Modules

Prerequisites

Contents

1. Modeling strategy: relevant scales, inputs / outputs, assumptions 2. Balancing: partial mass balances, total mass balances, momentum balance, energy balances. Substantive and local formulations 3. Entropy Balance: Source terms, drivers and rivers 4. Balancing of multiphase systems 5. Constitutive equations: Overview of kinetics (reaction, mass and heat transport, impulse transport), thermodynamic equations of state. Stefan Maxwell kinetics of mass transport. 6. Boundary and initial conditions: species, bad and well-posed problems 7. finite volume method 8. method of characteristics 9. Model reduction: quasi stationarity, balance, integration 10. Differential Algebra Systems: Differential Index, Index Reduction, Solution Methods

Learning outcomes

The students are able to describe dynamic and locally distributed systems of process engineering with the help of mathematical models. For this purpose, you can make suitable assumptions and neglects for the derivation of a model from the context of a task, then compile them on the basis of material, momentum, energy and property balances and complete them with kinetic approaches, thermodynamic equations of state and suitable boundary and initial conditions , In addition, students are able to apply systematic methods for model reduction, in particular for the reduction of spatial coordinates, for the introduction of quasi-stationarity assumptions and equilibrium assumptions. The students can use the finite-volume method to transform spatially distributed process models into systems of ordinary differential equations, to implement and solve them in a numerical simulation environment.

Assessment

Examination 120 min