Process modeling and simulation
- Introduction: the importance of modeling in analysis and optimization of processes; course outline; evaluation breakdown.
- Steady-state and dynamic modeling with common industrial examples; general modeling approaches: steady state, ordinary differential equations, partial differential equations, differential-algebraic equations.
- Differential-algebraic equation (DAE) systems (2): the importance of these systems in modeling chemical processes; basic definitions such as index; challenges of solving DAEs.
- Differential-algebraic equation (DAE) systems (2): index reduction methods
- Differential-algebraic equation (DAE) systems (3): DAE initialization issues with process examples; consistent DAE initialization methods.
- Overview of DAE solution methods and parametric sensitivity analysis.
- Hybrid discrete-continuous dynamic systems: process examples, discrete events, simulation challenges
- Simulation of hybrid dynamic models: operational modes, event detection and mode switching, model re-initialization
- Modeling of mode switching using optimization: optimization techniques for simulation of phase equilibrium systems
- Modeling of mode switching using non-smooth functions (1): basic concepts and definitions related to non-smooth functions and their application to the modeling of process discontinuities
- Modeling of mode switching using non-smooth functions (2): non-smooth function methods for simulation of phase equilibrium systems
- Steady-state process simulation (1): sequential-modular methods; convergence of recycle streams and calculation blocks
- Steady-state process simulation (2): Simultaneous methods; pros and cons of the sequential and simultaneous methods.
- Dynamic process simulation (1): simultaneous and hybrid methods
- Dynamic process simulation (2): simultaneous methods; improved convergence using permutation and block solution