A predictive approximation based on squeeze functional in solving nonlinear simulation problem

Abstract

The performance requirement for nonlinear simulation of an industrial process is especially important when used in an operator training simulator (OTS), which is usually integrated with an emulator of a distributed control system (DCS). While coupled with such a DCS system, the simulator must be able to respond faster than real-time to process variations and upsets. Without such performance requirement, model fidelity will suffer and the simulator may fail to predict dangerous process conditions or warnings. In this paper, we address the performance issue by introducing a predictive approximation of physical properties based on the concept of a squeeze functional. Proof of accuracy and computational performance enhancement are given by examples, including simulation of a polyethylene synthesis process using the PC-SAFT model and an olefin metathesis process using NRTL model.