Optimization

LMS Virtual.Lab Optimization

LMS Virtual.Lab Optimization drastically improves the efficiency of any LMS Virtual.Lab-based engineering process by accelerating exploration of design alternatives, by finding the optimal solution to any design problem and by modeling uncertainty to manage risk. New scripting capabilities have increased the scalability of LMS Virtual.Lab Optimization is also much more scalable.





Design Space Exploration

Design Space Exploration allows users to automatically explore and visualize the design space through the use of a wide variety of Design Of Experiments (DOE) techniques. DOE methods sample the design space with a minimum number of experiments, yielding the most relevant information about the design’s performance. The results of these virtual experiments give critical insight into the variations of a design and the related ‘trade-offs’.

Response Surface Modeling

Design Space Exploration is mostly used in combination with Response Surface Modeling (RSM), which fits a continuous surface through the discrete data to get more insight into the influence of the design variables on the specified result quantities. This surrogate model allows the user to replace expensive simulation sequences.