2018 Spring Meeting and 14th Global Congress on Process Safety
(164a) Simulation of Intermediate Boilers in Distillation for Piloting and Scale-up
Authors
Piloting a distillation system is fairly straight forward but when the system has intermediate impurities the design of the pilot can become complex. Understanding the column profiles for each species can help to avoid complications. The goal is to have a pilot plant that can be used to determine optimum conditions for the design of a larger commercial scale operation. When non key intermediates are present they can build up and cause âburpingâ or âdumpingâ in laymen terms. This can occur when the design of the column enables the concentration of non-key lights (in the rectification section) or concentration of non-key heavies (in the stripping section of a column). When the system has a small upset, there can be major impacts to product profiles and the column product streams. A robust design of the pilot can help to identify and correct these problems and study the most effective ways to prevent them from occurring at the commercial scale.
Simulation of the column is a critical starting point to understanding the capabilities of the pilot plant design. Paying attention to the intermediate boiling components and their composition profile can help to identify where to make special arrangements for the column design to enable measurements or in some cases retrofit of the column. Custom designed columns can be expensive and knowing where to expect problems can help minimize costly replacements and or missing the opportunity to study the potential problems before the commercial design.
Process optimization of distillation columns is important for cost of production, cost of operation, and product quality. Simulating the column is not a substitute for piloting, but it can help to identify areas which need further study during the piloting stage. A sensitivity study of the component profiles can guide the piloting design efforts and the experimental run plan in order to identify and minimize scale-up problems.