Inicio  /  Computation  /  Vol: 12 Par: 3 (2024)  /  Artículo
ARTÍCULO
TITULO

Numerical Covariance Evaluation for Linear Structures Subject to Non-Stationary Random Inputs

M. Domaneschi    
R. Cucuzza    
L. Sardone    
S. Londoño Lopez    
M. Movahedi and G. C. Marano    

Resumen

Random vibration analysis is a mathematical tool that offers great advantages in predicting the mechanical response of structural systems subjected to external dynamic loads whose nature is intrinsically stochastic, as in cases of sea waves, wind pressure, and vibrations due to road asperity. Using random vibration analysis is possible, when the input is properly modeled as a stochastic process, to derive pieces of information about the structural response with a high quality (if compared with other tools), especially in terms of reliability prevision. Moreover, the random vibration approach is quite complex in cases of non-linearity cases, as well as for non-stationary inputs, as in cases of seismic events. For non-stationary inputs, the assessment of second-order spectral moments requires resolving the Lyapunov matrix differential equation. In this research, a numerical procedure is proposed, providing an expression of response in the state-space that, to our best knowledge, has not yet been presented in the literature, by using a formal justification in accordance with earthquake input modeled as a modulated white noise with evolutive parameters. The computational efforts are reduced by considering the symmetry feature of the covariance matrix. The adopted approach is applied to analyze a multi-story building, aiming to determine the reliability related to the maximum inter-story displacement surpassing a specified acceptable threshold. The building is presumed to experience seismic input characterized by a non-stationary process in both amplitude and frequency, utilizing a general Kanai?Tajimi earthquake input stationary model. The adopted case study is modeled in the form of a multi-degree-of-freedom plane shear frame system.

 Artículos similares

       
 
Yunseong Lee, Chanhong Park, Taeyoung Kim, Yeongyoon Choi, Kiseon Kim, Dongho Kim, Myung-Sik Lee and Dongkeun Lee    
Source enumeration is an important procedure for radio direction-of-arrival finding in the multiple signal classification (MUSIC) algorithm. The most widely used source enumeration approaches are based on the eigenvalues themselves of the covariance matr... ver más
Revista: Applied Sciences

 
Yihao Wu, Jia Huang, Hongkai Shi and Xiufeng He    
Mean dynamic topography (MDT) is crucial for research in oceanography and climatology. The optimal interpolation method (OIM) is applied to MDT modeling, where the error variance?covariance information of the observations is established. The global geopo... ver más
Revista: Applied Sciences

 
Jose M. Gonzalez-Ondina, Lewis Sampson and Georgy I. Shapiro    
Data assimilation methods are an invaluable tool for operational ocean models. These methods are often based on a variational approach and require the knowledge of the spatial covariances of the background errors (differences between the numerical model ... ver más

 
Alexander Schaum    
The application of autoencoders in combination with Dynamic Mode Decomposition for control (DMDc) and reduced order observer design as well as Kalman Filter design is discussed for low order state reconstruction of a class of scalar linear diffusion-conv... ver más
Revista: Algorithms

 
Minjeong Kim, Daseon Hong and Sungsu Park    
This paper presents two amplitude comparison monopulse algorithms and their covariance prediction equation. The proposed algorithms are based on the iterated least-squares estimation method and include the conventional monopulse algorithm as a special ca... ver más
Revista: Applied Sciences