Zachodniopomorski Uniwersytet Technologiczny w Szczecinie

Administracja Centralna Uczelni - Wymiana międzynarodowa (S1)

Sylabus przedmiotu MODELING AND SIMULATION IN CHEMICAL ENGINEERING:

Informacje podstawowe

Kierunek studiów Wymiana międzynarodowa
Forma studiów studia stacjonarne Poziom pierwszego stopnia
Tytuł zawodowy absolwenta
Obszary studiów
Profil
Moduł
Przedmiot MODELING AND SIMULATION IN CHEMICAL ENGINEERING
Specjalność przedmiot wspólny
Jednostka prowadząca Katedra Inżynierii Chemicznej i Procesowej
Nauczyciel odpowiedzialny Anna Story <Anna.Story@zut.edu.pl>
Inni nauczyciele Bogdan Ambrożek <Bogdan.Ambrozek@zut.edu.pl>, Halina Murasiewicz <Halina.Murasiewicz@zut.edu.pl>
ECTS (planowane) 5,0 ECTS (formy) 5,0
Forma zaliczenia zaliczenie Język angielski
Blok obieralny Grupa obieralna

Formy dydaktyczne

Forma dydaktycznaKODSemestrGodzinyECTSWagaZaliczenie
wykładyW1 30 2,00,60zaliczenie
laboratoriaL1 30 3,00,40zaliczenie

Wymagania wstępne

KODWymaganie wstępne
W-1Mathematics. Fundamentals of chemical engineering.

Cele przedmiotu

KODCel modułu/przedmiotu
C-1The student will be able to: 1. Develop of process models based on conservation laws and process data. 2. Use computational techniques to solve the process models. 3. Use simulation tools such as MATLAB, POLYMATH, and ASPEN PLUS.

Treści programowe z podziałem na formy zajęć

KODTreść programowaGodziny
laboratoria
T-L-1Analysis of experimental results.4
T-L-2Nonlinear parameter estimation.4
T-L-3Development of exemplary mathematical models.4
T-L-4Modelling and simulation of selected chemical engineering systems using MATLAB, POLYMATH, CFD and ASPEN PLUS.18
30
wykłady
T-W-1Analysis of experimental results. Nonlinear parameter estimation.6
T-W-2Dimensional analysis. Scaling.4
T-W-2Mathematical model development. Synthesis of sub-models. Classification of models: deterministic, stochastic, lumped and distributed parameter.4
T-W-4Modelling and simulation techniques.8
T-W-5Population balance models. Microbial population.4
T-W-6Monte Carlo methods.2
T-W-7Nonlinear dynamics and chaos.2
30

Obciążenie pracą studenta - formy aktywności

KODForma aktywnościGodziny
laboratoria
A-L-1Class participation30
A-L-2Solving computational problems30
A-L-3Repetition of the classes content15
75
wykłady
A-W-1Obligatory attendance the lectures30
A-W-2Literature study on the topics discussed within the frame of the lectures4
A-W-3Remembering, understanding and analyzing of the lectures content4
A-W-4One-on-One teaching consultations2
A-W-5Repetition of the lectures content to the exam10
50

Metody nauczania / narzędzia dydaktyczne

KODMetoda nauczania / narzędzie dydaktyczne
M-1Lecture illustrated by Power Point presentation and computer simulation
M-2Classis illustrated by computer and manual calculations

Sposoby oceny

KODSposób oceny
S-1Ocena formująca: Periodic assessment of student achievement
S-2Ocena podsumowująca: Lecture: exam at the end of the semester Classis: written test

Zamierzone efekty uczenia się - wiedza

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
WM-WTiICh_1-_??_W01
The student will be able to develop of process models based on conservation laws and process data.
C-1T-W-1, T-W-7, T-W-2, T-W-2, T-W-5, T-W-6, T-L-1, T-L-2, T-L-3M-1, M-2S-2, S-1

Zamierzone efekty uczenia się - umiejętności

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
WM-WTiICh_1-_??_U01
The student will be able to use computational techniques to solve the process models.
C-1T-W-4, T-L-1, T-L-4, T-L-2M-1, M-2S-2, S-1

Zamierzone efekty uczenia się - inne kompetencje społeczne i personalne

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
WM-WTiICh_1-_??_K01
The student will be able to use simulation tools such as MATLAB, POLYMATH, and ASPEN PLUS.
C-1T-L-1, T-L-4M-1, M-2S-2, S-1

Kryterium oceny - wiedza

Efekt uczenia sięOcenaKryterium oceny
WM-WTiICh_1-_??_W01
The student will be able to develop of process models based on conservation laws and process data.
2,0
3,0The student is able to develop of process models based on conservation laws and process data.
3,5
4,0
4,5
5,0

Kryterium oceny - umiejętności

Efekt uczenia sięOcenaKryterium oceny
WM-WTiICh_1-_??_U01
The student will be able to use computational techniques to solve the process models.
2,0
3,0The student is able to use computational techniques to solve the process models.
3,5
4,0
4,5
5,0

Kryterium oceny - inne kompetencje społeczne i personalne

Efekt uczenia sięOcenaKryterium oceny
WM-WTiICh_1-_??_K01
The student will be able to use simulation tools such as MATLAB, POLYMATH, and ASPEN PLUS.
2,0
3,0The student is able to use simulation tools such as MATLAB, POLYMATH, and ASPEN PLUS.
3,5
4,0
4,5
5,0

Literatura podstawowa

  1. Hangos K.M., Cameron L.T., Process modelling and model analysis, Academic Press, San Diego, 2001
  2. Rice R.G., Do D.D., Applied mathematics and modeling for chemical engineers, Wiley, New York, 2011
  3. Finlayson B.A., Introduction to chemical engineering computing, Wiley, New York, 2005

Literatura dodatkowa

  1. Ingham J., Dunn I.J., Heinzle E., Prenosil J.E., Snape J.B., Chemical engineering dynamics, Wiley, Weinheim, 2007
  2. Dobre T.G., Marcano J.G.S., Chemical engineering. Modelling, simulation and similitude, Wiley, Weinheim, 2007

Treści programowe - laboratoria

KODTreść programowaGodziny
T-L-1Analysis of experimental results.4
T-L-2Nonlinear parameter estimation.4
T-L-3Development of exemplary mathematical models.4
T-L-4Modelling and simulation of selected chemical engineering systems using MATLAB, POLYMATH, CFD and ASPEN PLUS.18
30

Treści programowe - wykłady

KODTreść programowaGodziny
T-W-1Analysis of experimental results. Nonlinear parameter estimation.6
T-W-2Dimensional analysis. Scaling.4
T-W-2Mathematical model development. Synthesis of sub-models. Classification of models: deterministic, stochastic, lumped and distributed parameter.4
T-W-4Modelling and simulation techniques.8
T-W-5Population balance models. Microbial population.4
T-W-6Monte Carlo methods.2
T-W-7Nonlinear dynamics and chaos.2
30

Formy aktywności - laboratoria

KODForma aktywnościGodziny
A-L-1Class participation30
A-L-2Solving computational problems30
A-L-3Repetition of the classes content15
75
(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta

Formy aktywności - wykłady

KODForma aktywnościGodziny
A-W-1Obligatory attendance the lectures30
A-W-2Literature study on the topics discussed within the frame of the lectures4
A-W-3Remembering, understanding and analyzing of the lectures content4
A-W-4One-on-One teaching consultations2
A-W-5Repetition of the lectures content to the exam10
50
(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięWM-WTiICh_1-_??_W01The student will be able to develop of process models based on conservation laws and process data.
Cel przedmiotuC-1The student will be able to: 1. Develop of process models based on conservation laws and process data. 2. Use computational techniques to solve the process models. 3. Use simulation tools such as MATLAB, POLYMATH, and ASPEN PLUS.
Treści programoweT-W-1Analysis of experimental results. Nonlinear parameter estimation.
T-W-7Nonlinear dynamics and chaos.
T-W-2Dimensional analysis. Scaling.
T-W-2Mathematical model development. Synthesis of sub-models. Classification of models: deterministic, stochastic, lumped and distributed parameter.
T-W-5Population balance models. Microbial population.
T-W-6Monte Carlo methods.
T-L-1Analysis of experimental results.
T-L-2Nonlinear parameter estimation.
T-L-3Development of exemplary mathematical models.
Metody nauczaniaM-1Lecture illustrated by Power Point presentation and computer simulation
M-2Classis illustrated by computer and manual calculations
Sposób ocenyS-2Ocena podsumowująca: Lecture: exam at the end of the semester Classis: written test
S-1Ocena formująca: Periodic assessment of student achievement
Kryteria ocenyOcenaKryterium oceny
2,0
3,0The student is able to develop of process models based on conservation laws and process data.
3,5
4,0
4,5
5,0
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięWM-WTiICh_1-_??_U01The student will be able to use computational techniques to solve the process models.
Cel przedmiotuC-1The student will be able to: 1. Develop of process models based on conservation laws and process data. 2. Use computational techniques to solve the process models. 3. Use simulation tools such as MATLAB, POLYMATH, and ASPEN PLUS.
Treści programoweT-W-4Modelling and simulation techniques.
T-L-1Analysis of experimental results.
T-L-4Modelling and simulation of selected chemical engineering systems using MATLAB, POLYMATH, CFD and ASPEN PLUS.
T-L-2Nonlinear parameter estimation.
Metody nauczaniaM-1Lecture illustrated by Power Point presentation and computer simulation
M-2Classis illustrated by computer and manual calculations
Sposób ocenyS-2Ocena podsumowująca: Lecture: exam at the end of the semester Classis: written test
S-1Ocena formująca: Periodic assessment of student achievement
Kryteria ocenyOcenaKryterium oceny
2,0
3,0The student is able to use computational techniques to solve the process models.
3,5
4,0
4,5
5,0
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięWM-WTiICh_1-_??_K01The student will be able to use simulation tools such as MATLAB, POLYMATH, and ASPEN PLUS.
Cel przedmiotuC-1The student will be able to: 1. Develop of process models based on conservation laws and process data. 2. Use computational techniques to solve the process models. 3. Use simulation tools such as MATLAB, POLYMATH, and ASPEN PLUS.
Treści programoweT-L-1Analysis of experimental results.
T-L-4Modelling and simulation of selected chemical engineering systems using MATLAB, POLYMATH, CFD and ASPEN PLUS.
Metody nauczaniaM-1Lecture illustrated by Power Point presentation and computer simulation
M-2Classis illustrated by computer and manual calculations
Sposób ocenyS-2Ocena podsumowująca: Lecture: exam at the end of the semester Classis: written test
S-1Ocena formująca: Periodic assessment of student achievement
Kryteria ocenyOcenaKryterium oceny
2,0
3,0The student is able to use simulation tools such as MATLAB, POLYMATH, and ASPEN PLUS.
3,5
4,0
4,5
5,0