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Problems of Visualization of Technological Processes

www.cgg.cvut.cz. Problems of Visualization of Technological Processes. Pavel Slav ík , Marek Gayer, Frantisek Hrdlicka, Ondrej Kubelka Czech Technical University in Prague Czech Republic 2003 Winter Simulation Conference December 7-10 Fairmont Hotel New Orleans Louisiana, USA.

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Problems of Visualization of Technological Processes

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  1. www.cgg.cvut.cz Problems of Visualization of Technological Processes Pavel Slavík , Marek Gayer, Frantisek Hrdlicka, Ondrej Kubelka Czech Technical University in Prague Czech Republic 2003 Winter Simulation Conference December 7-10 Fairmont Hotel New Orleans Louisiana, USA

  2. Outline of the presentation • Need for visualization of dynamic phenomena • Example of a system for filter design • Dynamic phenomena and their visualization • Brief introduction to Fluid Simulators and Solvers • Our solution overview • Fluid simulator and coal particle system • Fluid Simulator State Extension (FSS) • Control of visualization dynamics • Conclusion and future work

  3. The need for visualization of dynamic processes • Dynamic processes and understanding to their nature (e.g. in engineering education) • Classical approach: animation • Disadvantage of this approach: no interaction during the course of the process • Solution: on-line interaction with visualization module

  4. Our approach • Development of new simulation methods that are fast enough to generate sufficient number of frames for the controlled animation • Development of new visualization methods that allow extensive control of dynamic parameters of the process visualized

  5. Two applications • Design of flue gas filter • Combustion processes • Both cases: problems of flow dynamics • Traditional solutions: time consuming • Our solution is based on fluid simulator and particle systems • Simulations run much faster (in orders)

  6. Active coal filter: Integral - function scheme new active coal clean gas dirty flue gas saturated active coal

  7. Traditional designs of filters : • Ad hoc design • Real model • Testing the real model • Modification of the real model • Testing the real model • Modification ……Very costly and the filter efficiency is often questionable

  8. Simulation and visualization of filter behavior • Two aspects have been taken into account: • Physical behavior – behavior of granule flow • Adsorption behavior – adsorption capability of granules and its effect on gas cleaning

  9. Verification of the model Real test Simulation of granule flow

  10. Simulation of more complex configurations Angle of inner louvers 10° 20° 30°

  11. Our approach to dynamic visualization • To get maximum information from the picture we can zoom its interesting parts • Visualization mantra: Overview, zoom, details-on-demand • The same approach should be used for dynamic visualization – “zoom in time” • Time segments with interesting dynamic behavior are identified and the visualization is slowed down

  12. Visualization of granules flow !@!!

  13. Future work • Model of the dynamic behavior of granules (verified) • Model of adsorption it corresponds with data acquired from filter producers Creation of proper user interface that should allow the users to dynamically influence the speed of flow of granules

  14. Physical device for real tests

  15. Introduction and motivation to coal combustion modeling and visualization • Both for the ecological and economical reasons • Finding optimal boiler configurations • To reduce pollution • Combustion optimization • To find a way for optimal fuel preparation • How can visualization help

  16. Traditional Fluid Simulators and Solvers • For simulation and visualization of various nature phenomena: • Water and liquids • Clouds, smoke • Fire and combustion • Special effects

  17. Real-time modeling of fluids • Most often: solving differential equations (e.g. Navier-Stokes) • Real-time fluid simulator and solvers limitations and conditions: • Low resolution and/or 2D grid • Simplified physical models and computations • Code optimization

  18. Our system overview • Allows dynamic, interactive overview of the combustion process • Real-time simulation and visualization (currently using 2D model simplification) • Designed on following key parts • Fluid simulator • Virtual coal particle system • Simplified combustion engine

  19. Our Fluid Simulator • Dividing boiler area to structured grid cell arrays containing: • Velocities • Masses/Pressures • O2 concentrations • Temperatures • State update • Principle of local simulation

  20. Virtual coal particle system • Used for both simulation and visualization of the combustion process • Virtual particle system approach • Simplified combustion and heat transfer computation

  21. Interaction of virtual coal particles Interaction of virtual coal particles t = 0 seconds: T= 343oC(above ignition)O2 concentration = 25% Coal particle Partially burned particle C C C C C t = 0.01 seconds: T= 345oC (increased)O2 concentration= 24% Partially burnedcoal particles Coal particle transformed to burned ash particle C C B

  22. Results comparison – global parameters

  23. Sample visualization - cell characteristics

  24. Sample visualization – coal particles

  25. Sample visualization of particle characteristics (particle tracks)

  26. Our interactive combustion system

  27. Storing results for real-time replaying • Results are stored on hard disk, then real-time replayed • Data sets for selected characteristics • AVI and MPEG files • Our concept:Pre-calculated Fluid Simulator States (FSS)

  28. Extending Fluid Simulator with FSS • Simulation is divided into two phases: • Storing phase - fluid simulator states for each time step are saved on HDD • Replaying phase- simulation runs accelerated with pre-calculated fluid simulator states • Except first frame, no other data are saved (e.g. particles) • State files are stored in binary files

  29. Simulation system architecture

  30. Feature comparison against data sets Much less disk requirements (only fluid simulator states are being saved) Lower disk bandwidth Better scalability for large grids and/or tasks with many particles Same or even better acceleration resulting in better interactivity No seeking and skip frame ability + + + + -

  31. Conclusion and future research • Concept of Pre-calculated Fluid Simulator States offers: • Acceleration of Fluid Simulator based applications • Much less disk space & bandwidth requirements compared to using corresponding data sets • Better scalability then data sets • Future research: • Compression state data using GZIP • Testing with very large data sets • Pre-calculated Fluid Simulator States Tree

  32. Forming FSS to tree cluster structure

  33. Changing simulation parameters in each of the tree node

  34. Thank you for your attention. ??? Do you have any questions ?

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