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Response Surface Methods in modeFRONTIER

​​A rich set of dedicated algorithms support engineers and researchers in building interpolating or approximating surfaces and predicting the behavior of the whole system for a wide range of operating conditions.

Assessing the response of a complex structure often requires a large number of simulations which can be computationally expensive. The Response Surface Methods in modeFRONTIER generate reliable meta-models able to approximate the multivariate input/output behavior of such multifaceted systems, improving the quality of the design knowledge and accelerating the optimization step based on real physics models.

A rich set of dedicated algorithms support specialists in building interpolating or approximating surfaces and predicting the behavior of the whole system for a wide range of operating conditions.

Within modeFRONTIER the RSM wizard allows training and validation datasets to be quickly built on the basis of existing or new tables. As well, engineers are enabled to import previously created RSMs and to perform a contextual screening task to refine the knowledge about variable correlations before the training of meta-models.

The RSM tool offers in-a-glance insights on the generated model quality and enables the designer to select the portion of designs to be evaluated virtually, for a smart exploitation of available computational resources


Automatic RSM Training mode

With the new Automatic RSM Training mode users can now go straigth from data to metamodels with less clicks and less parameter settings. While the manual RSM training wizard will still be available, the new automatic mode will allow to save time and is ideal for model selection.

RSM Evaluation chart

The new RSM Evaluation Chart is an all-in-one visualization tool showing relevant information for the quality evaluation of many RSMs. The chart can be used for comparing multiple metamodels trained for the same function in order to select the most accurate one.
Make response surface modelling easier and fast: the new RSM Trainer Node automatically trains multiple models simultaneously and identify the most accurate. READ MORE


 modeFRONTIER sophisticated RSM algorithms lead to
  • the ability to perform hundreds of experiments in seconds
  • superior accuracy of metamodels gained with the Validation tool
  • easy and quick wizard-based set-up
  • single-click switch from virtual to real optimization​

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