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It is shown in this article that by changing the initial operation condition of the batch processes,the dynamic performance of the system can be varied largely,especially for the initial operational temperature of the exothermic reaction.The initial operation condition is often ignored in the designing batch processes for flexibility against disturbances or parameter variations.When the initial condition is not rigid as in the case of a batch reactor, where the initial reaction temperature is quite arbitrary,optimization can also be applied to determine the“best”initial condition to use.Problems for dynamic flexibility analysis of exothermic reaction including initial temperature and process operation can be formulated as dynamic optimization problems.Formulations are derived when the initial conditions are considered or not.When the initial conditions are considered,the initial condition can be transferred into control variables in the first optimal step.The solution of the dynamic optimization is on the basis of Rugge-Kutta integration algorithm and decomposition search algorithm.This method,as illustrated and tested with two highly nonlinear process problems,enables the determination of the optimal level.The dynamic performance is improved by the proposed method in the two exothermic reaction examples.
It is shown in this article that by changing the initial operation condition of the batch processes, the dynamic performance of the system can be varied largely, especially for the initial operational temperature of the exothermic reaction. batch processes for flexibility against disturbances or parameter variations. WHEN the initial condition is not rigid as in the case of a batch reactor, where the initial reaction temperature is quite arbitrary, optimization can also be applied to determine the “best ” initial condition to use. Problems for dynamic flexibility analysis of exothermic reactions including initial temperature and process operation can be formulated as dynamic optimization problems. Formulations are derived when the initial conditions are considered or not. What are the initial conditions are considered, the initial condition can be transferred into control variables in the first optimal step.The solution of the dynamic optimization is on the basis of Rugge-Kutta integration algorithm and decomposition search algorithm. This method, as illustrated and tested with two highly nonlinear process problems, enables the determination of the optimal level. dynamic performance is improved by the proposed method in the two exothermic reaction examples.