(370a) The Benefits of Polymerization Modeling: A History of Dupont Applications

DuPont has a long established culture of modeling and as a result has greatly benefitted from detailed fundamental models of polymerization processes.  Dr. John Congalidis, along with Dr. John Richards, were instrumental in establishing this culture in the mid-1980s. Today, the ground breaking work they did with their custom polymerization models is available to all DuPont engineers in DuPont’s dynamic simulator.

This talk will provide an overview and specific examples of how DuPont teams have used polymerization modeling to show real, tangible benefits. Much of the modeling has been focused on complex, multiphase emulsion polymerization, with a wide range of applications – from in depth, single-unit modeling for improved understanding, to large, plant wide models for operator training and control system checkout. Specifically, the applications that will be discussed are:

1. A detailed model of high pressure free radical polymerization was initially used to understand how phase partitioning, polymerization kinetics and non-ideal mixing contributed to reactor fouling.  Insights gained by modeling lead to changes that reduced fouling, lengthened the time in between cleanings and improved productivity.
2. A model of two continuous emulsion polymerization reactors was commissioned to support a process hazards analysis aimed at understanding the risk of forming a monomer vapor phase in the reactor when pressure decreased. The results of the modeling were used to assess if existing safety procedures were adequate. Several years later, this model was expanded and used in support of an emission reduction program.
3. A fundamental kinetic model of a high-value batch emulsion polymerization reactor was developed and validated in a Matlab(R) model then leveraged to DuPont’s in-house dynamic simulator in order to run the model real time, in parallel with batches. The model predicts batch quality, days before the results are available from the lab. Operators and engineers use the model output to pro-actively identify batches that should be segregated pending lab results, and if recipe changes for the next batch charge are required.

Each of these applications has demonstrated tangible benefits for DuPont, and re-enforced the value fundamental modeling can bring.