Memorias de investigación
Artículos en revistas:
A STOCHASTIC MODEL UPDATING METHOD FOR PARAMETER VARIABILITY QUANTIFICATION BASED ON RESPONSE SURFACE MODELS AND MONTE CARLO SIMULATION
Año:2012
Áreas de investigación
  • Ingenierías
Datos
Descripción
Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.
Internacional
Si
JCR del ISI
Si
Título de la revista
Mechanical Systems And Signal Processing
ISSN
0888-3270
Factor de impacto JCR
1,913
Información de impacto
Volumen
33
DOI
Número de revista
Desde la página
83
Hasta la página
96
Mes
SIN MES
Ranking
ENGINEERING, MECHANICAL 125 /16 Q1
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: SHENGEN FANG FUZHOU UNIVERSITY
  • Autor: WEI-XIN REN HEFEI UNIVERSITY OF TECHNOLOGY
  • Autor: Ricardo Perera Velamazan UPM
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Mecánica Estructural y Construcciones Industriales