On some of the peculiarities of propagation of an elastic wave through a gradient transversely isotropic layer

Anufrieva, A.V.; Tumakov, Dmitrii

doi:10.1109/dd.2014.7036417

Cited by 2 publications

(2 citation statements)

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“…However, we fully understand that this question is quite important [10,11] and deserves a separate attention and research investigation. In addition, it is better to train the network via taking into account the features of passing of elastic waves through characteristic peculiarities of the waveguide structures [12,13].…”

Section: Discussionmentioning

confidence: 99%

Recovery of parameters of a homogeneous elastic layer using neural networks

Tumakov¹,

Khairullina²,

Валеева³

2018

J. Fundam and Appl Sci.

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The problem of recovery of parameters of an elastic uniform layer is considered. The solution method of this problem is proposed by means of neural networks. For the input network parameters, amplitudes of transmitted or reflected waves are chosen. We consider the output parameter of network density and longitudinal speed of the environment filling a layer. Three types of neurons activation function are chosen: piecewise-linear, sigmoid and radial function (Gauss's function). The following algorithms of perseptron training are considered: the backpropagation algorithm and the genetic algorithm. In the genetic algorithm, the crossover method, in which the next gene is selected equiprobable and incidental from genes of the ancestors located in the same position is chosen. Then genes of a new chromosome with small probability are exposed to mutations at a small value. Training of neural network takes place according to the calculated data of the direct problem solved multiply times with various elastic parameters varying in the defined intervals. Dependences graphs of an error of parameter recovery on such parameters of neural network as selection dimension and neurons' number are provided. Deterioration in accuracy of recovery of required data, when training network, is shown. Results of comparison of neural networks with various activation functions are described. For density and speed of a layer recovery at the same time, the method of calculation of unknown elastic parameters using the neural network trained for recovery of acoustic rigidity and wave number is proposed. The conclusion is drawn that radial function of neurons activation yields steadier results.

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Section: Discussionmentioning

confidence: 99%

Recovery of parameters of a homogeneous elastic layer using neural networks

Tumakov¹,

Khairullina²,

Валеева³

2018

J. Fundam and Appl Sci.

Self Cite

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“…However, it is noteworthy that a more precise approach to an anisotropic model is in treating it as a transversely isotropic model. This approach was applied by our research group in the past to investigate the problem of elastic wave propagation through gradient isotropic materials [15] and gradient transversely isotropic materials [16,17]. In [18], diffraction of plane acoustic wave by inhomogeneous layer was investigated.…”

Section: Introductionmentioning

confidence: 99%

On Peculiarities of Propagation of a Plane Elastic Wave through a Gradient Anisotropic Layer

Anufrieva

Chickrin

Tumakov

2015

Advances in Acoustics and Vibration

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The problem of diffraction of a plane elastic wave by an anisotropic layer is studied. The diffraction problem is reduced to a boundary value problem for the layer. The grid method is used for solving the resulting boundary value problem. The diffraction of a plane longitudinal wave by the layer is considered. Some peculiarities of the gain-frequency and the gain-angle characteristics of a normal component of an energy flow of a passed longitudinal wave are numerically studied.

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On some of the peculiarities of propagation of an elastic wave through a gradient transversely isotropic layer

Cited by 2 publications

References 3 publications

Recovery of parameters of a homogeneous elastic layer using neural networks

Recovery of parameters of a homogeneous elastic layer using neural networks

On Peculiarities of Propagation of a Plane Elastic Wave through a Gradient Anisotropic Layer

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