The steps that are required to build comprehensive mathematical models are examined. These steps include: definition of the intended model use and user requirements; formulation of model equations; determination of model parameters from correlations and experimental data; parameter sensitivity and estimability analysis; solution of model equations using numerical techniques; model validation; and potential model applications. While the focus is on the development of fundamental models, empirical modeling techniques are also discussed. Process examples are selected from: reactive distillation, polymerization, bioreactors, heat exchangers, and fuel cells. Students complete a mathematical modeling project related to their research interests. K.B. McAuley. Not Offered 2007-2008.
The steps that are required to build comprehensive mathematical models are examined. These steps include: definition of the intended model use and user requirements; formulation of model equations; determination of model parameters from correlations and experimental data; parameter sensitivity and estimability analysis; solution of model equations using numerical techniques; model validation; and potential model applications. While the focus is on the development of fundamental models, empirical modeling techniques are also discussed. Process examples are selected from: reactive distillation, polymerization, bioreactors, heat exchangers, and fuel cells. Students complete a mathematical modeling project related to their research interests. K.B. McAuley. Not Offered 2007-2008.
