A Guide to Random Data Analysis for Computational Fluid Dynamics

Today’s CFD engineers will increasingly find themselves in situations where they need to integrate reliable statistical measures into their everyday post-processing routines.

At the beginning of a transient CFD analysis, the flow field is typically assigned an arbitrary initial condition or steady state solution.  This solution must be advanced to a fully-developed statistically stationary state before meaningful sampling can begin.

Authored by engineers with over 15 years of CFD experience, the Guide to Random Data Analysis for Computational Fluid Dynamics is intended to serve as a point of reference to aid the everyday CFD engineer when post-processing transient flow field data.

What’s Inside:

•    Chapter 1: Techniques for Transient Flow Field Data
•    Chapter 2: Introduction to The Fast Fourier Transform
•    Chapter 3: Understanding The Fast Fourier Transform Inputs
•    Chapter 4: Application of The Fast Fourier Transform
•    Chapter 5: Accuracy of Your FFT and Parseval’s Theorem
•    Chapter 6: The Short-Time Fourier Transform
•    Chapter 7: Cross-Coherence
•    Chapter 8: Auto and Cross Correlation
•    Chapter 9: Two-Point Statistics

Download your complimentary guide now to get commonly used mathematical approaches that may be useful for interpreting transient data in a CFD analysis.