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PROCESS SYSTEMS ENGINEERING GROUP

Førsteamanuensis Tore Haug-Warberg. Professor Heinz Preisig. PROCESS SYSTEMS ENGINEERING GROUP. Process modelling Including thermodynamic modelling Process optimization and control Process simulation and design Systems biology. Førsteamanuensis Nadi Skjøndal-Bar. Professor

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PROCESS SYSTEMS ENGINEERING GROUP

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  1. Førsteamanuensis Tore Haug-Warberg Professor Heinz Preisig PROCESS SYSTEMS ENGINEERING GROUP • Process modelling • Including thermodynamic modelling • Process optimization and control • Process simulation and design • Systems biology Førsteamanuensis Nadi Skjøndal-Bar Professor Sigurd Skogestad Professor II Krister Forsman, Perstorp 1 postdoc 5 PhD students 16 Master students

  2. 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 + +

  3. 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 +

  4. 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.)

  5. 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)

  6. 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

  7. TKP11Advanced 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

  8. TKP12Thermodynamics, 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.

  9. TKP13 Feedback systems in biology • Lecturer: Associate ProfessorNadi 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.

  10. 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)

  11. Projects Krister Forsman 76. Cascade control 77. Implementation of ratio control 78. Variance minimizing control 79. Industrial control case at Perstorp

  12. 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

  13. Model Library Equation Library MatLab DAE Model Species data Documentation Reaction data MODELLER Graph of Behaviour MatLab Library MatLab Data of Behaviour 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

  14. Tore Haug-WarbergResearch projects 2013 • Thermodynamics of LNG using the GERG equation of state. • Taylor-expansion of thermodynamic equilibrium states arising from flash calculations. • Validationofthermodynamicstatecalculations in Brilliant (Petrell). • Code wrappers in Python, Ruby, Lua for thermodynamicutilitysoftware (SINTEF). • Advanced massbalancesof zink refinery (Boliden-Odda).

  15. 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)

  16. Conclusion: Welcome to K4 – 2nd floor!

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