Structural uncertainty estimation through a Craig-Bampton Stochastic Method optimisation in satellites structures

Lellis, Salvatore De; Stabile, Alessandro; Aglietti, Guglielmo S.; Richardson, Guy

doi:10.1016/j.jsv.2019.115123

Cited by 4 publications

(3 citation statements)

References 32 publications

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“…Because the covariance matrix of a random field is defined in the regular geometric space domain, the eigenvalues and eigenvectors can be easily obtained. The detailed solution process of autocorrelation matrix

is as follows [ 5 ].

whereby the autocovariance function

is bounded, symmetric, and positive definite, which ensures that the eigenvalues and eigenfunctions have the following properties: (1) the set of eigenfunctions

is orthogonal and complete; (2) for each eigenvalue

, there are at most a limited number of linearly independent eigenfunctions; (3) there is at most one countable infinite set of eigenvalues; (4) all of the eigenvalues are positive real numbers; (5) the autocovariance function

can be decomposed into the following forms:

…”

Section: Representation Of the Uncertainty With Random Fieldmentioning

confidence: 99%

“…For example, Gorman and Yu [ 4 ] reviewed the method of superposition in vibration analysis of plates and shells, especially focusing on the Gorman method for accurate establishment of eigenvalues and mode shapes in free vibration analysis of rectangular plates. Although the system variables of the concerned structures are broadly accounted for as deterministic, it has been demonstrated that the fluctuation, i.e., uncertainties, of these parameters inevitably and inherently correlated to the structural modelling and analysis process [ 5 , 6 , 7 ]. The complexity of the actual structural material properties and various random errors during the manufacturing process will result in uncertainty of the structural parameters, such as vibration of the machine tool, random variation in the temperature during processing, etc., which will cause uncertainty among a group of structural components with the same nominal size that are manufactured with the same material and the same processing method [ 8 ] and ultimately lead to random fluctuation of material properties around the mean value and a certain correlation between the fluctuation and machining dimension direction [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

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Uncertain Dynamic Characteristic Analysis for Structures with Spatially Dependent Random System Parameters

Zhou

et al. 2023

Materials

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This work presents a robust non-deterministic free vibration analysis for engineering structures with random field parameters in the frame of stochastic finite element method. For this, considering the randomness and spatial correlation of structural physical parameters, a parameter setting model based on random field theory is proposed to represent the random uncertainty of parameters, and the stochastic dynamic characteristics of different structural systems are then analyzed by incorporating the presented parameter setting model with finite element method. First, Gauss random field theory is used to describe the uncertainty of structural material parameters, the random parameters are then characterized as the standard deviation and correlation length of the random field, and the random field parameters are then discretized with the Karhunen–Loeve expansion method. Moreover, based on the discretized random parameters and finite element method, structural dynamic characteristics analysis is addressed, and the probability distribution density function of the random natural frequency is estimated based on multi-dimensional kernel density estimation method. Finally, the random field parameters of the structures are quantified by using the maximum likelihood estimation method to verify the effectiveness of the proposed method and the applicability of the constructed model. The results indicate that (1) for the perspective of maximum likelihood estimation, the parameter setting at the maximum value point is highly similar to the input parameters; (2) the random field considering more parameters reflects a more realistic structure.

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is as follows [ 5 ].

whereby the autocovariance function

is bounded, symmetric, and positive definite, which ensures that the eigenvalues and eigenfunctions have the following properties: (1) the set of eigenfunctions

is orthogonal and complete; (2) for each eigenvalue

can be decomposed into the following forms:

…”

Section: Representation Of the Uncertainty With Random Fieldmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Uncertain Dynamic Characteristic Analysis for Structures with Spatially Dependent Random System Parameters

Zhou

et al. 2023

Materials

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show abstract

“…Teng et al [39] have studied the evolution of localized crack growth by introducing an acoustic data-driven deviation detection method based on statistical probability models called the consensus self-organizing models (COSMO). De Lellis et al [40] have computed perturbation parameters associated with structural impairments by applying a classic Craig-Bampton Approach version's stochastic version. e researchers have argued that this method can be constructed as an optimization black box technique for enhancing the model correlating with investigated data with the use of the finite element model.…”

Section: Related Workmentioning

confidence: 99%

Simulation and Analysis with Wavelet Transform Technique and the Vibration Characteristics for Early Revealing of Cracks in Structures

Abu‐Hamdeh

Daqrouq

Mebarek‐Oudina

2021

Mathematical Problems in Engineering

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Implementation of improved instruments is used to detect damage in an accurate manner and fully analyze its characteristics. An aluminum beam has been used in this work to identify cracks by using a vibration technique. The simulation of frequency response feature was conducted using a finite element model to provide average measures of intensities of vibration. Two forms of wavelet packet transform (WPT) entropies Shannon and log energy were applied to identify the position, width, and size of the crack. The results showed that with an increase in crack depth, the amplitude also increased at certain crack sizes and for all crack positions. For two crack depths of 1.6 mm and 0.16 mm having the same crack size and position 12 mm and 60 mm, respectively, a 4.5% increase in amplitude was observed at a crack depth of 1.6 mm. Moreover, the amplitude varied inversely with the position. A 12.6% increase in amplitude was observed at a crack depth of 1.6 mm rather than 0.16 mm, while both depths occurred at the same crack position (75 mm) and size (20 mm). Experimental validation was performed on a cantilever beam with one crack. The maximum absolute error found was 7.5% for the crack position and 9.1% for the crack size. With the increase in crack depth, the obtained results decrease the stiffness of a beam in a single crack case.

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Base force and moment based finite element model correlation method

Sairajan

Deshpande

Patnaik

et al. 2021

Advances in Space Research

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Structural uncertainty estimation through a Craig-Bampton Stochastic Method optimisation in satellites structures

Cited by 4 publications

References 32 publications

Uncertain Dynamic Characteristic Analysis for Structures with Spatially Dependent Random System Parameters

Uncertain Dynamic Characteristic Analysis for Structures with Spatially Dependent Random System Parameters

Simulation and Analysis with Wavelet Transform Technique and the Vibration Characteristics for Early Revealing of Cracks in Structures

Base force and moment based finite element model correlation method

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