JuliaCon 2026

Models of engineering systems can be used for many purposes. The most basic type of analysis is a "what if" scenario where you want to determine either the steady state behavior of the system or how the system responds in time to disturbances. While these steady-state and transient analyses are quite common, they are just the tip of the iceberg when it comes to engineering workflows.

For example, when engineering products it is often useful to transform a given system model into an FMU for use in software-in-the-loop (SiL) or hardware-in-the-loop (HiL) applications. But unlike the steady-state and transient analyses, generation of an FMU requires a different set of steps. But the key is that it can be based on the same model. By introspecting the model it is possible to reconstitute it as an FMU.

Another common application is to perform some kind of model optimization or model calibration. Having access to the symbolic representation of the system allows us to exploit automatic differentiation for efficient computation of gradients. Again, we wish to pass a model as "input" and then perform some transformation or computation which generates engineering results or artifacts for us. In this case, the result will be a design that has been optimized according to a provided objective and constraints.

The list of these potential analyses is nearly endless. Not only that, every company in every industry has their own specific engineering processes so it is impossible to provide a fixed set of analyses that will satisfy everybody. This is exactly why we need an open ended framework for formulating these analyses.

In this talk, we will talk about how we leverage the power and immense ecosystem of the Julia programming language to provide a structured way of constructing engineering workflows. Within this analyses framework, it is possible to create your own workflows described via Dyad models, parameters and even nested workflows and use Julia to map those inputs into engineering artifacts (time series data, reports, diagrams, etc). All of this works equally well on the desktop as well as in continuous integration (CI) pipelines.

Once authored, these workflows can be extended and customized using the Dyad graphical user interface. This provides turnkey access to engineers across the organization without having to be experts in Julia. Those engineers provide the necessary inputs via the GUI and once the analysis is complete they can review the engineering artifacts in the same GUI.

Finally, it isn't just humans who benefit from these analyses because they are also fully recognized and understood by the Dyad agent. This means that when you create your own analyses, they become part of the toolbox that our Dyad agent can use in helping you answer your most pressing engineering questions.