Methods and data for: Modeling hydrogen flames with physics-informed neural networks

Research data and scripts used to generate the results presented in Chapter 2 titled <em>Modeling hydrogen flames with physics-informed neural networks </em>of the doctoral dissertation of E.Bunschoten titled <em>Consistent data-driven equations of state for reacting and nonideal compressible fluids</em>. Instructions for the various steps are found in the README file. The data set includes the python scripts used for generating the flamelet solutions and training the neural networks, the SU2 configuration files and flow solutions, and the detailed chemistry solution data used for validation.