Each history curve can be pointwise (at each sampled time-step) approximated using metamodels. These approximations of the entire history curves in time-domain are called predicted histories. These history approximations are used to study the influence of changes in the variables as well as for parameter identification problems.
The approximation of histories is enabled by setting the Approximate Histories flag on the Features page of the Sampling dialog as shown in the figure on the right.
While the approximation models for the histories and responses can be different, the number and location of sampling points remain the same such that all options for history approximation may not be suitable depending on the number of available data points, for example, if the response sampling is linear polynomial the number of points sampled would not be sufficient to approximate the histories using a quadratic polynomial and that option should be avoided.
It is also important to note that approximation of histories may take significantly long as approximations at thousands of time-steps are carried out.
Remarks
Calculation of Predicted Histories
The following steps are carried out to calculate a predicted history.