Parameter identification of viscoelastic materials

Ohkami, T.; Swoboda, G.

doi:10.1016/s0266-352x(99)00011-7

Cited by 27 publications

(12 citation statements)

References 6 publications

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“…Ohkami and Swoboda [1999] presented two parameter identification procedures for linear viscoelastic materials. Chang [2006] used the genetic algorithm for parameter estimation of nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Estimation of parameters of a three-layered sandwich beam

Barbieri

Winikes

et al. 2008

JOMMS

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In this work the physical parameters of a sandwich beam made with the association of hot rolled steel, polyurethane rigid foam, and high impact polystyrene, used for the assembly of household refrigerators and food freezers, are estimated using measured and numeric frequency response functions. The mathematical models are obtained using the finite element method and the Timoshenko beam theory. The physical parameters are estimated using the amplitude correlation coefficient and genetic algorithm methods. Initially, the experimental procedure to determine the material's mechanical properties, Young and shear moduli, and the density of the components of the sandwich beam is described. The elastic properties were obtained through tension and torsion tests. The shear modulus G c of the polyurethane rigid foam core was determined using a rectangular specimen and the Young's moduli of the steel and high impact polystyrene were determined using a conventional tension test. To estimate the dynamical values of the parameters in the frequency range from 10 to 400 Hz, separated dynamic sweeping tests were conducted using cantilevered beams of polyurethane rigid foam and high impact polystyrene. The experimental data from a three layered sandwich beam were obtained using an impact hammer and four accelerometers, displaced along the cantilevered beam sample. The parameters estimated are the Shear modulus and the loss factor of the polyurethane rigid foam, and the Young's modulus and the loss factor of the high impact polystyrene.

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Section: Introductionmentioning

confidence: 99%

Estimation of parameters of a three-layered sandwich beam

Barbieri

Winikes

et al. 2008

JOMMS

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“…In [14][15][16][17] the non-linear constitutive behavior of the system has been represented by ANN and directly incorporated in a Finite Element (FE) code, while in [18] ANNs are used for the identification of the parameters of a constitutive law. In [15,[19][20][21][22][23][24][25][26][27]] interesting reviews of possible applications of ANNs in nonlinear mechanics can be found.…”

Section: 2mentioning

confidence: 99%

Some aspects of application of artificial neural network for numerical modeling in civil engineering

Lefik¹

2013

Bulletin of the Polish Academy of Sciences: Technical Sciences

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Abstract. In order to obtain reliable results of computations in civil engineering, the numerical procedures that are used at the stage of design should be calibrated by comparison of the theoretical results with an observed behavior of previously modeled and then executed structures. The hybrid Finite Element code with an Artificial Neural Network inserted as a representation of a constitutive law, offers a possibility to adjust not only parameters of the constitutive relationships but also its qualitative form. Because of this, the representation of constitutive law by the ANN is presented in this paper. The constitutive data should be calibrated to fit well the observable values, measured in experiments. If the constitutive law is expressed by ANN, the inverse problem can be reduce to a training of the ANN inserted into the Finite Element code. An example of a solution of the inverse problem in calibration of constitutive law is presented. An identification of parameters of flow of pollutant in soils is described as another example of application of ANN in engineering.

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“…The back analysis method for identifying the properties of the materials is essentially equivalent to the problem of identification of the material parameters P (in this case, damage tensor X) by observing the loadst on the part S u of the boundary S u , where the displacementsû are given, or by observing the displacementsū on the part S t of the boundary S t where the loadst are given [13][14][15]. The model is symbolically shown in Figure 1.…”

Section: Constitutive Equationmentioning

confidence: 99%

“…The displacements u in an element are related to the nodal displacements U, through the shape functions N as u = NU and then the finite element form of Equation (12) is KU = F+F * (13) where…”

Section: Constitutive Equationmentioning

confidence: 99%

Identification of damage parameters for discontinuous rock mass

Ohkami

Maruden

Koyama

2009

Int. J. Numer. Meth. Biomed. Engng.

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SUMMARYThis paper presents an identification method for a discontinuous rock mass employing damage mechanics theory and wavelet analysis. Parameter identification methods based on deterministic approaches are classified into inverse and direct approaches. The proposed method combines the inverse approach and the direct approach and by applying the discrete wavelet transform to the system matrix of the iteration equation, we estimate unknown damage tensors for the case in which the number of unknown parameters exceeds the observed data. The validity of this method is examined for geotechnical engineering problems.

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Parameter identification of viscoelastic materials

Cited by 27 publications

References 6 publications

Estimation of parameters of a three-layered sandwich beam

Estimation of parameters of a three-layered sandwich beam

Some aspects of application of artificial neural network for numerical modeling in civil engineering

Identification of damage parameters for discontinuous rock mass

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