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Process Optimization for the Cement Industry

Process Optimization for the Cement Industry

What is process optimization ? Getting better results without big investment

Who needs process Optimization? Equipment suppliers, Cement producers, corporations,

associations Everybody !

How does it work? Identification of limitations

Understanding of root causes

Provision of solutions to overcome limitation/shortcoming

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Permanent Need For Process Optimization

• Cost pressure and ever changing requirements force cement plants to modify & optimize their production process continuously

• The process inside the vessel is different from what it looks like from the outside!

• Equipment as delivered by OEM‘s needs to be adapted:

• “as much as necessary – as little as possible”

• Supplier-independent optimization is necessary for: • Process • Equipment • operation

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The aixergee Approach

Understanding the process & optimize it:

Process optimization needs

• a knowledgeable understanding of the real plant and the transfer to the model

• Careful check of the model and its computational results

• Solutions from experts as a synthesis from their know-how and the models results

Modeling • gas-flows • meal flows • combustion • calcination • mineralization • emission • clinker quality • …

transfer

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The aixergee Approach

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• Site visits • Measurements • Control system • Operator interviews

Analysis

Data collection from control system Operator interviews

On-site visits including measurements

Generate a deep understanding of

pneumatic, physical and chemical

phenomena. Detect root causes and eliminate those

Proposal

Develop a reasonable and materializable

solution

Data assessment

The aixergee Approach

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CFD modeling Flowsheet modeling Preheater exhaust gas StackTemperature 360 °C Temperature 110 °CFalse air ingress tower 20000 Nm³/h False air ingress conditioning tower & ESP 0 Nm³/hFlow rate 203352 Nm³/h Flow rate 203352 Nm³/hFlow rate 471508 m³/h (@360°C) Flow rate 285288 m³/h (@110°C)O2-content n.a. vol-% O2-content 6,5 vol-%

SO3-content n.a. vol-% SO3-content n.a. vol-%NOx-content n.a. ppm NOx-content 1000 ppm

Cyclone 1Exit temperature gas 360 °C Cyclone 2Meal temperature n.a. °C Exit temperature gas 550 °CPressure -48 mbar Meal temperature n.a. °CNumber of cyclones 1 Pressure -37 mbar

Number of cyclones 1

Cyclone 3Exit temperature gas 670 °CMeal temperature n.a. °C Cyclone 4Pressure -29 mbar Exit temperature gas 800 °CNumber of cyclones 1 Meal temperature 810 °C

Pressure -21 mbarNumber of cyclones 1

Cyclone 5Exit temperature gas 890 °CMeal temperature 865 °C BypassPressure -15 mbar Objective No bypassNumber of cyclones 1 Temperature after mixing chamber °C

Total flow rate Bypass ID fan m³/hKiln inlet Flow rate cooling fan m³/hTemperature 1000 °C Dust load mg/m³pressure -2 mbar LOI bypass dustO2-content 0,4 vol-%

SO3-content n.a vol-%NOx-content n.a vol-% Flow rates are calculated on the basis of oxygen content at stack

False air ingress assumed based on typical values

Energy, species and mass balancing

• Site visits • Measurements • Control system • Operator interviews

Data assessment Analysis Proposal

Develop a reasonable and materializable

solution

• Conventional • Mass & Energy

Balancing • Combustion • Process models • CFD • CPFD • Thermochemical models

The aixergee Approach

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Modification/Retrofit Detail Engineering Basic Engineering

• Site visits • Measurements • Control system • Operator interviews

Data assessment Analysis Proposal

• Conventional • Mass & Energy

Balancing • Combustion • Process models • CFD • CPFD • Thermochemical models

• Process settings • Control concepts • Modification/Retrofit • Equipment selection • Basic Engineering • Detail Engineering

DEM:

Discrete Elements

CFD:

Euler/Lagrange Euler/Euler

The aixergee Approach – Modeling Options

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low (e.g.: behind filter) high (e.g.: silo discharge)

Influence of particle on the multi-phase flow

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Flowsheet Simulation: Mass- & energy balances – properties of process

equipment

Granular flow

modeling

CPFD:

MP-PIC (multi phase – particle in cell)

Conventional - Spreadsheet,

Table

Conventional - Spreadsheet,

Table

Modeling of a cyclone preheater

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Preheater with shaft-stage: high temperatures and unstable operation

• Twin-string preheater with common shaft-stage

• Meal from stage 1 introduced above the shaft-stage

• Meal from stage 2 introduced into shaft-stage

• Meal from stage 2 also partially bypassed around the shaft-stage

Where does the meal go?

Does it take this path continuously?

Degree of calcination?

Stable kiln operation?

What is the optimum for lowest exhaust gas temperatures?

Modeling of a cyclone preheater

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Preheater with shaft-stage: where does the meal go?

Meal from stage 2 into riser duct:

Enters the shaftstage in suspension from the riser duct

Splits into: 1 stream upwards

2 stream downwards

Meal from stage 2 into shaft-stage (left side)

falls down

Meal from stage 2 into shaft-stage (left side)

falls down

Meal from stage 2 into shaft-stage (right side)

Splits into: 1 stream upwards

2 stream downwards

Modeling of a cyclone preheater

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Preheater with shaft-stage: where does the meal go?

Meal flow and gas temperatures:

• Meal particles flowuncontrolledly

• Huge temperaturedifferences within theshaft-stage

• Calcination veryinhomogenuous

• Kiln operation disturbedby unstableprecalcination

• Preheater exhaustgastemperatures high

Modeling of a cyclone preheater

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Distribution of the calcination degree: • Either uncalcined (20 % of quantity) or fully calcined (35 % of

quantity) material enters the preheater cyclones

• Rather no partly decarbonized material delivered to the cyclones

• While fine particles can be of both types, coarse particles are likely uncalcined

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Modeling of a cyclone preheater

• Counter-current flow with internal recycles requires model based mass and energy balancing

• Combination of flow sheets and CFD

• Dynamic flow-sheets based on unit operations

• Customized models for specific process units featuring

• miscellaneous material/phase properties

• solid flows including particle size distribution

Which split-rates for the meal produce the lowest exhaust gas temperature?

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Transfer of the CPFD-model into a dynamic flowsheet-model

Plant design operation

Current plant operation

Optimum plant operation

Optimization of the cyclone preheater

Parameter study shows: • Optimum operation point can be found generating a shaft exit

temperature of 715 °C • Todays operation generates 750 °C (at worse calcination!) • PH exit Temperature can be lowered by 30 °C • Heat consumption of kiln can be lowered by approx. 100 kJ/kg Cli

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CFD Modeling

Kiln burner:

• Energy loading of sintering zone • Material quality of product • Mineralogy • Burn-out • Ash drop-out

Calciner:

• Lower particle loading • Complex chemistry • Dynamic / transient simulation • Numerical evaluation: • Particle classes • Residence times • Calcination degrees • Fuel burn out rates • Histograms of particles • Scenario studies • Sensitivity analyses • Forward simulation of modifications • “Virtual plant”

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Conclusion

Process Optimization achieves: • Improvement of plant performance, e.g.:

• Reduction of exhaust gas temperatures

• Reduction of pressure drops

• Stabilization of plant operation

• Increase of secondary fuel utilization

• Increase of product quality

• Support of decision making through virtual plant simulation:

• Comparative rating of different optimization options

• Feasibility checks

• Investment safeguarding

• Speed up of optimization projects:

• No trial & error but target directed action

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Some References

CEMEX WestZement, Beckum CEMEX OstZement, Rüdersdorf CEMEX UK, Rugby, UK

China United Cement Company, Wulanchabu, CHN

ECOMB AB, Södertälje, SWE

Greco, Gödersdorf, AUT

HeidelbergCement, Harmignies, BEL

Holcim Czesko, Prachovice, CZ

KHD Humboldt Wedag, Köln

Lagan Cement, Kinnegard, IRL

LHOIST, Flandersbach

Loesche GmbH, Düsseldorf

Praxair Deutschland, Düsseldorf

CEMENTAREN Ladce, Ladce, SVK

Thyssen Krupp Polysius, Neubeckum

ECRA CCS-Research Partner

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