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Realization method of aeroelastic optimal design of turbomachinery considering random detuning

A technology of aeroelasticity and impeller machinery, applied in computer-aided design, design optimization/simulation, multi-objective optimization, etc., can solve problems such as blade fatigue failure, accidents, blade cracks, etc., to reduce sensitivity, improve life, and reduce forced Effect of Vibration Amplitude

Active Publication Date: 2021-10-19
SHANGHAI JIAO TONG UNIV +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

These two forms of vibration will increase the stress on the blade and cause fatigue failure of the blade within a limited number of vibration cycles: at the slightest, the blade will crack, and at the worst, the blade will break, causing serious accidents

Method used

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  • Realization method of aeroelastic optimal design of turbomachinery considering random detuning
  • Realization method of aeroelastic optimal design of turbomachinery considering random detuning
  • Realization method of aeroelastic optimal design of turbomachinery considering random detuning

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Embodiment Construction

[0047] Such as figure 1 As shown, this embodiment relates to an optimal design method of turbomachinery aeroelasticity including random detuning, including the following steps:

[0048] Step 1: Select an axial fan blade, and use the function (blade parameter extraction unit) written by Matlab to parameterize the original blade.

[0049] Step 2: Experimental design: According to the number of blade design variables and the upper and lower limits of each variable, use Latin hypercube sampling to generate an appropriate number of experiments.

[0050] Step 3: Use the custom Matlab function to drive the Turbogrid module in the computational fluid dynamics software CFX to divide the single-channel grid of the flow field, such as figure 2 shown. The surface of the blade is an O-shaped grid, and the grid scale meets the requirement that Y+ is less than 5. Import the single-channel flow field grid into CFX-Pre, and use Turbo Rotation to copy (N-1) grids with the rotation axis to o...

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Abstract

An implementation method for the aeroelastic optimization design of turbomachinery including random detuning, flutter calculation based on influence coefficient method, foundation detuning model and forced vibration analysis of Monte Carlo method, under the premise of constrained aerodynamic performance and static stress , so that the industrially processed blades have similar vibration characteristics under different installation methods; the flutter stability is significantly improved and the forced vibration response of the blades is reduced in the case of random detuning. This method is for the selected axial flow fan blades, On the premise of constraining the aerodynamic performance and static stress, the minimum aerodynamic damping increases by about 19% and the maximum forced vibration amplitude decreases by about 18% under random detuning.

Description

technical field [0001] The invention relates to a technology in the field of aero-engine manufacturing, in particular to a method for realizing the optimal design of turbomachinery aeroelasticity taking into account random detuning. Background technique [0002] As the working part of the turbomachinery, the blade is subjected to various loads (such as the centrifugal force generated by the rotation, the unsteady aerodynamic force generated by the wake of the upstream vane / guide vane, etc.), which will not only affect the aerodynamic performance but also cause Blade vibration problem. Therefore, in order to ensure efficient and safe operation, the design of the blade must take into account both aerodynamic and structural performance. [0003] The aeroelastic vibration caused by the interaction between the blade and the fluid will lead to the fatigue failure of the blade. The two most common aeroelastic phenomena are: 1. Flutter; 2. Forced vibration. Flutter is a self-excit...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/17G06F30/23G06F111/04G06F111/06G06F113/06G06F119/14G06F119/18
CPCG06F30/17G06F30/23G06F2111/04G06F2111/06G06F2113/06G06F2119/14G06F2119/18
Inventor 范城玮吴亚东
Owner SHANGHAI JIAO TONG UNIV
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