| Autor: |
Inoue, Tomoki, Matsuda, Yu, Ikami, Tsubasa, Nonomura, Taku, Egami, Yasuhiro, Nagai, Hiroki |
| Předmět: |
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| Zdroj: |
Physics of Fluids; Jul2021, Vol. 33 Issue 7, p1-10, 10p |
| Abstrakt: |
We propose a noise reduction method for unsteady pressure-sensitive paint (PSP) data based on modal expansion, the coefficients of which are determined from time-series data at optimally placed points. In this study, the proper orthogonal decomposition (POD) mode calculated from the time-series PSP data is used as a modal basis. Based on the POD modes, the points that effectively represent the features of the pressure distribution are optimally placed by the sensor optimization technique. Then, the time-dependent coefficient vector of the POD modes is determined by minimizing the difference between the time-series pressure data and the reconstructed pressure at the optimal points. Here, the coefficient vector is assumed to be a sparse vector. The advantage of the proposed method is a self-contained method, while existing methods use other data, such as pressure tap data for the reduction of the noise. As a demonstration, we applied the proposed method to the PSP data measuring the Kármán vortex street behind a square cylinder. The reconstructed pressure data agreed very well with the pressures independently measured by pressure transducers. This modal-based approach will be applicable not only to PSP data but other types of experimental data. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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