**DYNAMIC VISUALISATION OF THE COMBUSTION PROCESSES IN**

**BOILERS**

**Marek Gayer**

**1**

**, František Hrdlička**

**2**

** and Pavel Slavík**

**3**

Department of Computer Science and Engineering

Czech Technical University, Karlovo náměstí 13

121 35 Prague 2

Czech Republic

xgayer@fel.cvut.cz, slavik@cslab.felk.cvut.cz

http://www.cgg.cvut.cz/~xgayer/

**ABSTRACT**

This paper focuses on the simulation and visualisation of coal combustion in the pulverised coal boilers. It

is important to find optimal boiler configurations (both for the ecological and economical reasons),

determine appropriate combustibles, optimize process of combustion, etc. These tasks are typically solved

using traditional Computational Fluid Dynamics (CFD) methods that are in general computationally very

expensive. Our work is based on a different approach. We use simplified methods for determining

direction and speed of air stream in particular places in the boiler. Further we use simplified methods for

the simulation of combustion processes and heat transfer as well. A particle system is used to simulate

and visualise the behaviour of the coal particles and air streams in voxelized boiler space. We developed

concept of virtual particles – they represent certain amount of coal, air, ash and other materials in a voxel

under investigation.

**Keywords:** FLUENT, visualisation, fluid, CFD, combustion, pulverized coal

1

Department of Computer Science and Engineering

2

Faculty of Mechanical Engineering, Department of Thermal and Nuclear Power Plants

3

Department of Computer Science and Engineering

**1.**

** **

**INTRODUCTION**

This paper describes our current work of

visualisation of combustion processes in pulverized

coal boilers [Hrdl96]. The goal is to improve design

of the boilers - to reduce pollution, find ways of

preparing fuel, determine particle sizes and quantity,

speed etc. In engineering practice, it is very difficult

to investigate the combustion processes of various

kinds of combustibles directly in the boiler. Rather

than constructing real boilers and trying to check

and improve these characteristics „on the fly“,

computers are used to experiment with models of the

boiler.

Therefore the efficient boiler design is

based on simulation models. The models that

simulate combustion processes are of various types.

One type of models deals with simulation and

visualisation of behaviour of flames. These models

use several approaches like cellular automata

[Takai95] or diffusion processes [Stam95]. Models

of this type are more concentrated on the

visualisation part of the combustion process. The

resulting pictures can be used in applications where

the quality of visual effect plays decisive role (e.g.

movies etc.). In our case we investigated the

approach that simulates and visualises the

combustion process from the point of parameters of

the combustion process. These parameters can be:

temperature achieved in various parts of the boiler,

speed of air and gases in the boiler during the

combustion process and similar aspects that would

help the boiler designer during the boiler design.

Some well-known algorithms and

technologies for solving this problem based on CFD

[Anderson95] have been already developed. CFD is

a sophisticated analysis technique. It not only

predicts fluid flow behaviour, but also heat transfers,

mass, phase change (such as in freezing or boiling),

chemical reaction (such as combustion), mechanical

movement (such as an impeller turning), and stress

or deformation of related solid structures (such as a

mast bending in the wind). Using current CFD

methods, we are able to solve only some specific

cases with simplified boundary conditions.

Nevertheless they sufficiently cover our needs.

Slice of the temperature array in a boiler

Figure 1

**2.**

** **

**FLUENT**

FLUENT is the most known and respected universal

CFD application for modelling fluid flow and heat

transfer in complex geometries. Currently, FLUENT

is one of the most used professional systems for

CFD.

Geometry modelling in FLUENT is based

on constructing a mesh for object (e.g. boiler).

Supported are 2D and 3D meshes. The second step

(after defining a correct mesh) is to define boundary

conditions – walls, inlets, outlets, and physical

properties and models of used materials and

environments. The FLUENT offers excellent ways

of visualisation of computed results. Various

conditions such as temperature arrays, mass tracks

and heat flux could be displayed (see Fig. 1. and Fig.

2.). Using a special pre-processor – PREPDF – the

system can be applied for solving coal combustion

computation tasks.

We use FLUENT results as reference ones

to verify our results.

Sample visualisation of the vectors of the air stream speed in a boiler

Figure 2

**3.**

** **

**OUR WORK**

Current CFD effort is based on solving complex

differential equations (such as the Navier-Stokes

equations). Computation time needed for solving

non-trivial tasks is counted in hours and days, even

on a very powerful system.

In no way, current CFD methods can be

used for dynamic real-time computations and

visualisation with ability to change boundary

conditions online. These real-time simulations are

often needed to determine dynamic characteristics of

the boiler for the transition to the stable state,

synoptically display the flow of fuel and air etc.

The aim of our research is to develop a

much faster system (though less accurate), based on

a completely different approach, than the

computation of the differential equations. It should

even allow dynamic visualisation of the combustion

process in the real-time.

**4.**

** **

**PRINCIPLES**

The main principles, by means of which our

methodology enables dynamic visualisation, could

be summarised as follows:

**Particle system** – is a common method for

visualisation of fuzzy objects (e.g. clouds, water, and

fire) in computer graphics. It is also used for

industrial technology [Rhodes98]. In our case, the

application of particle system represents a real

technological problem. The simulation and

visualisation using particle system is divided into

separated steps. For simplicity and maximum

computation speed, this part and all the other parts

of our system are implemented only in the 2D space.

**Pre-calculated vectors of motion** - (**flow**

**array)** – (See Fig. 3 and Fig. 4) dramatically

increases visualisation and computation speed. The

particles are moved only on the pre-calculated

trajectories. These trajectories are computed only

once at the beginning of simulation. They are

represented as a floating-point data structure – called

Flow array. The size of the flow array in our case is

typically calculated and visualised 32 x 32 elements.

This array divides the area of the boiler into mesh of

squares (voxels in 3D interpretation see Fig. 4).

**5.**

** **

**INPUT**

Our system does not depend on some specific tasks

and boiler configurations. We use small flat text files

to describe geometry representation of the boiler and

to configure air and coal jets. This allows us to solve

boilers of different shape. It allows us to develop

some visual editor. It could be useful for

constructing and editing tasks without need of

changing current source codes of our system later

on.

Visualisation of Flow array in the test boiler

Figure 3

Velocity and direction of the vectors of velocity in

the Flow array

Figure 4

**6.**

** **

**FLOW ARRAY GENERATION**

There are many ways to obtain flow array. The

classical way is based on the differential equations.

Since we try to reach the maximum simulation

speed, we do not use this approach.

Instead of that, we use isotherm, loose flow

that runs from a circle jet. The air stream flows

through jets to the boiler. The solution of the streams

in a limited area in the boiler is quite complex,

especially for the non-isothermal flow. That is why

we calculate it as an isothermal free stream that

flows from the circle jet. Our solution is based on

the G.N.Abramovič’s idea that can be found in the

[Cihe69].

The air stream forces to move surrounding

air under the influence of the turbulence. This

approach allows us to speed up considerably the

calculation of flow array. The stream can be

considered as a cone. The top angle 2α depends on

the level of the turbulence of the stream in the jet,

see Fig 5.

* x *

* y v*

*xy*

*v*

*x*

y

tryska

*a*=0,07

'

50

26

2

°

=

α

x

Isotherm free stream flowing from the jet

Figure 5

For any distance x from the input of the

stream, the maximal speed in the x-axis and y-axis is

decreasing to zero with the Gauss distribution (see

Fig. 6) described as (Eq. 1):

2

2

2

)

(

2

1

)

(

σ

µ

π

σ

−

−

⋅

=

*y*

*e*

*y*

*f*

(1)

*x*

*f(y)*

µ

Graph of the Gauss distribution

Figure 6

The x-axis speed gradually decreases (see Fig. 7)

and is determinate by the Eq. 2. See Fig. 8 for an

illustration of all the above given approach.

145

,

0

48

,

0

0

0

+

⋅

=

*d*

*x*

*a*

*v*

*v*

*x*

** **(2)

0,335

6

3

0,5

0

1

0

*v*

*v*

*x*

0

*d*

*x*

*a*

⋅

Curve of the axial speed *v*

*x*

Figure 7

Distribution of the speed of the air stream in the

space, see [Faltyn99]

Figure 8

However, there may appear a situation,

when a stream collides with the wall and/or there

may occur a collision with another air stream. In

such a case, other virtual jets are added to handle

this situation and to match the real situation. Detail

description of this situation exceeds the scope of this

paper.

**7.**

** **

**THE PARTICLE SYSTEM AND VIRTUAL**

PARTICLES

For our work, the particle system allows us

computation and visualisation of mass elements in

the boiler. The particles displayed and calculated do

not correspond to the real coal particles in the boiler.

Instead of that, they represent some corresponding

mass of coal in the voxel under investigation.

Various particle types represent proper amounts of

air, gas, ash and other materials in the boiler space.

Therefore, we call them virtual particles. Thus, one

virtual coal particle carries many real coal particles.

The quality and speed of simulation and

visualisation could be altered by increasing or

decreasing the amount of these virtual particles.

The movement of the virtual particles is

strongly determined by the flow array. For each

particle, the new x and y position, according to air

speed current in the current voxel is computed. The

magnitude of the speed is time dependent.

There are some factors that could change

their motion. For coal particles, we cannot omit the

force of gravity. The coal particles are attracted to

the bottom of the boiler. The acceleration is

determined by the weight of the particle and by the

surrounding environment. Before moving a particle

to the predicted destination, we must check for

possible collisions with the wall. For each voxel, we

have list of walls the voxel interferes with it. We

first determine, in which voxel the particle is

located, and according to that we check for possible

collisions. If this is the case, the particle track is

mirrored and bounced from the wall (See Fig. 9).

Particles are generated from the jets (usually

installed in the walls of the boiler).

β

β

wall x

Particle before bounce

Particle after bounce

C[x

t

,y

t

]

C[x

t+1

,y

t+1

]

C[x

’

t+1

,y

’

t+1

]

A particle bouncing from the wall

Figure 9

Currently, we are using a simplified model

of particle system, because we ignore collisions

between each single particle, from which the final

motion is calculated. Sample visualisation of our

particle system can be found in Fig. 10

**8.**

** **

**COMBUSTION AND HEAT TRANSFER**

Combustion process of the coal particles is in fact a

quite complex problem [Dibble96]. Again we use

some simplifications due to the need for the fast

computation. In each step we compute a temperature

array. It contains weighted average of the particle

temperatures for all the voxels. To start combusting

coal, two conditions must be satisfied: in the voxel

there must be at least some minimal combustion

temperature (which is defined - in our example we

use 300 K), and a proper mass of coal and air

(represented by virtual particles) that is to be burned.

Particles flowing from a jet

Figure 10

Depending on the current temperature,

weight and proportion of the coal, the coal particles

are being burned. For air particles, we just decrease

their appropriate mass. If the mass of the air particle

reaches some minimal value, we remove this particle

from the system. For coal particles, we decrease the

amount of the combustible part of the particle, and

increase the amount of the gas burnt. If the mass of

the combustible part reaches some minimal value,

we assume that the coal particle is burned out and

we change it to the burnt gas particle. This process is

shown in the Fig. 11 and Fig. 12.

The situation in a voxel before the combustion

process start

Figure 11

**T = 303K**

(above ignition temperature)

t = 0 seconds

Coal particle

Air particle

Partially burned coal particle

A

**C**

**C**

**C**

A

A

A

The situation in a voxel after the end of the

combustion process

Figure 12

Between these processes, depending on

reaction heat transfer, the released heat is transferred

to all the particles, which are present in the current

voxel. Therefore, the temperature of the voxel

increases.

Because of the dynamic processes in the

boiler, the heat is distributed by the moving particles

to the other voxels, thus increasing the temperature

and making possible to start another combustion

reactions. We also count with the heat radiation

between the walls and the mass in the voxels. The

heat transferred from the given surface *F* during the

time *dt *is comparable to differences of the

temperatures of the wall and the voxel (power of

four) [Dibble96]. We also need to determine the

coefficient of the radiation *C*

*12*

*. *These ideas are

summarized in Eq. 3.

*dt*

*T*

*T*

*C*

*F*

*Q*

⋅

−

⋅

⋅

=

4

2

4

1

2

.

1

100

100

(3)

We assume, for the sake of the simplicity, that the

temperature of the walls is constant (typically bellow

the minimal combustion temperature). In general, it

is possible to say that our model is based on mutual

reactions of virtual particles of various types in each

voxel in the boiler space.

**9.**

** **

**INITIAL CONDITIONS AND**

INITIALIZATION

To start combustion again, there must be already

some appropriate condition in the boiler. It is

necessary, because air and coal, which is coming

through the jets, are not usually heated enough.

Their temperature is under the ignition point. Thus,

there must be a way to start combustion. We assume

in the current implementation, that there are already

some air particles warmed up above the ignition

point, which allows the ignition.

**10.**

** **

**IMPLEMENTATION**

All the parts of our system have been implemented

in the standard, ANSI C language. Visualisation is

based on the OpenGL graphics interface.

Windowing interface is maintained by the GLUT

library [Mason 98]. Thanks to this, our system is

easily and fully portable to other systems. No

problems should occur porting to Linux systems or

even SGI workstations, although it was originally

developed on the Windows NT/2000 platform. We

have tested our system modelling a boiler with real

dimensions, characteristics and parameters. The

behaviour and results gained from our system were

well comparable with a situation in a real boiler.

Thus, the current implementation is correct,

although, there are still many things to improve.

**11.**

** **

**VISUALISATION**

To maintain the reliable and fast visualisation, our

system uses industry standard OpenGL platform.

Thanks to this, nowadays, our system could be used

on a standard, even a cheap graphics accelerator.

There is no big lack of speed in particle visualisation

even when using 10 000 of particles. Furthermore,

our system uses MGL graphics library on the

backend to maintain easier visualisations of common

OpenGL primitives [Gayer00]. That it is an

OpenGL based library optimised for visualisation of

common 2D graphics and graphical user interface

(supports images and fonts directly). We use it to

easy implement an easy user interface, in common

2D coordinates. Therefore, such tasks are much

easier to program than in a native OpenGL.

The boiler walls and outlets are

approximated by the straight lines. The particles are

displayed using standard OpenGL pixels. For the

examples of our current graphics output, see Fig. 3,

4 and 10. The selected local characteristics in the

voxel, such as the total temperature, mass storage,

the wattage, and heat flux state and/or changes can

be in the real-time visualised (see Fig. 13). The

particle tracks can be easily determined by the fast

particle system animation. Currently, the

characteristics in a voxel are simply visualised by

the quads. Although the quality of the visualisation

could be improved by choosing smaller voxel sizes,

we plan to implement contours to bring smoother

graphics output.

**12.**

** **

**RESULTS**

The current research brings promising results. On a

test boiler (dimensions 6m x 13.7m) we have

simulated and visualised combustion processes. We

have discussed the obtained results with the experts

from the Faculty of Mechanical Engineering of CTU

**T = 305K**

(increased)

t = 0.01 seconds

Coal particle (partially burned)

Air particle (decreased m)

Coal particle transformed to

burned gas particle

A

**C**

**B**

**C**

A

A

with positive response. To compare our results with

current CFD methodology, we used the FLUENT

solver.

Sample visualisation of the total voxel temperature

in the test boiler

Figure 13

The global parameters, which could be

easily compared, match well overall design and

implementation of our ideas, see Table 1.

**Parameter**

**Our system**

**FLUENT**

Average

temperature

1029

o

C

1158

o

C

Outlet temperature

1151

o

C

1384

o

C

Maximum

temperature

2360

o

C

2753

o

C

Average stream

velocity

23 m/s

17 m/s

Average outlet

velocity

28 m/s

21 m/s

Wattage

192 w/m

3

232 w/m

3

Mass total

21.1 kg

21.3 kg

Time needed to

converge solution

**12 seconds**

**7 hours**

Global parameters results in the test boiler

Table 1

Next we compared the images of the temperature

and velocity maps, which summarize local

characteristics. We found they are visually similar.

**13.**

** **

**CURRENT IMPLEMENTATION SPEED**

The current implementation is very fast. We tested it

on different systems. We measured the number of

the frames (images) which our system was able to

compute and display per second (FPS). On each

system we generated 10.000 particles, and we

measured the FPS value, see table 2.

**System**

**Frames**

per sec.

Celeron 300, no hardware OpenGL

accelerator, 64 MB RAM

2

Celeron 400, S3 Savage 4, 128

MB RAM

26

AMD Athlon 1333, nVidia

Geforce 2 MX 400, 256 MB RAM

64

Simulation speed on different systems

Table 2

On an average system (Intel Celeron 400,

128 MB RAM we can reach 26 frames per second

with 5000 particles computed and visualised. Note

that on the Celeron 300 system the speed of the

simulation rapidly decreased due to lack of the

OpenGL accelerator. However, it should not be a

problem, because almost every new computer

system is equipped at least with a cheap graphics

accelerator (such as Savage 4), which is sufficient

for our system.

**14.**

** **

**ADVANTAGES AND DISADVANTAGES**

As it is obvious from the previous text, the

main advantage is the speed of computation. The

speed is far beyond of reach offered by the

traditional methods. Thus, the developers of the

boilers could test many configurations and

modifications of the boiler with the immediate

response. This results in the possibility to get a very

good preview of the dynamics of combustion

processes in a boiler. This is not available in the

traditional approaches. Thus, our system could also

be used for experimentations and educational

purposes in the field of the combustion processes.

Although it gives fast and reliable results,

there still would be necessary to test and compare

more deeply the gained results with results gained

from CFD systems. So again, the main advantage

against less accuracy and features offered by the

CFD systems is the speed of computation. The next

advantage is the possibility to visualise the state of

the particles during the combustion process.

**15.**

** **

**FUTURE WORK**

The future work will be concentrated on:

•

We plan to implement more accurate heat

distribution.

•

We will develop a methodology for

verification of our results with the CFD

computations.

•

We plan to simulate and monitor additional

characteristics (pressure, turbulence, etc.)

•

Much interest we will probably give to the

computation of the Flow array. While this

is computed only once, with no influence to

the speed of the other computation, there

could be used some more complex

algorithms to compute. We plan to include

influence of the mode of combustion also.

•

Some advantages could be gained through

the visualisation itself. We plan to use

linear approximations to convert attributes

from the singular points to the continual

array. It would be useful for visualisation of

the temperature map.

**16.**

** **

**CONCLUSION**

For combustion system visualisation, current

investigation brings an interesting alternative to the

classical CFD applications. We implement a brand

new way based on the fast computation of the flow

arrays. We use simplified model of combustion

process and light-speed visualisation using OpenGL

graphics interface. Current implementation is very

fast even on average systems. The behaviour and

results gained from our system were comparable

with a situation in the real boiler and FLUENT CFD

system. Therefore, our system can be used for

dynamic simulation or preview of dynamic

processes of coal combustion in boilers. This may be

used in the CFD process for the fast and efficient

design for the boilers. The system could also be used

for education purposes in order to give students idea

about the behaviour of boilers under various

conditions.

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[Anderson95]

Anderson, J.: *Computational Fluid*

*Dynamics – The basics with the applications,*

McGraw Hill, 1995.

[Dibble96] Dibble, W., Maas U.: *Combustion*,

*Springer*, 1996.

[Cihe69]

Cihelka, J*.: Vytápění a větrání. SNTL,*

*Praha*, 1969.

[Faltyn99] Faltýn, R.: *Diploma work / Diplomová*

*práce,* *ČVUT FEL Praha*, 1999.

[Gayer00] Gayer, M.: *Graphical library MGL,*

*part of the diploma thesis Programové*

knihovny pro grafické akcelerátory (in

Czech),

*ČVUT FEL Praha*, 2000.

*http://sgi.felk.cvut.cz/~xgayer/mgl/*

[Hrdl96] Hrdlička,F., Janeba,B.: Fluid

combustion, *Energie* (Vol 1, pp. 50), 1996.

[Mason98] Mason, W.: OpenGL Architectural

Review Board, Jackie, N., Davis, T., Shreiner,

D.: *The OpenGL Programming Guide.*

Addison-Wesley, 1998.

[Rhodes98] Rhodes, M.: *Introduction to particle*

*technology, John Wiley & Sons Ltd.*, 1998.

[Stam95] Stam J., Fiume, L.: Depicting Fire and

Other Gaseous Phenomena Using Diffusion

Processes, *Proceedings of SIGGRAPH 95,*

Computer Graphics Proceedings, Annual

Conference Series, pp. 129-136, 1995.

[Takai95] Takai, Y., Ecchu, K. Takai, N.: A cellular

automaton model of particle motions and its

applications, *The Visual Computer, 11(5), pp.*

240-252, 1995*.*