Modelling of steam flow through transonic turbine rows using artificial neural networks

Grzymkowska, A.; Szewczuk, Natalia

doi:10.17814/mechanik.2016.7.132

Cited by 1 publication

(2 citation statements)

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“…The analysis of the literature and the results of calculations showed that it is possible to use artificial neural networks to solve scientific problems in the area of rotating rotor machine elements, such as an aircraft turbine engine. Although papers [23,46,47] deal with the problems of implementing Artificial Neural Networks to solve engineering problems, the analyses are limited to flows or to the problem of frictional contact with elements loaded with uniform forces. There are no attempts to use SSNs for strength calculations of rotating machine elements.…”

Section: Discussionmentioning

confidence: 99%

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Artificial Neural Network Structure Optimisation in the Pareto Approach on the Example of Stress Prediction in the Disk-Drum Structure of an Axial Compressor

Kozakiewicz

Kieszek

2022

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The article presents the process of selecting and optimising artificial neural networks based on the example of determining the stress distribution in a disk-drum structure compressor stage of an aircraft turbine engine. The presented algorithm allows the determination of von Mises stress values which can be part of the penalty function for further mass optimization of the structure. A method of a parametric model description of a compressor stage is presented in order to prepare a reduced stress distribution for training artificial neural networks. A comparative analysis of selected neural network training algorithms combined with the optimisation of their structure is presented. A genetic algorithm was used to determine the optimal number of hidden layers and neurons in a layer. The objective function was to minimise the absolute value of the relative error and standard deviation of stresses determined by FEM and artificial neural networks. The results are presented in the form of the Pareto front due to the stochastic optimisation process.

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Section: Discussionmentioning

confidence: 99%

“…ANNs are increasingly being used in aviation [8][9][10]. They are used in reliability analysis [11,12], fault detection [13][14][15][16], identification [17], control [18,19], and design and optimisation [20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network Structure Optimisation in the Pareto Approach on the Example of Stress Prediction in the Disk-Drum Structure of an Axial Compressor

Kozakiewicz

Kieszek

2022

Materials

View full text Add to dashboard Cite

show abstract

Modelling of steam flow through transonic turbine rows using artificial neural networks

Cited by 1 publication

References 1 publication

Artificial Neural Network Structure Optimisation in the Pareto Approach on the Example of Stress Prediction in the Disk-Drum Structure of an Axial Compressor

Artificial Neural Network Structure Optimisation in the Pareto Approach on the Example of Stress Prediction in the Disk-Drum Structure of an Axial Compressor

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