Random fields based on measurements

Often one is faced with the question of how to describe a field quantity (e.g. geometry variation, stress, strain variation, load strain curve). For example, the traditional way would be to describe signal data by parameters.

If enough measurements or simulation results from a DOE are available, parameterization can be performed using empirical random fields. The dominant variation patterns are automatically identified from the data. The variation patterns are sorted according to their importance. A parameter is then assigned to each variation pattern.

This auto-parameterization is optimal, i.e. it is ensured that a maximum of variation can be represented with the smallest possible number of parameters. The parameterization can be used to

  • find a statistical description (correlation in space/time, distribution type, etc.) based on measurements and store it for subsequent applications, or to
  • generate new random designs (e.g. signals, geometries, etc.).

An integration in optiSLang is available for generating random fields.


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Information material

Your contact person

Dr. Sebastian Wolff

Fon: +43 (0) 1997 1207-10
Fax: +43 (0) 1997 1207-20