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Continuous and Combined Discrete/ Continuous Models

Continuous and Combined Discrete/ Continuous Models. Chapter 11. Last revision August 19, 2006. What We’ll Do . What is a continuous system? Simple linear continuous systems Combined discrete/continuous systems Non-linear and complex systems. Continuous Systems.

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Continuous and Combined Discrete/ Continuous Models

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  1. Continuous and Combined Discrete/Continuous Models Chapter 11 Last revision August 19, 2006 Chapter 11 – Continuous & Combined Discrete/Continuous Models

  2. What We’ll Do ... • What is a continuous system? • Simple linear continuous systems • Combined discrete/continuous systems • Non-linear and complex systems Chapter 11 – Continuous & Combined Discrete/Continuous Models

  3. Continuous Systems • Discrete systems – State changes occur at isolated points in time called events • Continuous systems – State changes may occur continuously over time • Flow of fluids and fluid-like materials • Temperature changes • Chemical operations • Biological processes Chapter 11 – Continuous & Combined Discrete/Continuous Models

  4. Continuous Systems • Simple systems (linear) • Rate of change is constant between events • Future value can be calculated from starting value and rate • Can step directly to calculated event • Complex systems (non-linear) • Rate of change may depend on other continuous processes • Specialized approaches used to capture change • Approximates continuous change by making a series of small steps between the usual discrete events Chapter 11 – Continuous & Combined Discrete/Continuous Models

  5. Continuous Systems • Example of simple continuous system filling a tank smoothly over time (Model 11-1) Chapter 11 – Continuous & Combined Discrete/Continuous Models

  6. Continuous Systems • Basic constructs: Levels & Rates from Elements Panel • A Level is the value that is changing over time • A Rate determines the rate of change of the level • Both are similar to Variables in that they can be assigned a new value at any time. • Levels may also change as time advances if the value of the associated Rate is non-zero. • A Level and a Rate should be used as a pair (e.g. If you have 4 Levels you should have 4 Rates) Chapter 11 – Continuous & Combined Discrete/Continuous Models

  7. Simple Continuous Systems • Continuous Element specifies integration parameters: • Number of Dif Equations – In simple systems, leave at default of number of Rate/Level pairs. • Number of State Equations – Ignore in simple systems. • Minimum step size – The minimum time advance between integration steps. Use 0.0 in simple systems. • Maximum step size – The maximum time advance between integration steps. Use a high value (100) in simple systems. • Save Point Interval – The maximum time between save points for recording continuous statistics (CSTATS). • Method – Use Euler linear algorithm for simple systems. Chapter 11 – Continuous & Combined Discrete/Continuous Models

  8. Simple Continuous Systems • Discrete control loop to empty and refill a tank (Model 11-2a) Chapter 11 – Continuous & Combined Discrete/Continuous Models

  9. Combined Discrete/Continuous • Modify Model 11-2a to Model 11-2b to detect when Tank Level rises to 100 or falls to 0 • Detect Module from Blocks panel “watches” for and helps predict events. • Watches for value of a variable to cross a threshold value (e.g. a tank level reaching its maximum value) • Similar to Create Module in that an entity is created when crossing occurs. Chapter 11 – Continuous & Combined Discrete/Continuous Models

  10. Combined Discrete/Continuous • Fill and empty logic using Detect modules • Further examples (details in text) • Model 11-3: Coal-loading operation with above approach • Model 11-4: Coal-loading operation with Flow Process panel – special-purpose modules for such models Chapter 11 – Continuous & Combined Discrete/Continuous Models

  11. Complex Systems • Non-linear systems require special differential-equation algorithms (Runge-Kutta-Fehlberg) • Step sizes must be set carefully • Smaller step size will generate more accurate results because Arena will calculate continuous-change variables more often • Larger step size will run faster, but your error tolerances will need to be set higher • Many situations (like a gravity fed tank) are actually non-linear, but can be accurately approximated with faster, linear methods • Model 11-5: Soaking-pit furnace (details in text) • Differential equations defined in VBA Chapter 11 – Continuous & Combined Discrete/Continuous Models

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