Abstract
The development of the mathematical apparatus and computer technology leads to an increasingly widespread use of optimization methods in the design and development of turbomachines. The use of such methods makes it possible to automatically vary hundreds of variables and to determine the best combination considering the existing restrictions. Building the optimization based on 3D models allows to find new reserves for improving turbomachines by managing 3D effects and considering the mutual influence of elements on each other.
In this work, the problem of finding the best constructive solution for a single-stage uncooled turbine of a small-sized gas turbine engine for a helicopter is described using modern software tools for numerical simulation and optimization. Optimization was carried out according to the results of gas-dynamic simulation of the turbine working process, as well as strength analysis of the static and dynamic strength of its rotor wheel (RW).
The optimization algorithm was implemented in the IOSO program according to the following algorithm. At each step, IOSO formed a vector of variable parameters, which described the geometry of the turbine in a parametric form. On this basis, a model of the working process of the turbine was formed in the CFD program, as well as a finite element strength model of the rotor blade. For each RW configuration, a strength calculation was carried out and, if necessary, a gas-dynamic calculation. The results are transferred back to the optimizer as a text file. An automatic analysis of the results is carried out there, selection of points in the Pareto front, and a new set of initial parameters was formed. The cycle was repeated until the desired result was achieved.
Analysis of the baseline turbine showed that the RW has poor strength margins. The solution of this problem requires the re-profiling of the rotor blade, however, in this case, the parameters of the turbine working process could deteriorate. Therefore, the task was solved step by step. At the first stage, the strength state of the rotor blade was optimized without considering gas dynamics. Then this variant of the turbine was set as initial for the coupled gas-dynamic and strength optimization.
During the optimization, the shape of the profiles of the nozzle guide vanes and the rotor blades was changed, and the cross sections in the axial and circumferential directions. The shape of the flow path (the diameters and width of the blades did not change). In total, 76 variables were used to describe the shape of the blades.
As a result of the first stage, a variant of the rotor wheel was found that meets the strength requirements, but the efficiency of the stage fell by 2%. This decision was taken as an initial one for multidisciplinary optimization. Its results showed the impossibility of obtaining a variant of the RW with satisfactory strength without reducing the efficiency relative to the baseline turbine.
Analyzing the results of solving two optimization problems, it was concluded that to ensure the required strength margin of the RW and maintain a high level of efficiency, it is necessary to change the shape of the flow path and the design of the turbine. For this, an array of possible solutions was formed: a wheel without a shroud segment, changing the diameters and shape of the flow path, etc. For each design variant, the multidisciplinary optimization was performed in order to obtain the required strength margins of the RW at a high level of turbine efficiency.
As a result, a design solution was found that provided sufficient strength margins with an increase in the efficiency relative to the baseline turbine.
Multidisciplinary Optimization of a Single-Stage Uncooled Axial Turbine of a Gas Turbine Engine
Category
Technical Paper Publication
Description
Submission ID: 3509
ASME Paper Number: GT2020-14896
Authors
Igor Egorov Moscow Aviation Institute
Grigorii Popov Samara National Research University
Oleg Baturin Samara National Research University
Evgenii Goriachkin Samara National Research University
Anton Salnikov Central Institute of Aviation MotorsEvgenii Marchukov Moscow Aviation Institute

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