Analyzing large amounts of data can take seemingly forever. Animating images to a movie takes an entire weekend to complete. This Webinar shows how Tecplot’s Python API can take advantage of multi-process parallelism. The script used in the webinar is completely general, go ahead and download it and try it out.

If you find yourself doing the same thing over and over again you can save a lot of time by automating it. You can also, unfortunately, use up a lot of time in development. A quick and easy approach is to carry out the sequence of steps once and let the application record the actions. But you can do a lot better if you choose a different approach, as we’ll see in subsequent issues. See this article to get the terms right: as with most things in IT, why have one term or one meaning when we can make things more confusing?

Orthogonality and cell-spacing are desirable grid characteristics, as discussed earlier. The von Lavante/Hilgenstock/White formulation in Pointwise is precise, but can be unstable. The Steger-Sorenson formulation is stable but can be imprecise: for example, in highly concave regions the first grid point off the wall may be slightly farther away from the wall than specified. This brief video provides an overview. Don’t forget to review Angle Constraints and Spacing Constraints.