University “Babeş-Bolyai” Cluj-Napoca, ROMANIA
Faculty of Chemistry and Chemical Engineering
Department of Chemical Engineering
http://chem.ubbcluj.ro
Group of Chemical Process
Modeling,
Control and Simulation
http://chem.ubbcluj.ro/~chemeng/HPteam.html
Group of Chemical Process Modeling,
Control and Simulation
• Prof.dr.ing. Şerban AGACHI
control engineer
Head of Department, vice-rector of UBB
• Lect.dr.ing. Árpád IMRE-LUCACI
chemical engineer
• Lect.dr.ing. Mircea CRISTEA
control engineer
• Lect.dr.ing. Zoltán NAGY
chemical engineer
• Assit.drd. Anamaria CORMOŞ
chemist
Research Projects
• Modeling, Simulation and Advanced Control (Model Predictive) of Industrial
Electrolysers (Ion Exchange Membrane and Amalgam Process)
• Controllability Analysis and Model Predictive Control of Chemical Reactors
• Model Predictive Control of PVC batch reactors and Fluid Catalytic Cracking Units
• Sensitivity studies of chemical processes
• Process control and virtual instrumentation using LabVIEW environment
• Modeling and Model Predictive Control of bioreactors
• Adaptive control algorithms
• Simulation of chemical processes using MATLAB, SIMULINK, FEMLAB, ASPEN,
CHEMCAD, HYSYS, PRO/II,
• Direct digital control of chemical processes (CSTR, batch reactors)
• System for energy management in chemical industry
• Optimization of chemical processes (Pontryagin's maximum principle applied to
fixed bed methanol reactor, nonlinear programming applied to industrial
electrolysers)
• Multimedia applications in Computer Aided Education
• Modeling and control of recovering ammonia in the Ash Soda process
• Modeling and control of dryers in the ceramic industry
• Neural Networks in chemical kinetics and chemical engineering
• Environmental Pollution Mathematical Modeling and Simulation
Main Projects
1. Project supported by the World Bank and Romanian Government, No 70,
Theme: Computer Aided Chemical Engineering. Code 70.
Director: Prof.Dr.Ing. Şerban Paul Agachi. Value: 294,750 USD.
2. Institutional Partnership Project supported by the Swiss National Science Foundation,
in collaboration with Eidgenössische Technische Hochschule Zürich. No. 7 IP 62643.
Computer Aided Process Engineering. Director: Prof.Dr.Ing.Şerban Paul Agachi.
Romanian Coordinator: Lect.Dr.Ing. Cristea Vasile Mircea. Value: 48,000 CHF.
3. Project supported by the National Council of Scientific Research in High Education (CNCSIS),
Theme 42, No. 349/2001. Dynamic Mathematical Model and Optimization of the Brine
Electrolysis Process in Reactors with Ion Exchange Membrane. Optimization and optimal
process control. Director: Lect.Dr.Ing. Imre Arpad. Value: 80,000,000 lei.
4. Project supported by the National Council of Scientific Research in High Education (CNCSIS),
Theme B26, No. 7042/2001. Development and Practical Implementation of Model Predictive
Techniques for the Distillation Column. Director: Lect.Dr.Ing. Nagy Zoltan. Value: 28,260,000 lei.
5. Project supported by the National Council of Scientific Research in High Education (CNCSIS),
Theme 12, No. 57/2001. Development of Advanced Control Algorithms for Chemical Process
Control. Director: Lect.Dr.Ing. Cristea Vasile Mircea. Value 45,000,000 lei.
6. Project supported by the National Council of Scientific Research in High Education (CNCSIS),
Themes 9/25, No. 1259/177, 2002/2003. Software for remote data acquisition and control, remote
work and videoconference applied in chemical engineering research and education.
Director: Lect.Dr.Ing. Cristea Vasile Mircea. Value 113,000,000 lei.
7. Project supported by the Ministry of Research and Education in the frame of Information Society
Romanian Project, Project number 115/2003, Wireless monitoring system of industrial pollutant
emissions. Director: Prof.Dr.Ing. Şerban Paul Agachi. Value: 900,000,000 lei.
International scientific meetings
attended in 1999-2003
• Artificial Intelligence in Industry, AIII'98, High Tatras, Slovakia, 1998
• 13th International Congress of Chemical and Process Engineering CHISA'98, Prague, Czech
Republic, 1998
• 2nd Conference on Process Integration, Modeling and Optimization for Energy Saving and
Pollution Reduction PRES'99, Budapest, Hungary, 1999
• 5th International Conference on Computer Aided Engineering Education, CAEE'99, Sofia,
Bulgaria, 1999
• XIth Romanian International Conference on Chemistry and Chemical Engineering, RICCE-11,
Bucharest, Romania, 1999
• American Control Conference, ACC'2000, Chicago, Illinois, USA, 2000
• 14th International Congress of Chemical and Process Engineering CHISA'2000, Prague, Czech
Republic, 2000
• European Symposium on Computer Aided Process Engineering, ESCAPE-11, Denmark, 2001
• 5th Italian Conference on Chemical and Process Engineering ICheaP-5 Congress, Florence,
Italy, 2001
• 4th Conference on Process Integration, Modeling and Optimization for Energy Saving
and Pollution Reduction PRESS'01, Florence 20-23 May 2001
• International Conference and Exhibition Filtech Europa 2001, Düsseldorf, Germany, 2001
• European Symposium on Computer Aided Process Engineering, ESCAPE-12, Holland, 2002
• European Symposium on Computer Aided Process Engineering, ESCAPE-13, Finland, 2003
Laboratory equipment
HARDWARE
SOFTWARE
• Vapor-liquid equilibrium still (Siege and Roeck Type, Normag
Labor- und Verfahrenstechnik GmbH & Co., Hofheim am
Taunus, Germany),
• Pilot plant for studying the absorption processes,
• Pilot plant for three phase fluidization systems
• Separation modules
• Laboratory kit for chemical reaction engineering studies
• Laboratory kit for momentum, heat and mass transfer studies
• Independent data acquisition and control of the pilot plants by
special National Instruments data acquisition and control cards
• Spectrophotometer Jasco V-530 UV-VIS, wave length 190-1000
nm, accuracy 0.1 nm, spectrophotometer accessories
• Thermo balance MOM
• Gas chromatograph & ITD (Axel Semrau & Finnigan MAT)
• Reactor under pressure 100 bar
• Filtration pilot equipment
• Computers
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LabVIEW 6.0,
Matlab 6.5,
Simulink 3.0,
HYSYS,
ChemCAD 5.0,
Aspen Plus 12
Cosmos M
Designer,
• Hazoptimizer.
ILUDEST bubble cap tray column
with the following characteristics:
• 30 practical plates;
• operation volume 10 liters;
• reboiler with quartz heating rod 2 kW;
• column head with solenoid controlled reflux-withdrawal divider
and condenser;
• distillate cooler (cooling agent – water);
• feed heating system with quartz heating rod, 0.5 kW;
• product receivers 5 liters capacity each, to store the feed
mixture respectively to collect the bottom and head product;
• diaphragm pumps for feed and bottom product withdrawal;
• 39 sampling valves on every tray, for feed, bottom, distillate
flows.
The data acquisition and control system provided with the
system comprises the following components:
• sensors: 18 temperature sensors places on every second tray,
feed, reboiler and condenser; measurement of absolute
pressure at top and differential pressure between the top and
bottom, level probes, flow sensors, etc.
• actuators in the plant: solenoid valves, heating elements
(described above) liquid and vacuum pumps
• Personal computer and accessories
• 19” “ILUDEST-MOS” unit as an interface between distillation
plant and PC.
The ILLUDEST distillation column from the
Process Control Laboratory at UBB Cluj
Mathematical models developed
Dynamic model of the Fluid Catalytic Cracking Unit
• Models for two main industrial units: the Model IV FCCU and the UOP FCCU.
• Number of equations: 18 time dependent differential and 2 time and space dependent
differential equations.
• Software implementation: Matlab&Simulink.
• Model fitted with industrial data for the UOP FCCU.
• Controllability analysis
• Decentralized PID Control and Model Predictive Control.
Dynamic model of brine electrolysis in IEM reactors
• Model of the industrial process for brine electrolysis in IEM reactors
• Number of equations: 70 time dependent differential and 350 non-linear algebraic
equations.
• Software implementation: Matlab&Simulink.
• Model fitted with industrial data.
• Process optimization.
• Decentralized PID Control and Model Predictive Control.
Mathematical models developed
Dynamic model of a binary distillation column
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Model for continuous separation of n-propanol/water mixture
Number of equations: 42 time dependent differential and 122 algebraic equations.
Software implementation: Matlab&Simulink, C++
Model fitted with experimental data
Simulation and Model Predictive Control.
Dynamic model of PVC reactor
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Model for industrial batch process for polymerization of vinyl chloride
Number of equations: 10 ODE and 150 non-linear algebraic equations.
Software implementation: Matlab&Simulink.
Model fitted with industrial data.
Process optimization.
PID Control and Model Predictive Control.
Mathematical models developed
Dynamic model of a continuous fermentation bioreactor
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Model of a yeast fermentation bioreactor
Number of equations: 8 time dependent differential and 20 algebraic equations
Software implementation: Matlab&Simulink, C++
Model fitted with experimental data
Simulation and Model Predictive Control..
Artificial Neural Network based dynamic
model of a bioreactor
• Software implementation: Matlab
• Model fitted with experimental data.
• Nonlinear Model Predictive Control.
Mathematical models developed
Dynamic model of the Drying Process of Electric Insulators
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Dynamic model of the Drying Process of Electric Insulators.
Number of equations: 6 time dependent differential equations and 5 algebraic equations.
Model fitted with industrial data for the drying chamber of electric insulators.
Software implementation: Matlab&Simulink.
Controllability analysis.
PID Control of the gases temperature and moisture content of the drying product.
Model Predictive Control of the gases temperature and moisture content of the drying
product.
• Fuzzy Logic Control of the gases temperature and moisture content of the drying product.
• Neural Networks Model Based Control of the gases temperature and moisture content of
the drying product.
Mathematical models developed
Dynamic model of brine electrolysis in
amalgam cathode reactor
• Number of equations: 154 time dependent differential equations and more
than 500 non-linear algebraic non-linear equations
• Software implementation: Matlab&Simulink.
• Decentralized PID Control and Model Predictive Control.
Dynamic model of the Rotary Calcium
Soda Ash Production
• Number of equations: 7 time and space dependent differential equations and 2
algebraic equations
• Software implementation: Matlab&Simulink.
• Controllability analysis.
• PID & Model Predictive Control of the product sodium carbonate content
Mathematical models developed
Mathematical model of river pollution
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Steady state and dynamic mechanistic model
Time and space dependent differential equations
Software implementation: Matlab&Femlab
Simulation of propagation along the rivers for water soluble pollutants
Dynamic and steady-state model for ethanol-water
continuous distillation
• Software implementation: ChemCAD, HYSYS, Pro/II, AspenPlus, Aspen Dynamics
• Design, control
• Comparison of simulation results with real pilot plant data
Mathematical modeling and Simulation of Racemic Calcium
Panthothenate Synthesis
• Steady state and dynamic models developed in ChemCAd, HySys, Aspen
Plus, PRO/II - models fitted with industrial data
Industrial Data Acquisition System
Steam production and management in a thermo-electric station
• Natural gas, water consumption
and steam production monitoring
for 6 networked industrial boilers
• Steam consumption management
for 20 industrial consumers
• Provides water, natural gas and
steam flow, both instant and
integrated values on different time
intervals
• Generates graphic charts and
printable reports with the measured
values
• 96 transducers for temperature,
pressure and flow measurements
for gas, water and steam
• National Instruments SCXI
components and LabView software
development system
Industrial Data Acquisition System