2009
DOI: 10.1016/s1644-9665(12)60216-7
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Spectral density of the bridge beam response with uncertain parameters under a random train of moving forces

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Cited by 19 publications
(7 citation statements)
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“…Mehri et al [9] using the Green function derived the dynamic behavior of the Euler-Bernoulli beam excited by moving load. Also, spectral analysis of the beam under the influence of load is recommended by Gladyzs and Sniady [10]. The desired beam is contemplated orthotropic at any point, whereas the properties of different materials in the thickness of the beam are exponential.…”
Section: Introductionmentioning
confidence: 99%
“…Mehri et al [9] using the Green function derived the dynamic behavior of the Euler-Bernoulli beam excited by moving load. Also, spectral analysis of the beam under the influence of load is recommended by Gladyzs and Sniady [10]. The desired beam is contemplated orthotropic at any point, whereas the properties of different materials in the thickness of the beam are exponential.…”
Section: Introductionmentioning
confidence: 99%
“…As early as 1976, Fryba [2] began the study of random vibration of bridge under a moving load. Since 1990s, many researchers have begun to investigate the theory of vehicle-bridge coupling calculation and computer simulation [3][4][5][6][7][8][9][10]. At the same time, the study of bridge model has developed from simple, small and medium span to complex and long span.…”
Section: Introductionmentioning
confidence: 99%
“…e dynamic response of an infinite beam and a plate resting on a Pasternak foundation to the passage of a train of random forces, according either to Poisson's distribution or Erlang process, all travelling at the same speed, was analysed in [13], deriving explicit formulas for the expected value, the variance, and the n-th cumulant of flexural displacements. A spectral analysis of a beam's vibration with uncertain parameters under a random train of moving forces which forms a filtered Poisson process was studied in [14], assuming uncertain natural frequencies which were modelled by fuzzy numbers, random variables, or fuzzy random variables.…”
Section: Introductionmentioning
confidence: 99%