Transforming Equation-Based Models in Process Engineering

For the solution of realistic dynamic optimization problems, the computation of derivative information is typically among the crucial ingredients in terms of both numerical accuracy and execution time. This work aims to incorporate automatic differentiation into the DyOS framework for dynamic optimization. In this framework, the optimization algorithms and the mathematical models of the process systems under consideration are implemented in separate modules. In real-life settings, a process system is formed by integrating different submodels which are possibly formulated by means of different equation-oriented modeling languages such as gPROMS or Modelica. DyOS is currently redesigned to be capable of handling such component-based models by relying on a common intermediate format called CapeML, which defines a layer of abstraction so that various models can be expressed in a manner independent from a specific modeling language. Hence, CapeML is the adequate format to which automatic differentiation is applied in this dynamic optimization framework. A novel system called ADiCape is proposed, implementing the forward mode for models written in the XML-based language CapeML. This AD transformation is expressed in the form of an XSLT stylesheet.