(58e) A Deep-Knowledge Based Evolutionary Operation Approach for Distillation Process Optimization

This paper will present a deep-knowledge based evolutionary operation approach for separation process optimization, which involves uncertainties in predicting gas-liquid contacting hydraulics and mass transfer efficiency. A case study has been use to illustrate the usefulness of this experimantal method supplemented with gamma scanning and tracer techniques in solving a complex process operating problem involving an absorption column.