School of Chemical Engineering and Technology
Process Systems Engineering / Process Intensification / Thermocatalytic Pyrolysis Dehydrogenation / Metal Nanomaterials / Machine Learning & Intelligent Optimization Algorithms
Current position: Personal Profile > Home
Team member profile:2020级硕士研究生
Name of Research Group:Sunlight Process and Equipment Technology (SPET) Research Group
Description of Research Group:The lucky team put its interest in process intensification (PI) and process systems engineering (PSE) for higher energy efficiency, both academically and industrially, which is now strongly supported by China‘s policy on carbon neutrality and carbon reduction today. With research materials from on-site data resources and requirements, the current 3 Ph.D. candidates and 8 Postgraduates in team are contributing progresses in PI, PSE, CFD, nano syntheses & pyrolysis serving for green biofuel refinery, in form of papers and patents. As projects rapidly increase year by year in both number and complexity, the team notices the importance of machine learning & intelligent optimization and controlling algorithms and use the academic results in separations in petroleum, synthetic rubber, coal chemical, organic silicon and Nylon6/66 and other processes for bulk chemicals. Algorithms are investigated for fast distillation sequencing and optimum operating parameters, such as improved transient continuation models for complex processes, stochastic algorithms of parallel strategy based on population distribution, adaptive multi-objective differential evolution. The ongoing research uses surrogate models to replace traditional process solvers for quicker decisions. Efforts on process control include double liquid-only side stream prefractionation in place of vapor splitting in dividing wall columns for easier control; effectively controlled complex Kaibel columns for quaternary systems. These results then give rise to approaches in detailed frequency domain dependent open loop controllability in the aspect of set-point tracking and load rejection performance, as well as closed-loop validation in time domain. Other efforts on the way are intelligent optimization on coal to ethanol and ethylene glycol, isoprene from cracking C5, methylamine, diesel separation and an innovated direct vapor condensation in petroleum distillation.