Alfonsstr. 44 52070 Aachen Tel. +49 241 4134492-50 [email protected] www.aixergee.de
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
Leve
l of
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Proc
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ysic
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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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