2016
DOI: 10.1016/j.cma.2016.03.034
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Interval and random analysis for structure–acoustic systems with large uncertain-but-bounded parameters

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Cited by 41 publications
(13 citation statements)
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“…The discrete system equation of the acoustic domain can be written in the following matrix form [41]:…”
Section: Mathematical Model Of Asimentioning
confidence: 99%
“…The discrete system equation of the acoustic domain can be written in the following matrix form [41]:…”
Section: Mathematical Model Of Asimentioning
confidence: 99%
“…For the type of tensor product expansion, the Gaussian integral method is very suitable to estimate the expansion characteristics [51]. Generally, the Gauss-Jacobi integration method is able to realize a reliable precision for the estimation of the expansion coefficient of Jacobi expansion When the Gauss-Jacobi integration point is equal to the expansion amount [35].…”
Section: Invert Response Law By Establishing Jacobian Extensionmentioning
confidence: 99%
“…Jacobi expansion for , , and V can be obtained, namely: = = 4.5, = = 3.7, and V = V = 7.2. A relative improvement criterion will be introduced for random uncertainty analysis with IJCEM [51]. For multivariate random problems, the relative improvement of responses is given by [51] Ir (k, ) = (k + e ) − (k)…”
Section: Procedures Of Ijcem For Random Analysis Of Soundmentioning
confidence: 99%
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“…Recently, Wu et al have proposed a Polynomial Chaos–Chebyshev Interval (PCCI) method to determine the intervals of mean value and variance of the system response with hybrid uncertainties. Yin et al also used orthogonal polynomials and developed a unified interval and random Gegenbauer series expansion method to evaluate the uncertain response of acoustic fields with both random and interval parameters. However, the computational cost in calculating the coefficients will increase exponentially with the increase in uncertain variables.…”
Section: Introductionmentioning
confidence: 99%