Surrogate models (or Reduced-Order Models) allow simulation users to explore and identify optimal process performance conditions faster than full, rigorous simulations. But there are times when users may find they are extrapolating beyond the data used to develop the surrogate model or when there is a desire to confirm the accuracy of the surrogate model. In these cases, the surrogate model can be used to enhance model performance, from both a robustness and performance perspective.

In this session from OPTIMIZE™ 21, The Dow Chemical Company provides guidance on how the surrogate and detailed model can be combined to provide the best of both worlds.