To view results from manual what-if studies, LS-OPT provides a great way to import these results so we can take advantage of its data visualization package. The attached image, an excerpt from the LS-OPT Manual, shows how we can do this.
Sensors can be used to trigger entities based on certain criteria. The following image is a high-level steps involved to take advantage of sensors in LS-DYNA.
Update The blog no longer seems to exist. I recently came across a nice blog written by QUI. It is remarkable that he is willing to share examples and his experiences in LS-DYNA. The broad spectrum of LS-DYNA applications can never be fully covered by a single blog or a small set of publications. It…
You can download the LS-DYNA 971 r4 Manual (PDF, 11.5 Mb) Update The broken link has been fixed
The LS-OPT Version 4.0 beta release is now available at: LS-OPT 4.0 The Presentations folder has an overview and outlook of LS-OPT. The main feature is the next generation post-processor (Viewer). Note that LS-OPT/Topology will be available later in 2009 as a separate module.
Starting version 3.0, LS-OPT supports the definition of discrete variables. Discrete type of design parameters are helpful when there is a need to find the optimum values from a “set” of values. A good example would be the choice of element formulation. The possible values for LS-DYNA for a quad can only be a subset…
LS-OPT is widely used to optimize designs or parameters using a number of experiments obtained by running LS-DYNA simulations. The number of experiments (simulations) per iteration is dependent on the number of variables defined in LS-OPT in addition to the type of point-selection (DOPT, LatinHyperCube, etc). When a large number of simulations are involved, it…
LSTC has introduced a free limited LS-DYNA version for U.S. unemployed LS-DYNA users as a result of the current poor economic conditions. A free LS-DYNA course may also be introduced in the coming months. Please contact Marsha Victory at 925 449 2500 or send her an email at marsha@lstc.com.
In LS-OPT, one can run a multi-disciplinary optimiztion or a multi-solver type optimization problem, where the variables can be shared among the different solvers. In performing DOE or any optimization using LS-OPT, it is important that consistent experimental points are used in the evaluations. To ensure this, one can use solver experiment duplicate solver_1 command…
In a previous post about a simple Python script that scans a LS-DYNA input file to package all INCLUDED files recursively so the entire model can be compressed and sent to the recipient. Based on some new suggestions, largely by Brian Wainscott, I have attached a revised script that handles the included files a little…
