SubjectsSubjects(version: 965)
Course, academic year 2019/2020
  
Modelling Mathematical Processes for PhD Students - AP445011
Title: Modelling Mathematical Processes for PhD Students
Guaranteed by: Department of Computing and Control Engineering (445)
Faculty: Faculty of Chemical Engineering
Actual: from 2019 to 2020
Semester: both
Points: 0
E-Credits: 0
Examination process:
Hours per week, examination: 3/0, other [HT]
Capacity: winter:unlimited / unknown (unknown)
summer:unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: English
Teaching methods: full-time
Level:  
Note: can be fulfilled in the future
you can enroll for the course in winter and in summer semester
Guarantor: Kukal Jaromír doc. Ing. Ph.D.
Interchangeability : N445013, P445011
Examination dates   Schedule   
Annotation -
The course familiarizes the students with basic principles of mathematic modeling, apparatus models common in chemic sector, their evaluation, solution and simulation
Last update: Pátková Vlasta (19.11.2018)
Course completion requirements -
  • making all projects
  • final discusion on them with the demonstration of knowledge
Last update: Pátková Vlasta (19.11.2018)
Literature -

R: Tangirala A.K., Principles of System Identification:Theory and Practice, CRC Press, Boca Raton, 2015, ISBN 978-1-4398-9602-0

A: Bequette B.W.,Process Dynamics.Modeling, Analysis, and Simulation,Prentice Hall PTR,New Jersey,1998,0132068893

A: Ingham, J., Dunn, I.J., et al.:Chemical Engineering Dynamics,VCH,Weinheim,1994,9783527314607

A: Hangos, K.M., Cameron, I.T.,Process Modelling and Model Analysis,Academic Press,N.Y.,2001,0121569314

Last update: Jahoda Milan (29.11.2018)
Teaching methods -

lectures, projects and consultations

Last update: Pátková Vlasta (19.11.2018)
Requirements to the exam -

During the term some small project will be given to students. The exam has both written and oral parts. It is necessary show both the mathematical insight into the problem and basic programming knowledge in the written part.

Student will obtain credits after successful exam.

Last update: Pátková Vlasta (19.11.2018)
Syllabus -

1. Model and modeling definition, modeling postulates, model classification

2. Modeling methods, basic terms and conceptions of continuum mechanics

3. Basic equation for matter, momentum and energy sharing

4. Hydrodynamic flow models, their classification. Ideal mixing and piston flow

5. Cascade of ideal mixers model with and without back-mix

6. Dispersion model, models combination,

7. Kinetics of matter and heat transfer. Phases balance, chemic kinetics, reaction velocity, chemic balance

8. Static and dynamic behavior models. Dimensionless equations

9. Models of containers for liquids and gases

10. Models of heat exchangers I

11. Models of heat exchangers II - distribute parameters

12. Models of distillation columns

13. Models of chemical reactors, stability

14. Models of biochemical reactors

Last update: Pátková Vlasta (19.11.2018)
Learning resources -

internal materials

Last update: Pátková Vlasta (19.11.2018)
Learning outcomes -

Students will be able to:

• analyze a problem

• provide the mathematical description of the problem

• solve both static and dynamic behavior

• perform MATLAB implementation

• perform system behavior simulation

Last update: Pátková Vlasta (19.11.2018)
Entry requirements -

none

Last update: Pátková Vlasta (19.11.2018)
Registration requirements -

none

Last update: Pátková Vlasta (19.11.2018)
 
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