Stochastic identification of composite material properties from limited experimental databases, part I: Experimental database construction

Mehrez, Loujaine; Moens, David; Vandepitte, Dirk

doi:10.1016/j.ymssp.2011.09.004

Cited by 33 publications

(17 citation statements)

References 46 publications

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“…A common feature of most of these studies is the treatment of the primary uncertain parameters as random variables with assumed probabilistic characteristics. Experimental studies to investigate the appropriateness of the assumed probability distributions of the material parameters have been undertaken for different composite materials; see [8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Experimental characterisation of random field models for CFRP composite panels

Sasikumar

Suresh

Vijayaghosh

et al. 2015

Composite Structures

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Section: Introductionmentioning

confidence: 99%

Experimental characterisation of random field models for CFRP composite panels

Sasikumar

Suresh

Vijayaghosh

et al. 2015

Composite Structures

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“…The material properties determined from standard specimens tested in the laboratory may deviate significantly from those of actual laminated composite components manufactured in a factory [12]. Composite structures exhibit variability and uncertainties in their material properties with relation to their compositions and manufacturing processes [13]. Operating conditions, quality control procedures, and environmental effects are often difficult to control, which affect the performance of composite structures [14].…”

Section: Introductionmentioning

confidence: 99%

“…This usually involves minimizing an error function between the experimental and numerical outputs [13]. Constructing of predictive computational models for analysis and design of many complex engineering systems requires not only a fine representation of the relevant physics and their interactions but also a quantitative assessment of underlying uncertainties and their impact on design performance objectives [20].…”

Section: Introductionmentioning

confidence: 99%

A Numerical-Experimental Method for Drop Impact Analysis of Composite Landing Gear

Guan

Xue

et al. 2017

Shock and Vibration

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The special material performance, manufacturing process, machining behavior, and operating condition of composite materials cause uncertainties to inevitably appear in the mechanical properties of composite structures. Therefore, variability in mechanical properties must be considered in a mechanical response analysis of composite structures. A method is proposed in this paper to predict the dynamic performance of composite landing gear with uncertainties using experimental modal analysis data and nonlinear static test data. In this method, the nonlinear dynamic model of the composite landing gear is divided into two parts, the linear and the nonlinear parts. An experimental modal analysis is employed to predict the linear parameters with a frequency response function, and the nonlinear parameters caused by large deflection are identified by a nonlinear static test with the nonlinear least squares method. To check the accuracy and practicability of the method, it is applied to drop impact simulations and tests of composite landing gear. The results of the simulations are in good agreement with the test results, which shows that the proposed method is perfectly suited for the dynamic analysis of composite landing gear.

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“…Mehrez et al [14,15] accounts for both aleatory, i.e. the inherent uncertainty of the material proprieties from sample to sample, and epistemic uncertainties, related to lack of sufficient experimental data, using a Hermite Polynomial Chaos [5] expansion of the random variables on the identified Karhunen-Loeve (KL) series.…”

Section: Introductionmentioning

confidence: 99%