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Modelling and simulation of process systems (5 cr)

Code: EN00BH64-3008

General information


Enrollment
06.11.2023 - 17.11.2023
Registration for the implementation has ended.
Timing
08.01.2024 - 26.04.2024
Implementation has ended.
Number of ECTS credits allocated
5 cr
Local portion
2 cr
Virtual portion
3 cr
Mode of delivery
Blended learning
Unit
Department of Construction and Energy Engineering
Campus
Kotka Campus
Teaching languages
English
Finnish
Seats
0 - 25
Degree programmes
Degree Programme in Energy Engineering
Teachers
Merja Mäkelä
Teacher in charge
Merja Mäkelä
Groups
ENKT21SP
Energy engineering, full-time studies
Course
EN00BH64

Realization has 3 reservations. Total duration of reservations is 8 h 30 min.

Time Topic Location
Thu 11.04.2024 time 08:15 - 13:00
(4 h 45 min)
Prosessijärjestelmien mallintaminen ja simulointi EN00BH64-3008
D1044 Tietokoneluokka, 32
Wed 17.04.2024 time 10:00 - 11:45
(1 h 45 min)
Matlab-tentti Modelling and simulation of process systems EN00BH64-3008
D1044 Tietokoneluokka, 32
Wed 17.04.2024 time 14:00 - 16:00
(2 h 0 min)
Learn-tentti Modelling and simulation of process systems EN00BH64-3008
D1044 Tietokoneluokka, 32
Changes to reservations may be possible.

Course material

1. Learn materials.
2. Dorf, C.D., Bishop, R.H., Modern Control Systems, 10. edition or some later edition, Addison-Wesley, USA 2005, 881 s.
3. Harju, T., Marttinen, A., Säätöpiirin virityksen perusteet, Control CAD, Espoo 2001, 166 s.

Study forms and methods

After completing this course, you will be able to
* derive for dynamic phenomena differential equation models based on first principles
* design and realize process experiments, analyze them and create continuous and discrete models based on sampled data
* present the arrangement and realization of multivariable control methods used in energy production and other process industries
* apply simulation and design program tools to the description of process systems.
How would you create dynamic flow balance and heat balances of a flow-through tank using differential equations for Matlab Simulink simulations
How would you realize a process experiment of a heat exchanger and work out a time-series model based on sampled data and describing heat content, using Matlab Identification Toolbox?
Why could fuzzy logic or modelpredictive control improve the quality of products or the energy efficiency of a process plant?
Why is Matlab Simulink very widely used as a basic modelling and simulation tool, and how are you able to utilize Matlab in simulations of processes?

Scheduled track:
Lectures, supervised simulation projects and computing exercises

Independent track:
Exam and project integrated in one's own work.

Blended track:
Exam and intended training projects.

RDI and work-related cooperation

RDI work is not included in the course.

Student workload

30 h online-lectures
30 h Matlab Simulink simulations and computing exercises
75 h other self-study

Evaluation scale

1-5

Assessment methods and criteria

Exam (50 %) and Matlab Simulink projects (50 %), with grades 0 - 5.

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