Surrogate modeling

• ALAMOPY: ALAMO Python
• RIPE: Reaction Identification and Parameter Estimation
• HELMET: HELMholtz Energy Thermodynamics
• PySMO: Python-based Surrogate Modelling Objects
• Visualizing Surrogate Model Results

ALAMOpy, RIPE, and HELMET are data driven machine learning (ddm-learning) tools. They are regression tools for the development of property models for kinetics and thermodynamics of a system. The provided tools include both ALAMOpy and RIPE that can access ALAMO and other solvers through the Python API.

Python-based Surrogate Modeling Objects (PySMO) is a framework for general-purpose surrogate modeling techniques, integrated with the Pyomo mathematical optimization framework (on which IDAES is also based).