UDK 629.7.036.3 BBK 39.15

Kirenchev A. G.

Danilenko N. V.

The article considers the basic problems of vortex formation phenomenon and its natural and technogenic vortices. A new definition of vortex formation based on the physical essence of the working process is given. The mathematical foundation of the working process of vortex formation is presented with the use of Professor N. E. Zhukovsky’s theorem about the lifting force of the wing, as well as the equation for conservation of the gas movement energy and the Stokes theorem about the equality of the vortex tension and velocity circulation. Due to the analysis of the energy conservation equation the main factors of generation and accumulation of natural and technogenic vortices are revealed. The issue of the determining role of the underlying surface for forming effluent vortices of air intakes of aircraft gas-turbine propulsion systems is investigated. Influence of other external factors on the formation of technogenic vortices is noted. Classification of technogenic vortex formation and its vortices by the essence of the working process is given.

Keywords: vortex formation, technogenic vortices, vortex interference, the role of the underlying surface, gas turbine power plants, mathematical justification of Coriolis force vortices, air intake.

Download article in PDF 1.0 MB

UDK 621.438, 004.855 BBK З363.3, 32.813, 22.18

Novikova S. V.

Kremleva J. Sh.

The article presents a technique of increasing the robustness of a neural-net model of gas-turbine engine monitoring during stand tests due to decreasing the number of insignificant links in the neural network (neural network reduction). The technique is based on converting the problem of neural network learning into that of multi-criteria optimization which includes the error minimization criterion and the criterion of minimizing the absolute values of the weight links of a neural network. The latter requirement leads to reveal of insignificant links which can be deleted without any loss of accuracy. As a result, the ability of the model to summarize increases greatly, robustness increases as well, the calculation error of monitored parameters decreases.

Key words: model robustness, neural networks, stand tests, monitoring of a gas-turbine engine, reduction of a neural network.

Download article in PDF 219.4 kB

UDK 629.5.03-843.8 BBK 74.5

Karavaev Y.A.

Hodackij S.A.

The article presents general approaches to forming an estimation procedure of the residual operation life of the bypass turbojets operated on civil aircraft for long periods of time by taking actual operating conditions into account. With the example of D-436-148 aircraft engine having the standard control program the authors analyze how the size of turbine-blade tip clearances influences the rate of exhaustion of a bypass turbojet module – the gas turbine. A fraction of moving blade damage on takeoff is proposed to be used as a parameter defining the rate of exhaustion of the gas turbine.

Key words: gas-turbine engine lifetime, turbine-blade tip clearances, durability of moving blades, creep.

Download article in PDF 447.8 kB

UDC 004. 588 BBK 74.5

Yu. A. Karavaev

S. A. Khodatskiy

A significant number of aircraft engines taking out early from operation are associated with inter-shaft bearing failures. Possible causes of such failures are violations of their lubrication and cooling conditions. The article presents the results of experimental studies to assess the effect of reducing the performance of the oil tube with bending vibrations of the rotor on the thermal state of the inter-shaft bearing.

During the turbofan engine operation, its shaft co-performs bending vibrations due to the imbalance of the rotor. In this case, the oil tube, placed inside the engine shaft, will also make bending vibrations, which can be one of the reasons for reducing oil consumption through the oil tube with a significant level of vibrations. In this case, the working temperature of the inter-shaft bearing may increase significantly.

Keywords: aircraft engine, inter-shaft bearing, vibration velocity, bearing temperature, GTE oil system parameters.

Download article in PDF 793.0 kB

UDK 629.7:681.324 BBK 39.551-01-07 S21

A. A. San’ko

A. A. Shejnikov

The article presents the results of a comparative analysis of mathematical models of the turbine gas temperature sensor of the turbocharger of a helicopter gas turbine engine based on regression analysis and on a multilayer neural network. The inexpediency of using a multilayer neural network as a mathematical model of a gas temperature sensor is proved. The optimal type of the mathematical model of the gas temperature sensor is selected by the criterion of the minimum error of the output parameter calculation.

Keywords: gas turbine engine, rotor, mathematical model of gas temperature sensor, helicopter, neural network.

Download article in PDF 546.7 kB