About ASGRET
- ASGRET
- - Automated System of Gas-dynamic Research of Energy Turbomachines - CAE System for mathematical modeling of power machine thermodynamic processes.
It allows you to perform most kind of the thermal and gas-dynamic analysis related to the setting of gas turbine and combined engines and plants and engines with variable working process at all stages of the life cycle, including design, testing, operational development, mass production and operation.
The system is open, allowing connection of modules of any required units and modules implementing the new tasks. It is filled with models of units 1, 2 and 3 levels (including detailing by stages and with two-dimensional gas-dynamic models). It provides simulation of engine with up to five shafts and five circuits and with possibility its number increasing if necessary. It allows the various characteristics calculation (throttle, altitude – speed, climate, performance and so on) at a steady state; different characteristics in transient operating conditions (including acceleration, advanced acceleration, speed drop, and advanced speed drop), and also engine start (starter characteristics are given or can be determined).
It allows you to carry out engine parameters sampling, i.e., to select parameters and basic dimensions of the setting to ensure the engine performance with the given specifications, to produce engine parameters optimization that provides maximum or minimum specified scalar or vector target function. Wherein any input data parameters may be varied and output data may be imposed with any constraints. Various optimization algorithms with their automatic choice during the search are used.
Furthermore, the identification of the engine mathematical model is possible according to its test results on the test bed or in the flight, i.e. adjustment of low reliability input data selected by the user. Herein the identification for steady-state conditions on the measured parameters and for transient conditions — by parameters getting from oscilloscope is provided.
System allows performing technical diagnostics of the engine by the measured thermo gas dynamic parameters with detection of one, two or three defects presenting in the engine setting.
System allows simulating of test beds of GTE and its units with subsequent certification of designed test bed that has not been made as hardware yet, using a special task "stochastic model of GTE and its units".
System allows obtaining so-called “transfer” models of GTE, GTE test beds, and its units for automatic control system (ACS) and flight and navigation systems (FNS) design and development.
System enables to integrate mathematical models of gas turbine plants and ACS, and perform analysis for selecting the optimum GTE control and projected ACS development (definition of values for setting of the feedback factors, etc.).
Tasks
Throttle characteristics
This module is designed for the calculation of any throttling or load characteristics under all environmental conditions, at different altitudes and flight speeds, if it is an aircraft engine. The mode of the engine operation, the height and the flight Mach number at this point must be specified for each calculation point. Parameters for standard atmosphere condition are used. Number of calculation points is not limited. Basically, this module can calculate altitude and speed and climatic characteristics of GTE also, but it is not advisable because of the increased amount of data input.
Altitude-speed characteristics.
The module is designed to calculate the altitude and speed characteristics on any engine operating modes with a reduced amount of data input. For the calculation maximum, minimum Mach number and a step on it, maximum, minimum flight altitudes and a step between points on height, as well as all analysis modes should be given. Control program is set, which may include several control laws.
Climatic characteristics.
The module is designed to calculate the throttle or load characteristics in environmental conditions change, i.e., change of temperature and ambient pressure. These values must be preset. Standard atmosphere is not used in this module. Mach number and flight control program is also defined. Step of temperature and pressure changes, as well as it limit can be defined.
Approximation of characteristics.
The module has an auxiliary function. If necessary, it performs an approximation of any unit characteristics. There are various approximation algorithms and options providing input data for it. The most difficult is the approximation or tabulation of compressor characteristics due to the presence of vertical branches and surge curve. It was developed a special version of the module for it, in which the variables are replaced. After that the compressor characteristics are very flat, so after tabulating the data is selected from the tables with a minimum error. They are easy to approximate. However, there are four original graphs instead of two ones.
Characteristics with one-dimensional optimization.
The module is intended for calculation of the engine throttle characteristics with automatic selection of the one of the parameters value, providing the minimum or maximum of a given target function (optimization criterion). For example, the maximum power on the output shaft of the power turbine may be calculated for different values of rotational speed of the turbo-compressor, or the altitude may be calculated at which the fuel consumption is minimal.
Characteristics in fuzzy numbers.
The module provides calculation the spread of throttle characteristics parameters (responses) caused by the simultaneous spread of multiple input engine parameters (factors). It may be ambient conditions or errors of geometrical sizes. Change limits are set for them as a percentage of the nominal value. Algorithm is used a full factorial experiment.
Stochastic characteristics.
The module is also provides calculation the spread of throttle characteristics parameters, and not change limits of factors and parameters are set, but their distribution law is. The calculation for responses gives their distribution laws parameters also. The uniform, normal (Gauss law) or truncated normal laws are commonly used.
Dynamic characteristics.
This module is intended for transient analysis. It provides calculation of all parameters by the time when the engine switching from one given mode to another. Modes of operation and the control laws of the engine can be arbitrary.
Influence coefficients.
This module linearizes dependencies, and calculates tables, each element of which shows the percentage of the response change when factor will change in the one percent. Set of responses and factors is specified. Any parameter of the input data can be the factor, and any parameter of operating results array can be response.
GTE basic parameters sampling
The described above mathematical model provides only verification analysis of GTE, so all its basic dimensions and characteristics should be specified. This is very useful for operational development or modernization, i.e. for most large-scale calculations in the industry, but it does not apply during the new GTE establishing, when the required data is simply absence. In this case, you must start with the GTE basic parameters sampling. It uses an unusual artificial control law, which has different options. Constant values of parameters are set instead of units characteristics. Usually the engine thrust (or power, for turboshaft engine) and the maximum temperature of the gas before the turbine is specified. In this case the discrepancy on thrust (or on output shaft power) is arranged and the flow rate through the engine varies. Other options are possible. Such parameters sampling is the simplest and is used mainly for the setting options pre-selecting and in the student projects. In more complicated cases, where the designed engine manufacture is expected and the best parameters must be obtained, it is recommended to use the multidimensional optimization module.
Multidimensional optimization.
The module is intended to find the optimal variant of the engine setting. Its use begins with the selection of the target function (optimization criterion), on which the engine perfection degree is estimated. Detailed guidance on its choice for different types of aircraft and ground vehicles are developed. List of parameters, which can be changed in the search process, is compiled. They define the task dimension. Limitations of the first and second kind are specified, which define the search space. The specially designed algorithm is used for search, but any other algorithms described in the literature may also be applied. In any case, each step of the search is addressed to the mathematical model. Best results have been obtained in the process of finishing development of the setting when the majority of sizes are already impossible to change and thus the task dimension is reduced, and the mathematical model accuracy can be improved by identification.
Diagnostics
The module is intended for the GTE setting diagnostics by thermo gas dynamic parameters during exploration. The algorithm is based on the developed library of possible defects. In case of differences between the measured and the reference values all defects presented in the library for this engine or this instance are turned over, and the most probable defect reveals among them. It provides the minimum value of discrepancy squares sum between the parameters of the tested and the reference engine. In the search process, the magnitude of the researched defect varies also.
Identification..
The module is intended to improve the mathematical models accuracy, as well as for specific GTP diagnostic. It can be used when you already have the results of the engine or its separate units parameters measurements during operation or tests. The algorithm begins with calculation by mathematical model of the same parameters that were measured, and under the same conditions. Difference between calculated and measured values forms an array of discrepancies. Weighted sum of their squares is minimized by changing the values of the least reliable mathematical model parameters. Minimization algorithm is heuristic. The resulting identification posteriori model has better accuracy than the original a priori one. It can be successfully used for performing of any calculations with the listed above tasks modules. This module is the most widespread, since it proved to be very effective in fine-developing and modernization of engines.
Calculation of the gas turbine parameters.
It performed by the mathematical model of the third level of complexity that describes the workflow in the turbine setting, the geometric dimensions of which are given. All the parameters are considered averaged over the cross section, and all the formulas are written for the average diameter (average flow line). Spatial character of the flow can be considered by correction only. This module puts in the delivery set by special order only. The basic version uses the model of the second level of complexity.
Calculation of the axial compressor parameters.
It performed by the mathematical model of the third level of complexity that describes the workflow in the compressor setting, the geometric dimensions of which are given. All the parameters are considered averaged over the cross section and all the formulas are written for the average diameter (average flow line). This module puts in the delivery set by special order only.
Calculation of the axial compressor setting.
It performed by the mathematical model of the fourth level of complexity that describes the workflow in the compressor setting, the geometric dimensions of which are given in several radiuses. All the parameters are calculated on these radiuses. This module puts in the delivery set by special order only.
Optimization of own models.
The module is intended for search of the optimal variant of any of mathematical models, out of the system, so it always delivered optionally. It can be used when the customer has its own adequate mathematical model. Optimization begins with the selection of the target function (optimization criterion), which can estimate the product perfection degree. This module has been popular in the past, but is now a large number of optimization packages appeared on the market, some of which are faster.
Identification of own models
The module is intended to enhance the accuracy of any mathematical models, out of the system, so it always delivered optionally. It can be used when the customer already has its own mathematical model and the item test results that describe this model.