-like approach, in which the particle number is conserved exactly. A S-shaped heat capacity curve, which agrees qualitatively with the experimental data, has been obtained and analyzed in details. It is found that the one-pair-broken states play crucial roles in the appearance of the S shape of the heat capacity curve. Moreover, due to the effect of the particle-number conservation, the pairing gap varies smoothly with the temperature, which indicates a gradual transition from the superfluid to the normal state.Comment: 13 pages, 4 figure

Electroweak Chiral Lagrangian for a Hypercharge-universal Topcolor Model

Electroweak chiral Lagrangian for a hypercharge-universal topcolor model is investigated. We find that the assignments of universal hypercharge improve the results obtained previously from K.Lane's prototype natural TC2 model by allowing a larger Z' mass resulting in a very small T parameter and the S parameter is still around the order of +1Comment: 12 pages, 7 figure

A novel nonlinear approach to suppress resonant vibrations

A novel approach to suppress resonant vibration is presented by employing a single degree of freedom transmissibility system which utilizes a nonlinear damping element. Studies have shown that the nonlinear damping element can reduce the output energy at the driving frequency and at the same time spread the output signal energy over a wider range of harmonics. It will also be shown that the reduction becomes larger as the nonlinear damping characteristic gets stronger and in most cases, the power at the harmonics in the output spectrum will be much less if the nonlinear damping characteristic is an odd function. Hence, an odd polynomial nonlinear damping element can be introduced between the incoming signal and the structure of interest to suppress resonant vibration. An expression is derived to express the transmitted force spectrum in terms of the nonlinear generalized frequency response functions, to clearly show how the energy, at the excitation frequency, is modified by the nonlinearity

Suppressing resonant vibrations using nonlinear springs and dampers

The energy entering the resonant region of a system can be significantly reduced by introducing designed nonlinearities into the system. The basic choice of the nonlinearity can be either a nonlinear spring element or a nonlinear damping element. A numerical algorithm to compute and compare the energy reduction produced by these two types of designed elements is proposed in this study. Analytical results are used to demonstrate the procedure. The numerical results indicate that the designed nonlinear damping element produces low levels of energy at the higher order harmonics and no bifurcations in the system output response. In contrast the nonlinear spring based designs induce significant energy at the harmonics and can produce bifurcation behaviour. The conclusions provide an important basis for the design of nonlinear materials and nonlinear engineering systems

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