State and Parameter Estimation of Non-Ideal Batch Reactors with Heel Masses

In chemical batch reactors, proper mixing is important for consistent process and product quality. Heel masses (mass that is left behind from batch to batch) can be a feature of process design, or may occur inadvertently. The current practice at the Hanford nuclear waste processing site is to include heel masses (up to 30% by volume) to reduce batch to batch variation of chemical waste that will be vitrified. To monitor this process, the proposed process uses laboratory measurements with a mass balance to propagate composition estimates from tank to tank. Incorporating in-line monitoring tools can improve the ability to detect faults when they occur in processing, particularly faults concerning tank transfer and heel masses. A simulation study is performed based on reported data on expected tank concentrations, sensor accuracies, and analytical laboratory accuracies. Observability of model states and parameters are shown. By incorporating in-line sensors, the mean absolute prediction error for the heel mass of kyanite, an insoluble solid, is improved by a factor of 3.88 over mass-balance model approaches in a simulation study including a fault in heel mass.