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Link: ANSYS Manual on FFT Postprocessing
40.10. Fast Fourier Transform (FFT) Postprocessing
When interpreting time-sequence data from a transient solution, it is often useful to look at the data’s spectral (frequency) attributes. For instance, you may want to determine the major vortex-shedding frequency from the time-history of the drag force on a body recorded during an ANSYS 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.
ANSYS Fluent enables you to analyze your time dependent data using the Fast Fourier Transform (FFT) algorithm. Information on using the FFT algorithm in ANSYS Fluent is provided in the following sections:
Limitations of the FFT Algorithm
[134] C. Temperton. "Implementation of a Self-Sorting In-Place Prime Factor FFT Algorithm". Journal of Computational Physics. 58. 283–299. 1985
https://www.sciencedirect.com/science/article/pii/0021999185901640
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