Computational Model to Predict Nitrogen Oxides
Nitrogen oxides (NOx) are a major pollutant caused by combustion. To understand the NOx output of a combustion system, researchers can use computer simulations. Unfortunately, the size of chemical reaction mechanisms involved in combustion simulations has increased so much in recent years that these simulations are extremely computationally costly.
Hongyuan Zhang, a 2020 UMII MnDRIVE PhD Graduate Assistant, worked on a project called “Optimization of Combustion Parameters for the Reduction of Soot/NOx Emission Based on Regularized Multi-task Neural Nets.” In this project, Mr. Zhang developed a machine-learning method to reduce the size of the chemistry kinetics based on the Chemical Reaction Neural Network (CRNN). The CRNN is built based on the Arrhenius law, so the new neural nets are interpretable. Hence, the CRNN can be used to explore the new reaction mechanisms. The final model can accurately predict NOx formation and includes only half of the number of chemical reaction equations.
Mr. Zhang is a member of the research group of MSI PI Suo Yang (assistant professor, Mechanical Engineering) and used MSI resources for this project. He has received two prestigious awards for his research:
The AIAA Martin Summerfield Graduate Award is the most prestigious award for any graduate student in the field of propellants and combustion. Only one student is selected for this award annually. An article appears on the mechanical engineering website: ME Graduate Student Wins AIAA Award.
2021-22 Frontera Computational Science Fellowship, which allowed him to work with the Texas Advanced Computing Center (TACC) at the University of Texas at Austin. He is profiled in articles on the mechanical engineering department’s website and the TACC website.
The UMII MnDRIVE Graduate Assistantship Program was renamed the Research Computing-MnDRIVE Graduate Assistantship Program in January 2023. It supports U of M PhD candidates pursuing research at the intersection of informatics and any of the five MnDRIVE areas:
- Robotics
- Global Food
- Environment
- Conditions
- Cancer Clinical Trials
This project is part of the Environment MnDRIVE area.
Professor Yang’s research at MSI includes several projects on first-principles-based modeling and simulation of reacting flows, including combustion, turbulence, soot aerosols, and plasma physics, and their multiscale interactions.
Image description: The structure of the neural net used in this study. Left: The structure of one reaction. Right: The structure of the whole neural net system.