As we all know, optimization is an iterative process in which the underlying analysis is run multiple times before the process converges to an optimal solution. Depending on the time required for each analysis run, this process could be a few seconds or hours long. The resulting optimal is tied to the initial values and bounds on the constraints and design variables. In practice, constraints are constantly changing as Engineers try to balance cost and performance metrics. As part of this process, questions may arise such as ‘how would the optimal change if the bounds on the constraints increased or decreased?’. The answer to this would require discarding the results from the optimization study and re-running the entire optimization study with the new bound values. This may not be economical considering the time and cost requirements. To address this, what-if utility was built into Iliad to enable quick predictions by re-using available data and eliminating the need for new optimization runs.

The What-if utility works by fitting a regression model on select data points and then using it for predictions. The new ‘What-if’ utility offers significant advantages over the old one. For starters, the user can now easily switch between different models using the graphical user interface. Earlier, the user could only use one model at a time.

When the user launches the What-if, all possible polynomial approximation models and radial basis interpolation models are loaded into the tool and presented to the user in a few seconds. Because of the robust data filtering mechanisms and the power of the underlying DOT optimizer the user is guaranteed to get quick and accurate predictions as seen in Fig 2. For best results, the user is advised to limit the changes in constraints to less than 2.5%. Try it out today!