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Using Process Modeling to Improve Lime Kiln Operations

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Content

Abstract..2

Content...3

List of figures.41 Introduction.5

2 Mathematical model .6

3 Model application

3.1 Kiln geometry and setup conditions..7

3.2 Modeling results ..9

3.3 Buoyancy effects ..13

3.4 Avoiding high refractory temperatures ..13

3.5 Flame shape .14

3.6 Burning NCG .15

3.7 Firing alternative fuels .15

4 Simulator technology ....17

5 Conclusions.21


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List of Figures

Figure 1 Heat transfer in lime kiln .6

Figure 2 Generic lime kiln ..8

Figure 3 Gas burner ...8Figure 4 Distributions of axial velocity, gas temperature, and fuel (CH4) mass

fraction .9

Figure 5 Distributions of axial velocity and velocity vector .10

Figure 6 Distributions of fuel (CH4) mass fraction and flame shape .10

Figure 7 Distribution of refractory temperature .11

Figure 8 Axial profile in the kiln ...12

Figure 9 Buoyancy effect .12

Figure 10 Effect of burner angle .13

Figure 11 Effect of reduced air split on flame length ..14

Figure 12 NCG incineration .15

Figure 13 Gas temperature when firing oil ...16

Figure 14 Gas temperature when firing petroleum coke ...16

Figure 15 Advanced simulation and training 18

Figure 16 The virtual data camera .18

Figure 17 A sample DCS panel .19

Figure 18 HTML based training .20

Figure 19 Control interface .21


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1 Introduction

The primary function of the lime kiln is to convert CaCO3 to CaO for reuse in the

causticizing process. The process involves heat and mass transfer between the

kiln, fuel, primary and secondary air, drying of lime mud, and calcining of CaCO3.

It is important to have a comprehensive understanding of these processes in

order to:

Diagnose operational problems

Improve energy consumption

Increase production

Reduce emissions

Increase refractory life

Reduce process instabilities

Improve the product quality

Optimize kiln operations

A lime kiln process model has been developed by Process Simulations Ltd.

Associated simulator technology is also under development. By modeling with

sufficient accuracy the physical processes occurring in the kiln and effectively

visualizing and analyzing the results, it is possible to diagnose operational

problems, improve kiln efficiency, extend refractory life, improve operation, and

produce a controlled flame shape. Modeling information can be used by process

engineers to evaluate what if scenarios, by operators to supplement their

knowledge of lime kiln operations, by mill managers to make informed decisionsregarding kiln retrofits, and to address environmental issues. In this report we

present a brief introduction of the lime kiln process model and illustrate an

application of the model to a lime kiln.

2 Mathematical Models


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The CFD based process model of kiln uses block-structure body-fitted

coordinates with domain segmentation to model flow, heat transfer, and

combustion. The turbulent reacting flow in the lime kiln is simulated by solving

the fully three-dimensional Reynolds-averaged transport equations of mass,

momentum energy, and chemical species. A two-equation turbulence model is

used, in which equations for the turbulent kinetic energy k and its dissipation

rate are solved.

Gas Comb ust ionModel The gas phase combustion of CH4, H2, and CO is

modeled by the Magnussen model, in which the chemical reactions are

controlled by the turbulent diffusion rate. When heavy oil is burned in the kiln, the

evaporated hydrocarbon is represented by CmHn and the combustion of CmHn isalso modeled by the Magnussen model.

RadiationHeat Trans ferModelThe ray tracing method is adopted to simulate

the radiation heat transfer. Rays are emitted in prescribed directions from points

distributed over the domain boundary. A ray is defined by its point of origin, its

direction and the band of the wavelength spectrum that it represents. An energy

equation is solved along each ray, accounting for the energy emission from the

gas and the absorption and scattering by fine particulate and by H2O and CO2 in

the gas.

Refractory Heat Transfer

Model A multi-layer refractory

wall model is developed to

account for the heat transfer

from the combustion flue gas to

the refractory, the thermal

conduction through the

refractory, and the convection

cooling of the kiln shell by the

ambient air, as shown in Figure

Radiation

Radiation

Conduction

Convection

Convection

Figure 1 Heat transfer in lime kiln


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1.

Mud Calc inat ion Model A mud calcination model has been developed in this

project to simulate the lime recovery process. The feed lime receives heat from

flue gas and flame via convection and radiation and also from rotating refractory

wall. After being dried, lime is heated and then undergoes calcination when

reaching the calcination temperature. The endothermic calcination reaction is as

following and is controlled by the heat transfer.

KkgMJCOCaOCaCO 1089@/679.123 +=

When the calcination is finished, lime reaches the discharge end and is cooled by

coming air.

Liquor and Sol id Fuel Combust ion Model Oil and petroleum coke are often

burned in lime kiln as alternative fuels. The combustion models for oil and

petroleum coke have been developed respectively. The oil combustion includes

three sub-processes, i.e. evaporation, formation and oxidation of cenosphere,

and hydrocarbon combustion. The petroleum coke undergoes drying,

devolatilization, and char combustion during its combustion process.

NOx Formation ModelA NOx formation model is also coupled into the process

model to predict NOx emission from natural gas combustion. Two types of NOx

are accounted for in the model, thermal NOx and prompt NOx.

3 Model Application

The developed lime kiln process model was applied to a generic lime kiln to

illustrate its capabilities as an advanced modeling technology.

3.1 Ki ln Geometry and Setup Con di t ions


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annulus while more air, called primary air, enters through the outer annulus.

Natural gas is injected through the center annulus. The two air jets and the gas

jet are swirling in the same direction but at different swirling angles. The kiln also

fires alternative fuels, like oil and petroleum coke. Non-Condensable Gas (NCG)

is injected through a pipe in the hood parallel to the gas gun.

3.2 Modeling Resu lts

A typical operational case of the kiln is modeled to show the process inside the

kiln and the capability of the process modeling. The kiln is fuelled by natural gas

in a rate of 2024 kg/hr. A total of 40,490 kg/hr combustion air is provided, which

works out to about 15% excess air. 80% of the total combustion air is secondary

air, and the rest goes into the kiln through the gas burner. No NCG is injected

into the kiln in this case. The process modeling results are illustrated in Figures

4 and 5 by the distributions of axial velocity, gas temperature and fuel (CH4)

mass fraction on a vertical cross section.

- 4 - 2 0 2 4 6 8 10 12 14 1 6 18 20 2 2 24 26 2 8 30 32 3 4 36 38 4 0 42 44 4 6 48 50

Axial

velocity(m/s)

0 0. 02 5 0 .05 0.0 75 0 .1 0 .1 25 0.1 5 0 .1 75 0. 2 0 .2 25 0 .2 5 0 .27 5 0.3 0. 32 5 0 .3 5 0. 37 5 0 .4 0.4 25 0. 45 0 .4 75 0 .5

CH4

massfraction

4 00 500 6 00 700 800 90 0 10 00 1100 12 00 1300 14 00 1500 1 600 170 0 1 8 00 190 0 2 0 00

Gastemp. [K]

Figure 4 Distributions of axial velocity, gas temperature and fuel(CH4) mass fraction


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Figure 5 Distributions of axial velocity and velocity vector

Figure 6 Distributions of fuel (CH4) mass fraction and flame shape


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The axial velocity contours show a reverse flow in the discharge end above the

burner and low forward velocities in the lower part of the kiln. The flame surface,

as shown in Figure 6, is defined by the contour of 0.5% CH4 mass fraction, and

the flame length is shown about 4 times the kiln diameter. The gas temperature

distribution clearly shows the flame bending upward hitting the kiln refractory at

the top. As a result, the refractory has a high temperature in the flame region, as

shown in Figure 7. This indicates the potential operational problem of the

refractory failure in that region.

Figure 7 Distribution of refractory temperature

Figure 8 shows profiles of averaged gas temperature, mud temperature, gas

species concentration, and NOx emission along the kiln axis. It is seen that lime

calcination is finished before reaching the discharge end. The NOx emission in

this case is about 64ppm.


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Z(m)

0 10 20 30 400

200

400

600

800

1000

1200

1400

1600

1800

2000

0

5

10

15

20

25

30

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0

10

20

30

40

50

60

70

80

90

100

O2, CO2(%)

NO

(ppm)

Qmud

(MW/m2)

Tgas, Tmud

(K)

BurnerPosit

ion

NO

Tgas

Tmud

O2

CO2

Qmud

Figure 8 Axial profile in the kiln

Buoyancy Forces

No Buoyancy Forces

Figure 9 Buoyancy effect


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3.3 Bu oyancy Effects

Further process modeling is done without including the effects of buoyancy in the

model. The flame shape is shown in Figure 9 using the 3D viewer simulator

technology. Results show that there is significant upward bending of the flame

when buoyancy effects are included. This reveals that cold flow modeling

(numerical or experimental) will not adequately predict the kiln processes as no

buoyancy effects would be included.

3.4 Avo iding High Refractory Temperatures

To maximize refractory life, it is essential to avoid flame impingement on the

refractory lining. Process modeling supports the practice that tilting the gas gundownward is an effective method. Figure 10 illustrates that, for the generic kiln

modeled here, tilting five degrees downward appears to avoid impingement,

however slightly less tilt may be required to avoid overheating the product. The

optimal tilt angle will be different for different kilns, and for the same kiln with

different operational conditions. Process modeling and simulator technology can

be used to fine-tune the tilt angle based on current operational conditions.

0

-5

Figure 10 Effect of burner angle


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3.5 Flame Shap e

The burner and flame play a key role in determining the kiln production capacity,

efficiency, product quality and service life of the refractory. Tilting the burner is

not the only method of adjusting the flame. For persistent, flame shape related

operational problems, different burners can be installed. Generally, however,

ratios of primary, secondary, and other combustion air are adjusted by operators

to modify the flame shape. Short, hot flames are better for kiln efficiency and

production than long, lazy flames. While heat rates are better with short flames,

refractory temperatures can be substantially higher. Using this type of flame may

shorten the refractory service time. Different burner designs can produce

different flame length. Changing the combustion air split between the primary

and the secondary also produce different flame shapes. The flame becomes

longer when the primary air is reduced by 20%, as shown in Figure 11. Process

modeling also shows that when the primary air ratio is larger than a certain value,

further increasing of primary air ratio will not shorten the flame length. The

requirement of even shorter flame can only obtained by using different design of

the burner or using an adjustable burner.

Figure 11 Effect of reduced air split on flame length


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3.6 NCG Burn ing

In many pulp and paper mills, lime kilns are used to incinerate NCG. The oxygen

and small amount of combustible gases in NCG may influence the flow and gas

combustion process in the kiln, so care must be taken to inject the NCG so as

not to affect kiln operations. NCG can be injected into the kiln through a

separate pipe or by premixing with primary air. Separate injection of NCG is

modeled here as an illustration.

No NCG

With NCG

Reduced

Heat

Figure 12 NCG incineration

The NCG injection pipe is parallel to the gas gun on its right upper side. The

predicted temperature distributions show that the NCG forms a layer between the

flame and the refractory and reduces heat flux to the refractory in that area. In

this case, the NCG injection does not bring any negative effect on the kiln

performance. However, it may not be always the case. The gas combustion

process and the heat flux to the refractory could be worse if the NCG injection is

not appropriate.

3.7 Fir ing alternative fuels

Oil and petroleum coke are often alternative fuels for many lime kilns. Because of

different fuel properties, the process in the kiln appears different when firing


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different fuels. Figures 13 and 14 show predicted gas temperature in the kiln

when firing oil and petroleum coke respectively. Since oil contains more

hydrogen than natural gas, the flame temperature is much higher than that when

firing gas even the total heat input is the same. Petroleum coke is harder to be

ignited comparing with gas and oil, and as a result, the combustion is delayed.

Figure 13 Gas temperature when firing oil

Figure 14 Gas temperature when firing petroleum coke


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4 Simulator Technology

Process modeling is an effective and economical method of analyzing and

diagnosing process operations. The highly informative and detailed information

provided by modeling cannot be achieved by any other means. Environments

within process equipment, such as lime kilns, is either inaccessible or too volatile

to derive sufficiently detailed measurements to gain a thorough understanding of

the process. Even if it were possible, comprehensive measurements over

different operating conditions would be prohibitively expensive.

Process modeling provides effective, safe, and economical ways of creating a

detailed database of information about a process. Data includes detailed three

dimensional fields of velocity, temperature, gas species concentration (O2, CO,

CH4 NOx, TRS), heat transfer, fuel combustion, and a host of other important

information.

Despite the successes of modeling, it still remains a tool used by engineers who

usually have more than a decade of theory, training, and experience in this area.

The intensive amount of work necessary to set up, compute, and display results

for a process model, plus the knowledge required, makes it an ineffective tool for

mill personnel to use directly.

This issue has been addressed and new technologies have been developed to

package the results of process modeling into an interactive, intuitive, easy to use

software.

Figure 15 shows a schematic of the simulation system. To start, a lime kiln is

analyzed to map out the range of input control parameters of interest. Next, a

matrix of input conditions is developed. Each unique set of input conditions (i.e.,

primary air flowrate, fuel flowrate, burner angle) is termed a case. The process

model is applied to each case, and the results are stored in a database. Next,

the results are fed into a proprietary neural network system that learns the

relationship between the input data and complex three-dimensional field data that


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is generated by the model. Once properly trained, the network can rapidly

reproduce the training data to a specified accuracy. The most important aspect

of the network lies in the ability to generate accurate results for a case not

included in the training set. This allows the operator to adjust control settings

much like operating a real kiln, and to nearly instantaneously view the results.

ariableInput

Conditions

NeuralNetworkSystem

ProcessModeling

InteractiveGraphicalInterface

ProcessAnalysis

ProcessKnowledge

OperatorTraining

Figure 15 Advanced simulation and training

New technology for interactive display of results has also been developed. The

core of this system consists of four main components:

1. A virtual data camera that allows users to interactively view complex 3D data

in any perspective.

2. An iconic-based (DCS-like) viewer for displaying integrated and summarized

process information.

3. An HTML-based system for displaying instructional information.

4. An ergonomic control interface for setting process control input data.

Figures 16-19 show examples of these components.


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Figure 16 The virtual data camera

O2

TRS

TAVE

3.7%

24 ppm

820 K

Primary Air 0.974 kg/s

Secondary Air 3.507 kg/s

Fuel (Ch4) 0.265 kg/sInput Excess Air 2.9%

Burner Angle -2.5 degrees

Average Wall Temperature

Average Heat Flux to Mud

Figure 17 A sample DCS panel

The system allows users to interactively view process data in a

three-dimensional virtual environment. Using proprietary neural network

technology, a user can vary input control parameters and instantly view


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corresponding results. Results can be visualized in terms of flow animations and

streamlines, scalar and vector fields, scalar isosurfaces, and particulate

animations and distributions. Integrated and summarized process information is

shown on organized DCS-like screens. The system has an HTML based module

that can be used for classroom and web based training.

The software can be used to rapidly analyze and rectify process problems, or to

create virtual equipment for operator training. If equipment modifications are

made, new data from process modeling can easily be added.

Users can compare and contrast different operating conditions, making what if

scenarios a snap. HTML based lesson training, integrated into the system, can

guide users through a details series of lesson with ease. The learning curve for

new operators is dramatically shortened. Common insight into what used to be

guesswork means less shift to shift operating variation and ultimately more

effective operations. Dangerous operating conditions, useful for training, can

safely and easily be explored.

Figure 18 HTML based training


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Engineers can use the software to diagnose equipment problems. Refractory

failures? Dynamically adjust input conditions to reduce hot spots while ensuring

other aspects of the process remain in spec. TRS emissions too high? Examine

fuel/air mixing and combustion in detail to look for causes. Determine that a new

burner is needed? Modeling data can easily be added for the new burner.

Engineers and managers can evaluate the retrofit beforethey buy, greatly

reducing the risks on capital expenditures and maintenance downtime.

Figure 19 Control interface

5 Conclusions

Greater process knowledge in the hands of operators, engineers, and managers

will lead toward optimized equipment design and operation, and will have

significant impact on mill economics. Complex process models have been

developed that provide a detailed database of information about the process.

The models are complimented by new software tools that provide the process

information in an interactive user-friendly environment, allowing mill personnel to

maximize the benefits of process modeling.

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