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28.10 Fast Fourier Transform (FFT) Postprocessing

When trying to interpret time-sequence data from a transient solution, it is often useful to look at the data's spectral (frequency) attributes. For instance, you may wish to determine the major vortex-shedding frequency from the time-history of the drag force on a body recorded during a FLUENT simulation. Or, you may want to compute the spectral distribution of static pressure data recorded at a particular location on a body surface. Similarly, you may need to compute the spectral distribution of turbulent kinetic energy using data for fluctuating velocity components. To interpret some of these time dependent data, you need to perform Fourier transform analysis. In essence, the Fourier transform enables you to take any time dependent data and resolve it into an equivalent summation of sine and cosine waves.

FLUENT allows you to analyze your time dependent data using the Fast Fourier Transform (FFT) algorithm. Information on using the FFT algorithm in FLUENT is provided in the following sections:




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