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FAQs regarding setup of an optimization problem in LS-OPT
Strategies for metamodel-based optimization
There are three strategies for automating the metamodel-based optimization procedure. These strategies apply to the tasks Metamodel-based Optimization and RBDO, and are available in the Task dialog.
Strategy Single Iteration vs. Sequential
The two strategies for the calculation of global metamodels Single Iteration and Sequential are investigated.
Which meta model to choose?
Remarks and hints on selection of Meta-Model
Constrained space filling - Reasonable Design Space
In this part, we’ll look deeper into how the space filling point sampling algorithm works. Also, the definition of sampling constraints will be explained.
Can LS-OPT handle discrete variables?
LS-OPT can handle discrete variables and even discrete variables in combination with continuous variables, as well as discrete variables with string values.
How can I ensure that LS-OPT replaces the variables in the input file by integer values?
I defined a discrete variable with a list of integer values, but LS-OPT replaces the variables in the input file by e.g. 1. with a dot.
How can the number of solver jobs to be run in parallel be defined?
Specifying Computing Resources for Concurrent Processing
Is it possible to skip the reading of large include files?
The reading of big files can be skipped in the following way:
How can I determine the time value where a history curve takes a specific value?
Using Lookup, LookupMin and LookupMax
Result extraction for LS-DYNA input files using *CASE
How can I define in LS-OPT which output files are used for result extraction if I have mutliple output result files because of *CASE?
Probabilistic Variables: What is the difference between control and noise variables?
A probabilistic variable is completely described using a statistical distribution. The statistical distribution defines the mean or nominal value as well as the variation around this nominal value.