Peculiarities of identifying a power-generating single-shaft gte mathematical model
Keywords:
mathematical model, identification, gas turbine engine, variable parameters, controllable parameters, objective functionAbstract
The processes of designing and developing gas turbine engines (GTE) are based on using mathematical models (MM), reflecting the physical picture of engine operation processes. One of the ways of improving the MM validity is its identification on engine bench test results. Identifying MMs of modern energy GTEs is a very demanding task due to the necessity to identify the main controllable engine parameters determined in the course of experimental studies, depending on a large number of the parameters that are not controlled during the experiment. In this regard, the actual direction of reducing the complexity of the process of identifying MMs is using identification software systems. Developed by the A. N. Podgorny Institute of Mechanical Engineering Problems of NASU, the methodology and means of identifying the parameters and characteristics of power plants, using experimental data (Otpimum software package), allows one to conduct a directed search for an optimal solution based on modern mathematical methods. This, in turn, leads to a reduction in identification execution time, increases the MM adequacy and allows one to more reliably determine the characteristics of engine components. The article proposes an approach to identifying a non-linear unit MM, with a detailed calculation of a turbine flow path to the level of blade rows on the D045 engine bench test results. It describes the choice of variable and controllable parameters as well as the ranges of their changes. The results of solving the identification problem showed the possibility of using the Optimum software for optimizing and identifying parameters and characteristics of power plants when identifying D045 GTE MMs. The use of the developed methodology for identifying GTE MMs that is based on bench test results, allows one to take into account the maximum number of variable variables and significantly reduce the complexity and time of this process. The analysis of the results shows that with significant deviations of GTE characteristics from design values, a large amount of a priori information is needed to solve the identification problem. On the basis of the information, ranges of changes of variable and controllable parameters are assigned, as well as their values in the first approximation.References
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