The IDAES Process Systems Engineering Framework represents a new approach for the design and optimization of innovative steady state and dynamic processes by integrating an extensible, equation-oriented process model library with the Pyomo algebraic modeling language. Built specifically to enable rigorous large-scale mathematical optimization, the framework includes capabilities for conceptual design, steady state and dynamic optimization, multi-scale modeling, uncertainty quantification, and the automated development of thermodynamic, physical property, and kinetic submodels from experimental data. IDAES provides:

  • Flexible design approaches, which enable optimization over broad ranges of potential plant operation
  • New approaches for utilizing process intensification concepts to enable the identification and scale up of step change technologies that are smaller, more modular and more cost effective
  • Support for development, scale up, and deployment of new energy technologies
  • A modular framework and model library that supports large-scale optimization of advanced energy systems
  • Machine learning-based parameter estimation tools