Moduł oferowany także w ramach programów studiów:
Informacje ogólne:
Nazwa:
Modeling of Physical Processes
Tok studiów:
2013/2014
Kod:
JCS-2-106-CM-s
Wydział:
Fizyki i Informatyki Stosowanej
Poziom studiów:
Studia II stopnia
Specjalność:
Computer Methods in Science and Technology
Kierunek:
Applied Computer Science
Semestr:
1
Profil kształcenia:
Ogólnoakademicki (A)
Język wykładowy:
Angielski
Forma i tryb studiów:
Stacjonarne
Osoba odpowiedzialna:
dr hab. inż. Zimnoch Mirosław (zimnoch@agh.edu.pl)
Osoby prowadzące:
Krótka charakterystyka modułu

Opis efektów kształcenia dla modułu zajęć
Kod EKM Student, który zaliczył moduł zajęć wie/umie/potrafi Powiązania z EKK Sposób weryfikacji efektów kształcenia (forma zaliczeń)
Wiedza
M_W001 Knows and understands the physical phenomena associated with the mass, energy and momentum transport and distributions of stresses and deformations CS2A_W07 Aktywność na zajęciach,
Udział w dyskusji,
Wykonanie ćwiczeń laboratoryjnych
M_W002 Has knowledge on development trends and new achievements in the field of numerical modeling CS2A_W09 Aktywność na zajęciach,
Udział w dyskusji,
Wykonanie ćwiczeń laboratoryjnych
M_W003 Knows stages of creating numerical models and appropriate methods, techniques and tools for their implementation CS2A_W08, CS2A_W02 Aktywność na zajęciach,
Udział w dyskusji,
Wykonanie ćwiczeń laboratoryjnych
M_W004 Has broader and deeper knowledge concerning selected physical processes CS2A_W07 Aktywność na zajęciach,
Udział w dyskusji,
Wykonanie ćwiczeń laboratoryjnych
Umiejętności
M_U001 Can choose the best method for the numerical solution of selected process, and on this basis to prepare, perform and verify the model CS2A_U08 Aktywność na zajęciach,
Sprawozdanie,
Wykonanie ćwiczeń laboratoryjnych
M_U002 Can make a critical analysis, to properly interpret the results of simulation and present them correctly CS2A_U03 Sprawozdanie,
Wykonanie ćwiczeń laboratoryjnych
M_U003 Able to assess the usefulness and ability to use numerical models to better understand and improve the physical processes CS2A_U07, CS2A_U05 Aktywność na zajęciach,
Udział w dyskusji
Kompetencje społeczne
M_K001 Able to plan and allocate teamwork tasks and estimate the duration of tasks CS2A_K02 Sprawozdanie,
Wykonanie projektu
Matryca efektów kształcenia w odniesieniu do form zajęć
Kod EKM Student, który zaliczył moduł zajęć wie/umie/potrafi Forma zajęć
Wykład
Ćwicz. aud
Ćwicz. lab
Ćw. proj.
Konw.
Zaj. sem.
Zaj. prakt
Inne
Zaj. terenowe
Zaj. warsztatowe
E-learning
Wiedza
M_W001 Knows and understands the physical phenomena associated with the mass, energy and momentum transport and distributions of stresses and deformations + - + - - - - - - - -
M_W002 Has knowledge on development trends and new achievements in the field of numerical modeling + - + - - - - - - - -
M_W003 Knows stages of creating numerical models and appropriate methods, techniques and tools for their implementation + - + - - - - - - - -
M_W004 Has broader and deeper knowledge concerning selected physical processes + - + - - - - - - - -
Umiejętności
M_U001 Can choose the best method for the numerical solution of selected process, and on this basis to prepare, perform and verify the model - - + - - - - - - - -
M_U002 Can make a critical analysis, to properly interpret the results of simulation and present them correctly - - + - - - - - - - -
M_U003 Able to assess the usefulness and ability to use numerical models to better understand and improve the physical processes - - + - - - - - - - -
Kompetencje społeczne
M_K001 Able to plan and allocate teamwork tasks and estimate the duration of tasks - - + - - - - - - - -
Treść modułu zajęć (program wykładów i pozostałych zajęć)
Wykład:

The lectures cover the following topics:
• Classification models due to different criteria (dimension, area, modeled size, etc.)
• Dynamic and static models, stationary and non-stationary models, models with lumped and distributed parameters.
• Design a variety of computational grids.
• Defining the boundary and initial conditions.
• The transformation from differential equations to integral form, the method of weighted residuals, the method of variational equations of heat and mass transfer equations balance.
• The simplifications used in the modeling (reduced dimensions, neglecting insignificant factors, etc.)
• Stages of numerical modeling. Physical model. Computational model. A mathematical model. The problem of the continuum, and an introduction to homogenization. Calibration and scaling of the model. The calculation and verification of the results.
• Selection of the numerical algorithm for solving the phenomenon (numerical stability, the stability criteria)
• Forward and inverse modeling (optimization)
• Applications and limitations of methods:
- Finite differences,
- Finite Element
- Monte Carlo
• Alternative methods:
- Molecular dynamics
- Lattice gas method
- Cellular automata
- Artificial neural networks
- Genetic Algorithms
• Modelling of:
- Distribution of stress, deformation
- Transport processes (heat, diffusion, advection, convection, etc.)
- Phase transitions
- mechanical strength

Ćwiczenia laboratoryjne:
  1. Monte-Carlo simulation of Brownian motion

    - The student knows the physical basis of Brownian motion
    - The student can apply the Monte-Carlo method to simulate this phenomenon

  2. Boiogeochemical cycles modeling

    - student is able to create a model describing a complex physical system with an appropriate simplification
    - student is able to perform the model calibration based on the available experimental data

  3. Application of lumped parameter model for groundwater flow simulation

    - student knows how to apply the convolution integral to simulate the mass transport
    - student can apply the appropriate model variant that best describes the modeled object

  4. Inverse modeling

    - student is familiar with inverse modeling technique

  5. Inverse modeling using artificial neural network technique

    - student knows the basics of artificial neural networks modeling technique
    - student can properly plan and appropriately interpret the simulation results

  6. Flow simulation using particle method

    - student knows the basic types of particle methods
    - student knows the applicability and limitations of particle methods

  7. Heat transfer modeling

    - The student is able to perform discretization of the differential equation using a simple approximation of derivatives of functions
    - The student is able to verify the correctness of the results and analyze the numerical stability of the algorithm

  8. Advection-diffusion proces simulation using explicit method

    - The student knows the equation for the advection-disspersion transport
    - The student is able to write a script for the numerical solution of differential equations using explicit method

  9. Advection-diffusion proces simulation using implicit method

    - The student can apply the appropriate boundary conditions
    - The student can write a script to numerical solution of differential equation using implicit method

  10. Application of tracers for model calibration

    - student knows how to use tracer techniques for calibration and / or verification of the model

  11. Simulation of stress distribution using finite element method

    - student is able to apply the finite element method to simulate the stress distribution
    - student knows how to properly design the computational mesh

  12. Radiative balance of the Earth

    - student knows the mechanisms affecting the radiative balance of the Earth
    - student is able to assess the impact of different model parameters on the results

  13. Modeling of atmopsheric dissperssion using gaussian approach

    - student is able to calculate the level of air pollution as a function of distance from the emitter using information from official law regulations

Nakład pracy studenta (bilans punktów ECTS)
Forma aktywności studenta Obciążenie studenta
Sumaryczne obciążenie pracą studenta 110 godz
Punkty ECTS za moduł 4 ECTS
Udział w wykładach 30 godz
Samodzielne studiowanie tematyki zajęć 20 godz
Udział w ćwiczeniach laboratoryjnych 30 godz
Przygotowanie sprawozdania, pracy pisemnej, prezentacji, itp. 30 godz
Pozostałe informacje
Sposób obliczania oceny końcowej:

Laboratory grade is calculated as an aritmetic mean from partial grades.

Completion of the course is possible when all partial grades are positive.

Final grade can be enchanced by active participation in discussions during the lectures.

Wymagania wstępne i dodatkowe:

• knowledge of linear algebra (operations on vectors and matrices)
• knowledge of calculus
• knowledge of procedural programming
• knowledge of MATLAB or similar environment is recomended

Zalecana literatura i pomoce naukowe:

Suli E., Mayers D. An Introduction to Numerical Analysis. Cambridge University Press, 2003.

Sportisse B., Air Pollution Modelling and Simulation. Springer 2002.

Walker J.C.G. Numerical Advantures with Geochemical Cycles. Oxford niversity Press, 1991.

Praca zbiorowa, Use of Isotopes for Analyses of Flow and Transport Dynamics in Groundwater Systems. IAEA Tech-Doc

Blackadar A.K., Turbulence and Diffusion in the Atmosphere. Springer 1997.

Wells N., The atmosphere and Ocean. John Willey & Sons, 1999.

Carey G.F., Finite Element Modeling of Environmental Problems. Surfce and Subsurface Flow. Wiley, 1995.

Griebel M., Knapek S., Zumbusch G. Numerical Simulation in Molecular Dynamics. Springer 2007.

Publikacje naukowe osób prowadzących zajęcia związane z tematyką modułu:

Nie podano dodatkowych publikacji

Informacje dodatkowe:

Brak