scholarly journals Application of Neural Network Technology and High-performance Computing for Identification and Real-time Hardware-in-the-loop Simulation of Gas Turbine Engines

2017 ◽  
Vol 176 ◽  
pp. 402-408 ◽  
Author(s):  
G.I. Pogorelov ◽  
G.G. Kulikov ◽  
A.I. Abdulnagimov ◽  
B.I. Badamshin
Keyword(s):  
Neural Network ◽  
High Performance Computing ◽  
Gas Turbine ◽  
High Performance ◽  
Turbine Engines ◽  
Network Technology ◽  
Gas Turbine Engines ◽  
Hardware In The Loop ◽  
Performance Computing ◽  
Neural Network Technology

scholarly journals Progress in Novel Electrodeposited Bond Coats for Thermal Barrier Coating Systems

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4214
Author(s):  
Kranthi Kumar Maniam ◽  
Shiladitya Paul
Keyword(s):  
Gas Turbine ◽  
Thermal Barrier Coating ◽  
Gas Turbines ◽  
High Performance ◽  
Turbine Engines ◽  
Thermal Barrier ◽  
Gas Turbine Engines ◽  
Potential Cost ◽  
Bond Coats ◽  
Barrier Coating

The increased demand for high performance gas turbine engines has resulted in a continuous search for new base materials and coatings. With the significant developments in nickel-based superalloys, the quest for developments related to thermal barrier coating (TBC) systems is increasing rapidly and is considered a key area of research. Of key importance are the processing routes that can provide the required coating properties when applied on engine components with complex shapes, such as turbine vanes, blades, etc. Despite significant research and development in the coating systems, the scope of electrodeposition as a potential alternative to the conventional methods of producing bond coats has only been realised to a limited extent. Additionally, their effectiveness in prolonging the alloys’ lifetime is not well understood. This review summarises the work on electrodeposition as a coating development method for application in high temperature alloys for gas turbine engines and discusses the progress in the coatings that combine electrodeposition and other processes to achieve desired bond coats. The overall aim of this review is to emphasise the role of electrodeposition as a potential cost-effective alternative to produce bond coats. Besides, the developments in the electrodeposition of aluminium from ionic liquids for potential applications in gas turbines and the nuclear sector, as well as cost considerations and future challenges, are reviewed with the crucial raw materials’ current and future savings scenarios in mind.

Application of neural network expert systems for monitoring, diagnostics and forecasting of technical condition of aircraft engines

2020 ◽  
pp. 51-59
Author(s):  
Д.О. Пушкарёв
Keyword(s):  
Neural Network ◽  
Expert Systems ◽  
Gas Turbine ◽  
Technical Condition ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Fuzzy Interference System ◽  
Interference System ◽  
Monitoring And Diagnostics ◽  
Technical Operation

Рассматривается применение нейросетевых экспертных систем в области контроля, диагностики и прогнозирования технического состояния авиационных ГТД на основе нечеткой логики. Показана методика для решения таких задач в области технической эксплуатации авиационной техники совместно с использованием фаззи-интерференсной системы программы MATLAB. Используя статистические данные о работе двигателя формируется экспертная система на основе нейронной сети позволяющая осуществлять контроль и диагностику ГТД, а также прогнозировать дальнейшее техническое состояния анализируемого двигателя. The application of neural network expert systems in the field of monitoring, diagnostics and forecasting of the technical condition of aviation gas turbine engines based on fuzzy logic is considered. The technique for solving such problems in the field of technical operation of aircraft and using the fuzzy-interference system of the MATLAB program is shown. Using statistical data on the operation of the engine, an expert system is based on the fundamental of a neural network that provide monitoring and diagnostics of gas turbine engines, as well as predicting the further technical condition of the analyzed engine.

scholarly journals Cooled Radial In-Flow Turbines for Advanced Gas Turbine Engines

1981 ◽  
Author(s):  
J. M. Lane
Keyword(s):  
Gas Turbine ◽  
High Performance ◽  
Turbine Engines ◽  
Inlet Temperature ◽  
Internal Cooling ◽  
Gas Turbine Engines ◽  
Radial Turbine ◽  
Internally Cooled ◽  
Subsequent Discussion ◽  
Near Term

While the radial in-flow turbine has consistently demonstrated its capability as a high-performance component for small gas turbine engines, its use has been relegated to lower turbine-inlet-temperature cycles due to insurmountable problems with respect to the manufacturing of radial turbine rotors with internal cooling passages. These cycle temperature limitations are not consistent with modern trends toward higher-performance, fuel-conservative engines. This paper presents the results of several Army-sponsored programs, the first of which addresses the performance potential for the high-temperature radial turbine. The subsequent discussion presents the results of two successful programs dedicated to developing fabrication techniques for internally cooled radial turbines, including mechanical integrity testing. Finally, future near-term capabilities are projected.

Health Monitoring and Degradation Prognostics in Gas Turbine Engines Using Dynamic Neural Networks

2015 ◽  
Author(s):  
A. Vatani ◽  
K. Khorasani ◽  
N. Meskin
Keyword(s):  
Neural Network ◽  
Gas Turbine ◽  
Health Monitoring ◽  
Network Architecture ◽  
Information Criterion ◽  
Turbine Engines ◽  
Prediction Errors ◽  
Gas Turbine Engines ◽  
Dynamic Neural Networks ◽  
Turbine Engine

In this paper two artificially intelligent methodologies are proposed and developed for degradation prognosis and health monitoring of gas turbine engines. Our objective is to predict the degradation trends by studying their effects on the engine measurable parameters, such as the temperature, at critical points of the gas turbine engine. The first prognostic scheme is based on a recurrent neural network (RNN) architecture. This architecture enables ONE to learn the engine degradations from the available measurable data. The second prognostic scheme is based on a nonlinear auto-regressive with exogenous input (NARX) neural network architecture. It is shown that this network can be trained with fewer data points and the prediction errors are lower as compared to the RNN architecture. To manage prognostic and prediction uncertainties upper and lower threshold bounds are defined and obtained. Various scenarios and case studies are presented to illustrate and demonstrate the effectiveness of our proposed neural network-based prognostic approaches. To evaluate and compare the prediction results between our two proposed neural network schemes, a metric known as the normalized Akaike information criterion (NAIC) is utilized. A smaller NAIC shows a better, a more accurate and a more effective prediction outcome. The NAIC values are obtained for each case and the networks are compared relatively with one another.

scholarly journals METHOD OF FORMULATING INPUT PARAMETERS OF NEURAL NETWORK FOR DIAGNOSING GAS-TURBINE ENGINES

Aviation ◽  
2013 ◽  
Vol 17 (2) ◽  
pp. 52-56 ◽  
Author(s):  
Mykola Kulyk ◽  
Sergiy Dmitriev ◽  
Oleksandr Yakushenko ◽  
Oleksandr Popov
Keyword(s):  
Neural Network ◽  
Gas Turbine ◽  
Gas Turbine Engine ◽  
Training Data ◽  
Turbine Engines ◽  
Data Sets ◽  
Gas Turbine Engines ◽  
Turbine Engine ◽  
Wide Range ◽  
And Training

A method of obtaining test and training data sets has been developed. These sets are intended for training a static neural network to recognise individual and double defects in the air-gas path units of a gas-turbine engine. These data are obtained by using operational process parameters of the air-gas path of a bypass turbofan engine. The method allows sets that can project some changes in the technical conditions of a gas-turbine engine to be received, taking into account errors that occur in the measurement of the gas-dynamic parameters of the air-gas path. The operation of the engine in a wide range of modes should also be taken into account.

Development of a Retracting Vane/Centrifugal Main Fuel Pump for Gas Turbine Engines

1976 ◽  
Vol 98 (4) ◽  
pp. 619-625
Author(s):  
K. H. Pech ◽  
N. L. Downing
Keyword(s):  
Gas Turbine ◽  
Centrifugal Pump ◽  
High Performance ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Functional Requirements ◽  
Fuel Pump ◽  
Cost Weight ◽  
Performance Requirements ◽  
The Cost

Fuel pumps and metering systems are becoming more complex and expensive to meet the high performance requirements of advanced gas turbine engines. A simple, inlet throttled, centrifugal pump integrated with a retracting vane starting element provides the potential for a reliable, high performance design capable of reducing the cost, weight, and temperature rise of the fuel system. This paper presents the results of recent efforts to develop the retracting vane element and to integrate it with a vapor core centrifugal pump in order to meet the fuel performance and functional requirements of an advanced gas turbine main fuel pump.

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