LSTC's LS-OPT® Optimization Software
Livermore Software Technology Corp. (LSTC) years ago predicted the future for engineering analysis on large scale models required optimization software. At that time, they began developing an optimization software, under the direction of Dr. Nielen Stander. LSTC named their optimization software LS-OPT®, which is a registered trademark of LSTC.
The development success of this software allowed the LS-DYNA users to structure the design process, explore the design space and compute optimal designs according to specified constraints and objectives. Realizing that this software was needed by the LS-DYNA users, LSTC made the decision not to charge any fees for the use of LS-OPT. LS-OPT is included with LS-DYNA, at no additional fees. Although LS-OPT was designed for LS-DYNA it is a stand alone optimization software that can be linked to any simulation code.
Optimization is a mathematical procedure for minimizing or maximizing
a function of independent variables subject to constraints on other
functions or the variables themselves.
In mechanical design, these functions are measures of goodness of the
design such as safety, efficiency or serviceability and depend on a set
of changeable parameters. Optimization is usually applied to responses
as produced by mathematical models, e.g. finite element models. During
the optimization process the parameters are systematically changed using
an algorithm.
There are two basic areas of application of
optimization in Mechanical Design:
1. Optimal Design. This is a procedure
whereby a mechanical design is optimized with the purpose of achieving
the best performance. Various types of parameters can be changed namely
sizes (such as thickness), shape or material properties. An example is
the optimization of structural measurements of a vehicle frame for the
purpose of achieving maximal crashworthiness.
2. System identification. This is a
procedure whereby unknown properties of a system are identified using
experimental response data. A typical objective is to minimize the
discrepancy between the responses of the model and those of the
experiments. For instance, material parameters of a sample can be
determined from acceleration or force measurements during impact.