During a design exploration study, HEEDS makes many calls to your simulation model to evaluate potential designs. This means that your model needs to accurately predict design performance values (objectives and constraints) over a wide range of inputs (design variables). Most modern simulation models satisfy this requirement without difficulty.

But in some cases, it is too much to ask that a model be perfect for all combinations of variable values. For example:

- In a shape optimization problem, some combinations of shape parameter values might produce invalid geometries, making it impossible to generate a CAD model for those designs. Ideally, shape parameters should be defined in a way that ensures all geometries are valid, but that is not always a realistic expectation.
- Nonlinear or dynamic CAE models occasionally experience problems with convergence or other kinds of numerical errors. Hopefully your models are robust, but it is more difficult to predict the behavior of some designs than others, so numerical errors will occur now and then.

Of course there are many other reasons why a simulation model might terminate prematurely or predict incorrect results. Because many of these cases are unavoidable, HEEDS has been designed to be robust against these model failures. We refer to these as *error designs*. Continue reading