Parameter Estimation

How to tame a vast number of combinations

  use A I to learn material properties for e.g.

  • spotwelds with different material combinations
  • composites with different fiber or matrix materials
training results of machine learning models for parameter prediction training results of machine learning models for parameter prediction

check model validity

odd coverage, load distribution of experiments odd coverage, load distribution of experiments

analyzing input space

Your model parameters look perfect, but is your model valid within your load case?

  • find sparse areas where no experimental data exist
  • check if your simulation result is covered by experimental data

  use unsupervised learning methods