Fluid-analysis-based fluid parameter estimation method

Abstract

The invention provides a fluid-analysis-based fluid parameter estimation method. The method comprises the steps: carrying out empirical mode decomposition; to be specific, decomposing each frame of collected fluid velocity field into modes with different frequencies, thereby keeping information in a frequency domain; carrying out fluid velocity field dimensionality reduction; to be specific, carrying out integration on the decomposed model set and compressing the integrated one into a base and projecting calculation in three-dimensional space to sub space with a small scale, thereby reducing the calculation cost substantially; carrying out fluid simulation parameter estimation; to be specific, carrying out fluid simulation parameter back deduction in the sub space by using the collected fluid data according to an euler fluid simulation method; and carrying out re-simulation or fluid sequence editing; to be specific, reproducing a collected fluid sequence by using the fluid simulation parameter obtained by back deduction or carrying out parameter and boundary condition modification, and editing the fluid sequence. According to the invention, the empirical mode decomposition process is accelerated by using a GPU; and implementation of the process in the three-dimensional space is improved, so that the process can be completed within acceptable time.

Description

technical field [0001] The invention relates to the technical field of fluid simulation, in particular to a fluid parameter estimation method based on fluid analysis. Background technique [0002] Since the early 1990s, a variety of fluid simulation techniques have emerged in the field of computer graphics, discretizing and iteratively solving incompressible Navier-Stokes. In recent years, a large number of fluid acquisition technologies have emerged in computer graphics, computational fluid dynamics and related engineering disciplines, such as Particle Image Velocimetry, Time-resolved Schlieren System, fluid surface modeling, based on The method of optical flow analysis and so on. Due to the nonlinear and unsteady characteristics of fluids, it is difficult for existing analysis techniques (such as Fourier transform) to obtain ideal results. Therefore, the collected fluid data requires more powerful analysis methods to describe their complex internal characteristics. [00...

AI Technical Summary

Problems solved by technology

The traditional fluid dimensionality reduction technology uses the basis generated by principal component analysis (PCA). This method of building a basis naturally keeps the error minimum, but lacks information in the frequency domain, which will lose the details of the fluid and cause differences. Mutual interference of information on the frequency, the basis needs to be improved to prevent these situations from happening

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