Scientific Computing I  Winter 17
 Term
 Winter 17
 Lecturer
 Prof. Dr. Michael Bader
 Time and Place
 Wednesday, 1012; MI HS 2 (starts Oct 25)
 Audience
 Computational Science and Engineering, 1st semester
 Tutorials
 Steffen Seckler
time and place:
I group: Wednesday, 14:1515:45, MI 02.07.023,
II group: Monday, 14:1515:45, MI 03.13.010  Exam
 Monday, Feb 26, 2018, 13:15, room: CH 21010, HansFischerHörsaal (5401.01.101K)
2nd exam: Wednesday, Mar 28, 2018, 11:0012:30.  Semesterwochenstunden / ECTS Credits
 4 SWS (2V+2Ü) / 5 Credits
 TUMonline
 lecture, tutorial, Moodle
Contents
Announcements
 Repetition exam review: Apr 25, Wed, 08:0010:00 AM, MI 02.05.057. Student ID required.
Contents
The lecture will cover the following topics in scientific computing:
 typical tasks in the simulation pipeline in scientific computing;
 classification of mathematical models (discrete/continuous, deterministic/stochastic, etc.);
 modelling with (systems) of ordinary differential equations (example: population models);
 modelling with partial differential equations (example: heat equations);
 numerical treatment of models (discretisation of ordinary and partial differential equations: introduction to Finite Volume and Finite Element Methods, grid generation, assembly of the respective large systems of linear equations);
 analysis of the resulting numerical schemes (w.r.t. convergence, consistency, stability, efficiency);
An outlook will be given on the following topics:
 efficient implementation of numerical algorithms, both on monoprocessors and parallel computers (architectural features, parallel programming, load distribution, parallel numerical algorithms)
 interpretation of numerical results (visualization)
Lecture Notes and Material
Slides of the lectures, as well as worksheets and solutions for the tutorials, will be published here as they become available.
Day  Topic  Material 

Oct 25  Introduction  CSE/Scientific Computing as a discipline Population Models  Discrete Modeling 
slides: discipline.pdf, fibo.pdf 
Nov 6/8  Worksheet 1  Worksheet 1, Solution 1 
Nov 13/15 Nov 20/22 
Worksheet 2/3  Worksheet 2/3, Solution 2/3 
Nov 15  Population Models  Continuous Modelling (Parts I to II)  slides: population.pdf python worksheets: Population Models maple worksheets: popmodel.mw, maple_popmodel.pdf 
Nov 22  Population Models  Continuous Modelling (parts III to IV)  slides: population2.pdf python worksheets: Lotka Volterra, maple worksheets: lotkavolt.mws, maple_lotkavolt.pdf 
Nov 27/29  Worksheet 4  Worksheet 4, Solution 4, 
Nov 29  Numerical Methods for ODEs (part I) 
slides: ode_numerics.pdf python worksheets: Numerics ODE maple worksheets: numerics_ode.mws, maple_numerics_ode.pdf ipython: 
Dec 4/6  Worksheet 5  Worksheet 5,
Solution 5, ws5_ex1.py 
Dec 6  Numerical Methods for ODEs (part II) 
slides: ode_numerics.pdf python scripts for visualisation of stability: unstable explLLM2 example, visualisation of stability regions, explicit midpoint rule examples (Martini glass effec), Martini glass effect in scaled plot 
Dec 11/13  Worksheet 6  Worksheet 6, Solution 6, ws6_ex1.py, 
Dec 6/13  Heat Transfer  Discrete and Continuous Models, Finite Difference and Finite Volume Methods 
slides: heatmodel.pdf python worksheets: Heat Transfer maple worksheets: poisson2D.mws, poisson2D.pdf 
Dec 18/20  Worksheet 7  Worksheet 7, Solution 7, ws7_ex3.py 
Dec 13/20  1D Heat Equation  Analytical and Numerical Solutions  slides: heateq.pdf, heatenergy.pdf python worksheets: 1D Heat Equation,

Jan 08/10  Worksheet 8  Worksheet 8, Solution 8, ws8_ex1.py 
Jan 10/17  Introduction to Finite Element Methods  slides: pde_fem.pdf maple worksheets: fem.mw, maple_fem.pdf python worksheets: FEM 
Jan 15/17  Worksheet 9  Worksheet 9, Solution 9, ws9_ex2.py 
Jan 22/24  Worksheet 10  Worksheet 10 ,Solution 10, ws10_ex2.py 
Jan 24, 31 Feb 7 
Case Study: Computational Fluid Dynamics  slides: study_cfd.pdf 
Jan 29/31  Worksheet 11  Worksheet 11, Solution 11, ws11_ex2.py 
Feb 5/Feb 7  Worksheet 12  Worksheet 12, Solution 12, ws12_ex1.py 
Exams
 Helping material: A handwritten A4 sheet (written on both sides) will be allowed as helping material during the exam  all other items (incl. electronic devices of any kind) will be forbidden.
 Exam topics are all topics covered during the lectures. An overview is given on slide 33 of the CFD slideset: study_cfd.pdf.
Final Exam
 Date of final exam: Feb 26, 2018, 13:3015.00, room: HansFischerHörsaal (CH 21010, Chemistry Department)
 Please be on time (13.15 in the lecture hall)  the working time will start at 13.30, at the latest, and there will be organizational remarks and announcements before
 Registration: via TUMOnline
Repeat Exam
 repeat exam is currently scheduled on Mar 28, 2018, 11:0012:30.
Last Years' Exams
Please, be aware that there are always slight changes in topics between the different years' lectures. Hence, the previous exams are not fully representative for this year's exam.
 midterm exam winter 02/03, Solution
 final exam winter 02/03, Solution
 midterm exam winter 04/05, Solution
 final exam winter 04/05, Solution
 exam winter 05/06
 exam winter 06/07
 exam winter 07/08, solution
 exam winter 11/12
 exam winter repeat 11/12
 exam winter 12/13
 exam winter 13/14
 exam winter repeat 13/14
 exam winter 14/15
 exam winter repeat 14/15
The following catalogue contains questions collected by students of the lectures in winter 05/06 and 06/07. The catalogue is intended for preparation for the exam, only, and serves as some orientation. It's by no means meant to be a complete collection.
Literature
Books and Papers
 A.B. Shiflet and G.W. Shiflet: Introduction to Computational Science, Princeton University Press (in particular Chapter 3,5,6)
 G. Strang: Computational Science and Engineering, WellesleyCambridge Press, 2007
 G. Golub and J. M. Ortega: Scientific Computing and Differential Equations, Academic Press (in particular Chapter 14,8)
 Tveito, Winther: Introduction to Partial Differential Equations  A Computational Approach, Springer, 1998 (in particular Chapter 14,7,10; available as eBook in the TUM library)
 A. Tveito, H.P. Langtangen, B. Frederik Nielsen und X. Cai: Elements of Scientific Computing, Texts in Computational Science and Engineering 7, Springer, 2010 (available as ebook in the TUM library)
 B. DiPrima: Elementary Differential Equations and Boundary Value Problems, Wiley, 1992 (excellent online material)
 D. Braess: Finite Elements. Theory, Fast Solvers and Applications in Solid Mechanics, Cambridge University Press (in particular I.1, I.3, I.4, II.2)
Online Material
 Website for the book of A.B. Shiflet and G.W. Shiflet: Introduction to Computational Science
 Maple Computational Toolbox Files: contains an introduction worksheet to Maple plus several worksheets related to CSE, which are covered in this textbook.
 ODE Software for Matlab (website by J.C. Polking, Rice University)