Innovative methods for random field establishment and statistical parameter inversion exemplified with 6082-T6 aluminum alloy

Zheng, Kaikai; Yang, Kangkang; Shi, Jun; Yuan, Jian; Zhou, Guangchun

doi:10.1038/s41598-019-54046-9

“…for geosystems [12], thin-walled composite cylinders [13], three-dimensional concrete microstructures [14],and the representation of the continuous mode conversion observed by the propagation of guided ultrasonic waves in thin-walled structures made of fiber-reinforced composite [15]. A first application of random fields in the context of nonlinear behavior for isotropic material is provided by Zheng et al [16]. The application to SFRC is limited to the linear elastic domain so far [2].…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of the Elastic-Ideal Plastic Material Behavior of Short Fiber-Reinforced Composites Including Its Spatial Distribution with an Experimental Validation

Rauter¹

2022

Preprint

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For the numerical simulation of components made of short fiber-reinforced composites the correct prediction of the deformation including the elastic and plastic behavior and its spatial distribution is essential. When using purely deterministic modeling approaches the information of the probabilistic microstructure is not included in the simulation process. One possible approach for the integration of stochastic information is the use of random fields. In this study numerical simulations of tensile test specimens are conducted utilizing a finite deformation elastic-ideal plastic material model. A selection of the material parameters covering the elastic and plastic domain are represented by cross-correlated second-order Gaussian random fields to incorporate the probabilistic nature of the material parameters. To validate the modeling approach tensile tests until failure are carried out experimentally, that confirm the assumption of spatially distributed material behavior in both the elastic and plastic domain. Since the correlation lengths of the random fields cannot be determined by pure analytic treatments, additionally numerical simulations are performed for different values of the correlation length. The numerical simulations endorse the influence of the correlation length on the overall behavior. For a correlation length of 5mm a good conformity with the experimental results is obtained. Therefore, it is concluded, that the presented modeling approach is suitable to predict the elastic and plastic deformation of a set of tensile test specimens made of short fiber-reinforced composite sufficiently.

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“…for geosystems 12 , thin-walled composite cylinders 13 , three-dimensional concrete microstructures 14 ,and the representation of the continuous mode conversion observed by the propagation of guided ultrasonic waves in thin-walled structures made of fiber-reinforced composite 15 . A first application of random fields in the context of nonlinear behavior for isotropic material is provided by Zheng et al 16 . The application to SFRC is limited to the linear elastic domain so far 2 .…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of the elastic-ideal plastic material behavior of short fiber-reinforced composites including its spatial distribution with an experimental validation

Rauter

¹

2022

Preprint

1

0

View full text Add to dashboard Cite

For the numerical simulation of components made of short fiber-reinforced composites the correct prediction of the deformation including the elastic and plastic behavior and its spatial distribution is essential. When using purely deterministic modeling approaches the information of the probabilistic microstructure is not included in the simulation process. One possible approach for the integration of stochastic information is the use of random fields. In this study numerical simulations of tensile test specimens are conducted utilizing a finite deformation elastic-ideal plastic material model. A selection of the material parameters covering the elastic and plastic domain are represented by cross-correlated second-order Gaussian random fields to incorporate the probabilistic nature of the material parameters. To validate the modeling approach tensile tests until failure are carried out experimentally, that confirm the assumption of spatially distributed material behavior in both the elastic and plastic domain. Since the correlation lengths of the random fields cannot be determined by pure analytic treatments, additionally numerical simulations are performed for different values of the correlation length. The numerical simulations endorse the influence of the correlation length on the overall behavior. For a correlation length of 5mm a good conformity with the experimental results is obtained. Therefore, it is concluded, that the presented modeling approach is suitable to predict the elastic and plastic deformation of a set of tensile test specimens made of short fiber-reinforced composite sufficiently.

show abstract

Numerical Simulation of the Elastic–Ideal Plastic Material Behavior of Short Fiber-Reinforced Composites Including Its Spatial Distribution with an Experimental Validation

Rauter

¹

2022

View full text Add to dashboard Cite

For the numerical simulation of components made of short fiber-reinforced composites, the correct prediction of the deformation including the elastic and plastic behavior and its spatial distribution is essential. When using purely deterministic modeling approaches, the information of the probabilistic microstructure is not included in the simulation process. One possible approach for the integration of stochastic information is the use of random fields. In this study, numerical simulations of tensile test specimens were conducted utilizing a finite deformation elastic–ideal plastic material model. A selection of the material parameters covering the elastic and plastic domain are represented by cross-correlated second-order Gaussian random fields to incorporate the probabilistic nature of the material parameters. To validate the modeling approach, tensile tests until failure were carried out experimentally, which confirmed the assumption of the spatially distributed material behavior in both the elastic and plastic domain. Since the correlation lengths of the random fields cannot be determined by pure analytic treatments, additionally numerical simulations were performed for different values of the correlation length. The numerical simulations endorsed the influence of the correlation length on the overall behavior. For a correlation length of 5mm, a good conformity with the experimental results was obtained. Therefore, it was concluded that the presented modeling approach was suitable to predict the elastic and plastic deformation of a set of tensile test specimens made of short fiber-reinforced composite sufficiently.

show abstract

Innovative methods for random field establishment and statistical parameter inversion exemplified with 6082-T6 aluminum alloy

Cited by 3 publications

References 20 publications

Numerical Simulation of the Elastic-Ideal Plastic Material Behavior of Short Fiber-Reinforced Composites Including Its Spatial Distribution with an Experimental Validation

Numerical Simulation of the Elastic-Ideal Plastic Material Behavior of Short Fiber-Reinforced Composites Including Its Spatial Distribution with an Experimental Validation

Numerical simulation of the elastic-ideal plastic material behavior of short fiber-reinforced composites including its spatial distribution with an experimental validation

Numerical Simulation of the Elastic–Ideal Plastic Material Behavior of Short Fiber-Reinforced Composites Including Its Spatial Distribution with an Experimental Validation

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