CPU+GPU heterogeneous parallel computing based natural frequency characteristic analysis method for turbomachinery blade

Abstract

The invention provides a CPU+GPU heterogeneous parallel computing based natural frequency characteristic analysis method for a turbomachinery blade. The method comprises the steps of firstly, establishing a finite element model according to a three-dimensional model and material parameters of a to-be-analyzed turbomachinery blade, and performing pre-stress analysis on the blade; secondly, performing blade grid data preprocessing, simultaneously calculating a rigidity matrix and a mass matrix of each unit in a CPU and a GPU, and assembling the rigidity matrix and the mass matrix into total rigidity and mass matrixes; setting constraint conditions of the blade and a rim, wherein the setting process comprises constraint of rigid and elastic displacement of a boundary, contact coupling of a blade root and the rim or contact coupling of connecting pieces and correction of the total rigidity matrix; thirdly, extracting generalized eigenvalues and eigenvectors of the total rigidity and mass matrixes by using a CPU+GPU heterogeneous parallel algorithm; fourthly, converting the eigenvalues and eigenvectors into a frequency and a vibration mode of the blade, and performing output; and finally, judging a vibration type of a natural vibration mode, and drawing frequency curve distribution, a vibration safety graph or a Campbell chart of the blade according to the vibration type.

Description

technical field [0001] The invention belongs to the field of engineering design and calculation, and in particular relates to a method for analyzing natural frequency characteristics of turbomachinery blades based on CPU+GPU heterogeneous parallel computing. Background technique [0002] In recent years, due to the powerful floating-point computing capability of GPU and its rapid development at a speed exceeding Moore's Law of CPU, GPU-based parallel algorithms have rapidly become one of the research hotspots in the field of high-performance computing. The traditional finite element parallel computing methods commonly used in engineering mainly use parallel processing technologies such as distributed computing, parallel computers or multi-threading at the technical level, or use GPU on a single computing node to solve general problems such as linear equations. Local acceleration, for many specific problems in the engineering field, the acceleration effect is very limited. ...

AI Technical Summary

Problems solved by technology

[0003] At present, there is no software dedicated to the analysis of the frequency characteristics of turbomachinery blades. The traditional general-purpose finite element software is too cumbersome for the analysis of complex components such as turbomachinery blades. With the improvement of engineering design requirements for calculation accuracy, As well as the deepening of the research on the whole ring of detuned blades, more nodes and units (tens of millions of levels) have to be used to simulate the actual blades. The calculation speed of general finite element software is no longer suitable for handling such a huge amount of calculations.

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