Model Diagnostics for Equation-Oriented Models: Roadblocks and the Path Forward

Abstract

Equation-Oriented (EO) modeling techniques have been gaining popularity as an alternative for simulating and optimizing process systems due to their flexibility and ability to leverage state-of-the-art solvers inaccessible to many procedural modeling approaches. Despite these advantages, adopting EO modeling tools remains challenging due to the significant learning curve and effort required to build and solve models. Many techniques are available to help diagnose problems with EO process models and reduce the effort required to create and use them. However, these techniques still need to be integrated into EO modeling environments, and many modelers are unaware of sophisticated EO diagnostic tools. To survey the availability of model diagnostic tools and common workflows, the U.S. Department of Energy�s Institute for the Design of Advanced Energy Systems (IDAES) has conducted user experience interviews of users of the IDAES Integrated Platform (IDAES-IP) for process modeling. The interviews reveal a gap between the availability and utilization of model diagnostic tools driven primarily by a lack of awareness of and lack of standard interfaces among different tools. To address this gap, the IDAES team has developed a recommended workflow for integrating diagnostics into the model development process and an IDAES Model Diagnostics Toolbox that provides a standard interface for many of these best practices. This paper identifies barriers to the widespread adoption of diagnostic tools for EO models and reduces these barriers by providing a standard, user-friendly interface for many different tools.