The user must write a subroutine that packages this data into a TECPLOT ASCII. Typically, a user has an application program (fluid flow solver, engineering stress program, aeronautic simulator, heat flow program), that produces lots of data. This method could be employed to round to other digits by altering the scale factor. TECPLOT ASCII files are used by the TECPLOT program, which is a visualization program for technical data. After rounding, Data is divided by 10 to rescale it properly. The round function always rounds to the nearest whole number so by multiplying Data by 10 before rounding, the tenths digit is temporarily shifted to the ones digit. In this example, Data is rounded to the nearest tenths digit (0.26 would be rounded to 0.3) and stored in variable RoundedData. You can round more precisely using an equation of the following form: In this example, a new variable named Data is rounded to the nearest whole number and stored in variable RoundedData. Then you have a sufficient number of time steps to compute the RMS without transient data.Alter > Specify Equations and enter the following equation:

Continue to run the software until the window averaging of the FFTs converge to a constant signature. As you add each window and then average, if the frequency signature changes considerably, then you have not eliminated the transients. Perform an FFT on each window, then sum and average each FFT together to get one window. If you have 100,000 time steps, try 25,000 time steps each, where the first window is 1-25k, the second is 12.5k-37.5k, the third is 25k-50k, the fourth is 37.5k-62.5k, etc.

Simply take your time accurate data set (preferably second order accurate in time) and divide it into windows of equal size. I recommend looking at Welch's method for windowing. In theory, if the window size is sufficiently sized, there will be very little variance between each window. To do the FFT, you'll want to use multiple segments of the data that over lap. The second is to perform a Fast Fourier Transform (FFT) analysis of the data. The first is an RMS (root mean square) of whatever parameter you are targeting. The best way I've seen this done is to compute two quantities. One of the more perplexing issues is determining if the transient data is eliminated from your data when computing the mean.

Tecplot incorrect data