A method is presented for obtaining, approximately, the response covariance and probability distribution of a non-linear oscillator under a Gaussian excitation. The method has similarities with the hierarchy closure and the equivalent linearization approaches, but is different. A Gaussianization technique is used to arrive at the output autocorrelation and the input-output cross-correlation. This along with an energy equivalence criterion is used to estimate the response distribution function. The method is applicable in both the transient and steady state response analysis under either stationary or non-stationary excitations. Good comparison has been observed between the predicted and the exact steady state probability distribution of a D...
The problem of non-linear systems excited by random forces with known power spectral density functio...
Dynamic behaviour of a beam, subjected to stationary random excitation, has been investigated for th...
A new method is presented for approximating the stationary probability density function of the respo...
A method is presented for obtaining, approximately, the response covariance and probability distribu...
A technique is developed to study random vibration of nonlinear systems. The method is based on the ...
First examined is the problem of obtaining the nonstationary stochastic response of a nonlinear syst...
First examined is the problem of obtaining the nonstationary stochastic response of a nonlinear syst...
In this paper, Equivalent Linearization techniques are used to develop a novel method for predicting...
Non-stationary non-Gaussian random vibration problems of structures are challenging and drawing incr...
Analytical and experimental investigations are made of the response of linear systems subject to mag...
The analysis of the free and forced vibration of a randomly time-varying system is the subject matte...
Nonlinear vibration systems with adjustable stiffness property have attracted considerable attention...
Non-parametric methods for estimation of the non-linear damping, non-linear stiffness and excitation...
This dissertation provides the foundation for an in-depth understanding and significant development ...
Application of a stationary Gaussian Random process to describe a non-deterministic forcing function...
The problem of non-linear systems excited by random forces with known power spectral density functio...
Dynamic behaviour of a beam, subjected to stationary random excitation, has been investigated for th...
A new method is presented for approximating the stationary probability density function of the respo...
A method is presented for obtaining, approximately, the response covariance and probability distribu...
A technique is developed to study random vibration of nonlinear systems. The method is based on the ...
First examined is the problem of obtaining the nonstationary stochastic response of a nonlinear syst...
First examined is the problem of obtaining the nonstationary stochastic response of a nonlinear syst...
In this paper, Equivalent Linearization techniques are used to develop a novel method for predicting...
Non-stationary non-Gaussian random vibration problems of structures are challenging and drawing incr...
Analytical and experimental investigations are made of the response of linear systems subject to mag...
The analysis of the free and forced vibration of a randomly time-varying system is the subject matte...
Nonlinear vibration systems with adjustable stiffness property have attracted considerable attention...
Non-parametric methods for estimation of the non-linear damping, non-linear stiffness and excitation...
This dissertation provides the foundation for an in-depth understanding and significant development ...
Application of a stationary Gaussian Random process to describe a non-deterministic forcing function...
The problem of non-linear systems excited by random forces with known power spectral density functio...
Dynamic behaviour of a beam, subjected to stationary random excitation, has been investigated for th...
A new method is presented for approximating the stationary probability density function of the respo...