Abstract
This work demonstrates the usefulness of non-linear data reconciliation to evaluate available measurements and estimate unmeasured variables for a full-scale partial nitritation (SHARON) reactor for the treatment of wastewater with high ammonium concentrations. Despite a lack of measured data, the bilinear approach of formulating system constraints allowed to satisfy the requirements for data reconciliation and gross error detection, leading to a balanced data set and the estimation of unmeasured variables.
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