The paper presents a stochastic methodology for handling uncertainty in process development as part of a general framework for batch and continuous process models. The method combines systematic modelling procedures with Hammersley sampling based uncertainty analysis and a range of sample-based sensitivity analysis techniques which are used to quantify predicted performance uncertainty and identify key uncertainty contributions. The methodology was implemented on a batch chemical reactor process and some clear recommendations as to how to reduce the uncertainty in the main output variables are obtained.
Reliable Computing – Springer Journals
Published: Oct 25, 2006
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