PROCESS SYSTEMS ENGINEERING GROUP

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PROCESS SYSTEMS ENGINEERING GROUP

• Process modelling
• Including thermodynamic modelling
• Process optimization and control
• Process simulation and design
• Systems biology

Professor Sigurd Skogestad
Førsteamanuensis Nadi Skjøndal-Bar
Professor II Krister Forsman, Perstorp
1 postdoc 5 PhD students 16 Master students
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Modeling and control

• Very useful and general knowledge
• Can be used for everything ?
• Wide range of applications and job opportunities
• Usual process companies (Statoil)
• Siemens, ABB, Cybernetica, software companies
  

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• CORE SUBJECTS PROCESS SYSTEMS ENGINEERING
• Modelling
• Optimization
• Simulation, computation programming
• Control operation
• Design synthesis

• Subjects expected to remain relevant and growing
  in importance
• over the next 50 years

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4th year courses Autumn TKP4140 Process
control (Prosessregulering) Spring TKP4135
Chemical process systems engineering TKP4195
System modellering og analyse i Biologi Also
recommended spring TTK4135 Optimalisering og
regulering (tekn.kyb.)
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• 5th year courses, autumn
• TKP4555 PROCESS- SYSTEM ENGINEERING
  specialization
• Select two modules from the following
• TKP10 Process Control, Advanced Course
• TKP11 Advanced Process Simulation
• TKP12 Thermodynamics, Advanced Course
• TKP13 Feedback systems in biology
• It is also possible to select other modules, but
  this has to be approved in advance.
• Examles
• TKPX Kjemisk prosessteknologi, spesielle emner
  (distillation)
• TTK16 Modellprediktiv regulering (MPC) og
  optimalisering (Institutt for teknisk
  kybernetikk)
• TEP9 Termisk kraft/varme - produksjon (Institutt
  for termisk energi og vannkraft)

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TKP10 Process Control, Advanced Course

• Lecturer Professor Sigurd Skogestad
• Learning outcome Be able to design plantwide
  control system
• Content
• Control structure design for complete chemical
  plants.
• Selection of controlled variables
  (self-optimizing control).
• Consistent inventory Control.
• Regulatory control.
• Tuning of PID controllers.
• Multivariable control.
• Decentralized control.
• RGA. Introduction to MPC. Use of dynamic
  simulators.
• Teaching activities Lectures, computer
  simulation. exercises.
• Course material Copies from scientific papers
  and books including Chapter 10 in Skoegstad and
  Postlethwaite, "Multivariable Feedback Control,
  Wiley, 2010

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TKP11 Advanced Process Simulation

• Lecturer Professor Heinz Preisig
• Contents Simulators solve sets of equations
  representing the behaviour of plants, namely
  mathematical models for the plant. The topic of
  the course is to shed some light on what is under
  the hood of these simulators.
• The subject is extended by optimisers which are
  superimposed on the simulators upwards and
  physical property interfaces downwards.
• The course touches on the theoretical subjects
  associated with the methods used in simulators
  and optimisers, such as graph theory for the
  representation of networks, sequential modular
  approaches and simultaneous equation approaches
  and possibly integrators.
• Course form Lectures, tutorials and project. The
  course is largely project oriented.
• Prerequisites Course in numerics, optimisation
  and preferably TKP4135 Chemical Process Systems
  Engineering
• Compulsory activities exercises, presentations,
  project work

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TKP12 Thermodynamics, Advanced Course

• Lecturer Associate professor Tore Haug-Warberg
• Content
• Thermodynamic methods (Euler functions and
  Legendre transformations) with applications to
  thermodynamic state theory.
• Systematic derivation of basic equations in
  canonical state variables.
• Conservation principles of mass and energy used
  in the analysis of practical problem solutions
  connected to phase and reaction equilibria.
• Introduction to thermodynamic modelling.
• The course is adapted to individual needs if
  feasible (more weight on the modelling and less
  weight on the problem analysis, or vice versa).
• Teaching activities Regular teaching and
  colloquiums.
• Course material Lecture notes and copies of
  articles.

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TKP13 Feedback systems in biology

• Lecturer Associate Professor Nadi Skjøndal-Bar
• Aim of the course To present the concept of
  feedback in relation to biological intra- and
  intercellular processes
• Prerequisites TKP4140 process control or
  equivalent knowledge in control
• Module description The concept of feedback is
  well known from control theory, and is quite
  abundant in biology.
• Concept of negative and positive feedback inside
  the cells and in genetic circuits.
• Cellular response to combinations such as
  negative-negative, positive-negative feedback
  structures
• Oscillations and bi-stability
• Effect of feedback on the evolution of species.
• Teaching methods Seminars, self study,
  exercises/project work with presentations.
• Course material Articles and excerpts from
  textbooks.

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Sigurd SkogestadResearch projects 2014

• 69. Modelling and optimization of compact subsea
  separators
• 70. Modelling and optimization of a 2-stage
  compressor train
• 71. Optimization using ideas from self-optimizing
  control
• 72. Dynamics and plantwide control of the Dynea
  silver formaldehyde
• process
• 73. Optimal location of the throughput
  manipulator
• 74. Alternative implementations of midranging
  control
• 75. Expected problems when pairing on negative
  RGA-elements
• 75b. New method for temporary heating or cooling
  with minimal energy consumption and CO2 emission
  (with Harald Martens)

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Projects Krister Forsman

• 76. Cascade control
• 77. Implementation of ratio control
• 78. Variance minimizing control
• 79. Industrial control case at Perstorp

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Nadi Skjøndal-BarResearch projects

• 80. Simulation and numerical optimization of a
  dynamic model of model of growth (System biology
  applied modelling
• 81. Modeling and simulations of bat flight and
  sonar in 3-dimensions (Systems biology
  Neuroscience).
• 82. Modeling and simulation of path -finding and
  tracking, applied to ants

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Heinz PreisigResearch projects

• 83. Temperature distribution in milli-reactor,
  CFD-simulations
• 84. Residence-time distribution in various mixed
  systems, CFD Simulations
• 85. Nonlinear experiment design
• 86. Ontology for material models
• 87. SINTEF Bio-Refinery Pretreatment of marine
  biomass
• 88. Continuous distillation
• 89. Chemical Engineering ontology for standard
  reactor types
• 90. CAPE-OPEN interface to unit simulations
• 91. Computer-aided modelling
• 92. Control and Felles lab rejuvenation
• 93. Automatic Safety and Hazard Analysis
• 94. Simple Thermo Server (with Tore Haug-Warberg)
• 95. On time scaling in chemical processes
• 96. Frequency Analysis of Distillation
• 97. Process Identification using Wavelets
• 98. Felles lab new suggested experiment colloid
  chemistry experiment

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Tore Haug-WarbergResearch projects 2013

1. Thermodynamics of LNG using the GERG equation of
   state.
2. Taylor-expansion of thermodynamic equilibrium
   states arising from flash calculations.
3. Validation of thermodynamic state calculations in
   Brilliant (Petrell).
4. Code wrappers in Python, Ruby, Lua for
   thermodynamic utility software (SINTEF).
5. Advanced mass balances of zink refinery
   (Boliden-Odda).

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Some recent PhD graduates (and where they work)

• Federico Zenith, Control of fuel cells, June 2007
  (SINTEF Cybernetics, Trondheim)
• Jørgen B. Jensen, Optimal operation of
  refrigeration cycles, May 2008 (ABB, Oslo)
• Heidi Sivertsen, Stabilization of desired flow
  regimes using active control, December 2008
  (Statoil, Stjørdal)
• Elvira M.B. Aske, Design of plantwide control
  systems with focus on maximizing throughput,
  March 2009 (Statoil Research, Trondheim)
• Andreas Linhart, An aggregation model reduction
  method for one-dimensional distributed systems,
  Oct. 2009 (Conergy AG, Hamburg).
• Henrik Manum, Simple implementation of optimal
  control for process systems, Nov. 2010 (Statoil
  Research, Trondheim).
• Jens P. Strandberg, Optimal operation of dividing
  wall columns, June 2011 (Aker Solutions, Oslo).
• Johannes Jäschke, Invariants for optimal
  operation of process systems, June 2011 (postdoc,
  NTNU, Trondheim).
• Magnus Glosli Jacobsen, Identifying active
  constrain regions for optimal operation of
  process plants, Nov. 2011 (ABB, Oslo).
• Mehdi Panahi, Plantwide control for economically
  optimal operation of chemical plants -
  Application to GTL plants and CO2 capturing
  processes, Dec. 2011 (Aker Solutions, Oslo).
• Ramprasad Yelchuru, Quantitative methods for
  controlled variable selection, June 2012 (ABB,
  Oslo).
• Deeptanshu Dwivedi, Control and operation of
  dividing-wall columns with vapor split
  manipulation, Jan. 2013 (ABB, Oslo).
• Esmaeil Jahanshahi, Control solutions for
  multiphase flow Linear and nonlinear approaches
  to anti-slug control, Oct. 2013. (Siemens,
  Trondheim)

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Conclusion Welcome to K4 2nd floor!