Intelligent Combustion

The project of Intelligent Combustion is to develop algorithms based on deep learning for combustion study. Currently, we have two specific tasks.

DeePMR

DeePMR: DeeP Model Reduction, develop DNN-based algorithms for reducing chemical reaction mechanisms.

DeePCK

DeePCK: DeeP chemical kinetics, develop DNN-based surrogate model to accelerate the simulation of chemical kinetics.

This open project will release various models based on our algorithms.

About the team

Advisors (alphabetical order)

• Zhi-Qin John Xu, associate professor, Institute of Natural Sciences/School of Mathematical Sciences, Shanghai Jiao Tong University. Homepage: https://ins.sjtu.edu.cn/people/xuzhiqin and Email: [email protected]

• Tianhan Zhang, associate professor. Homepage: https://faculty.sustech.edu.cn/zhangth and Email: [email protected]

Collaborators (alphabetical order)

• Yaoyu Zhang, associate Professor, Institute of Natural Sciences/School of Mathematical Sciences, Shanghai Jiao Tong University. Homepage: https://ins.sjtu.edu.cn/peoples/zhangyaoyu

Team Members (alphabetical order)

• Liangkai Hang (Shanghai Jiao Tong University)

• Pengxiao Lin (Shanghai Jiao Tong University)

• Chenyang Ren (Shanghai Jiao Tong University)

• Zhiwei Wang (Shanghai Jiao Tong University)

• Tinghao Wang (Peking University)

• Junjie Yao (Shanghai Jiao Tong University)

• Yuxiao Yi (Shanghai Jiao Tong University)

• Xumeng Zhang (Shanghai Jiao Tong University)

• Enhan Zhao (Peking University)