Mo phỏng

1. Group of Chemical Process
Modeling,
Control and Simulation
University “Babeş-Bolyai” Cluj-Napoca, ROMANIA
Faculty of Chemistry and Chemical Engineering
Department of Chemical Engineering
http://chem.ubbcluj.ro/~chemeng/HPteam.html
http://chem.ubbcluj.ro

2. 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

3. 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

4. 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.

5. 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

6. Laboratory equipment
HARDWARE
• 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
SOFTWARE
• LabVIEW 6.0,
• Matlab 6.5,
• Simulink 3.0,
• HYSYS,
• ChemCAD 5.0,
• Aspen Plus 12
• Cosmos M
Designer,
• Hazoptimizer.

7. ILUDEST bubble cap tray column
with the following characteristics:
The ILLUDEST distillation column from the
Process Control Laboratory at UBB Cluj
•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.
•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 data acquisition and control system provided with the
system comprises the following components:

8. 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.

9. Mathematical models developed
Dynamic model of a binary distillation column
• 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
• 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.

10. Mathematical models developed
Dynamic model of a continuous fermentation bioreactor
• 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.

11. Mathematical models developed
Dynamic model of the Drying Process of Electric Insulators
• 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.

12. 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

13. Mathematical models developed
Mathematical model of river pollution
• 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

14. Industrial Data Acquisition System
• 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
Steam production and management in a thermo-electric station

15. Industrial Data Acquisition System