Efficient Chemical Equilibria Calculation by Artificial Neural Networks for Ammonia Cracking and Synthesis

23 May 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The calculation of chemical equilibria in detailed reactor simulations frequently requires elaborate numerical solution of the governing equations in an iterative way, which is often computationally expensive and can significantly increase the overall computation time. In order to reduce these computational costs, we introduce a ready-to-use tool, ANNH3, for calculation of equilibrium composition for synthesis and cracking of ammonia based on a neural network. This tool provides excellent agreement with the conventional approach in the range of 135 – 1000 °C and 1 – 100 bar and is ca. 100 times faster than conventional stoichiometry-based concepts. While speed-up is significant even for the relatively simple case of ammonia synthesis and decomposition, we expect an even higher performance gain for the equilibrium calculation in reaction systems where more components and multiple reactions are involved.

Keywords

ammonia synthesis
ammonia cracking
machine learning
neural networks
chemical equilibrium
shortcut modeling tool

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