problems of visualization of technological processes

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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 www.cgg.cvut.cz Problems of Visualization of Technological Processes

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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. - PowerPoint PPT Presentation

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Page 1: Problems of Visualization of Technological Processes

Pavel Slavík , Marek Gayer, Frantisek Hrdlicka, Ondrej Kubelka

Czech Technical University in PragueCzech Republic

2003 Winter Simulation Conference December 7-10

Fairmont Hotel New Orleans Louisiana, USA

www.cgg.cvut.cz

Problems of Visualization of

Technological Processes

Problems of Visualization of

Technological Processes

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Outline of the presentationOutline 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

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The need for visualization of dynamic processesThe 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

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Our approachOur 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

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Two applicationsTwo 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)

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Active coal filter: Integral - function scheme

new active coal

saturated active coal

clean gas

dirty

flue gas

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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

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Simulation and visualization of filter behaviorSimulation 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

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Verification of the model

Real test Simulation of granule flow

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Simulation of more complex configurations

Angle of inner louversAngle of inner louvers10°10° 20°20° 30°30°

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Our approach to dynamic visualizationOur 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

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Visualization of granules flow !@!!Visualization of granules flow !@!!

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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

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Physical device for real testsPhysical device for real tests

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www.cgg.cvut.czIntroduction and motivation to coal combustion modeling and visualization

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

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Traditional Fluid Simulators and SolversTraditional Fluid Simulators and Solvers

For simulation and visualization of various nature phenomena:– Water and liquids– Clouds, smoke– Fire and

combustion– Special effects

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Real-time modeling of fluidsReal-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

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Our system overviewOur 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

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Our Fluid SimulatorOur Fluid Simulator

Dividing boiler area to structured grid cell arrays containing:– Velocities– Masses/Pressures

– O2 concentrations

– Temperatures State update Principle of local

simulation

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Virtual coal particle systemVirtual coal particle system Used for both simulation

and visualization of the combustion process

Virtual particle system approach

Simplified combustion and heat transfer computation

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t = 0 seconds:

T = 343oC (above ignition)O2 concentration = 25%

Coal particle

Partially burned particle

C

C

C

t = 0.01 seconds:

T = 345oC (increased)O2 concentration = 24%

Partially burned coal particles

Coal particle transformed to burned ash particle

C

B

C

C

C

Interaction of virtual coal particlesInteraction of virtual coal particlesInteraction of virtual coal particlesInteraction of virtual coal particles

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Results comparison – global parametersResults comparison – global parameters

Parameter Our system FLUENT 5.5

Average Temperature 890 oC 1002 oC

Outlet Temperature 814 oC 1068 oC

Max Temperature 2546 oC 2488 oC

Average stream velocity 14 m/s 11 m/s

Average outlet velocity 56 m/s 48 m/s

Wattage 187 W/m3 232 W/m3

Mass total 21.1 kg 21.3 kg

Solution converge time Below 1 min In hours

Real-time simulation / visualization

Enabled, 10 FPS+

Not available

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Sample visualization - cell characteristicsSample visualization - cell characteristics

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Sample visualization – coal particlesSample visualization – coal particles

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Sample visualization of particle characteristics (particle tracks)Sample visualization of particle characteristics (particle tracks)

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Our interactive combustion systemOur interactive combustion system

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Storing results for real-time replayingStoring 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)

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Extending Fluid Simulator with FSSExtending 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

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Simulation system architectureSimulation system architecture

VisualizationVisualization

InteractionInteraction

Store FullData Sets

Store FullData Sets

Fluid simulatorFluid simulator

Combustion &heat transfer

engine

Combustion &heat transfer

engineParticlesystem

ParticlesystemGrid cellsGrid cells

Store FSSextension

Store FSSextension

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Feature comparison against data setsFeature comparison against data sets

Much less disk requirements (only fluid simulator states are being saved)

Lower disk bandwidthBetter scalability for large grids and/or tasks

with many particlesSame or even better acceleration resulting in

better interactivityNo seeking and skip frame ability

+

++

-

+

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Conclusion and future researchConclusion 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

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Forming FSS to tree cluster structureForming FSS to tree cluster structure

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www.cgg.cvut.czChanging simulation parameters in each of the tree node

Changing simulation parameters in each of the tree node

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Thank you for your attention.Thank you for your attention.

???Do you have any questions ?