ETH ZürichDepartments of Mathematics and Physics
CSERechnergestützte WissenschaftenComputational Science and Engineering
M.H. Gutknecht, Sep. 2002, page 1
Computational Science and Engineering:a New Challenge
Prof. Dr. Martin H. Gutknecht
Seminar for Applied Mathematics, ETH Zurichhttp://www.sam.math.ethz.ch/
ETH ZürichDepartments of Mathematics and Physics
CSERechnergestützte WissenschaftenComputational Science and Engineering
M.H. Gutknecht, Sep. 2002, page 2
What is ‘‘Computational Science and Engineering’’?
Branches in Science and Engineering, where comput-ers contribute substantially to problem solving
ETH ZürichDepartments of Mathematics and Physics
CSERechnergestützte WissenschaftenComputational Science and Engineering
M.H. Gutknecht, Sep. 2002, page 3
Computational Chemistry: molecules are computed before being synthesized
Computational Aerodynamics: the airflow around airplanes iscomputed in the design phase
Computational Astrophysics: the formation of stars and galaxies iscomputed
ETH ZürichDepartments of Mathematics and Physics
CSERechnergestützte WissenschaftenComputational Science and Engineering
M.H. Gutknecht, Sep. 2002, page 4
The two classic main pillars of science and engineering:
The three main pillars of Computational Science and Engineering:
theory (modelling)
experiment
numerical simulation
experiment
theory (modelling)
ETH ZürichDepartments of Mathematics and Physics
CSERechnergestützte WissenschaftenComputational Science and Engineering
M.H. Gutknecht, Sep. 2002, page 5
Reasons for numerical simulations:
• cheaper and faster than experimentse.g., wind tunnel, exploratory drilling, ...
• experiments impossiblee.g., galaxies, stars, weather, climat, cosmology, ...
• experiments influence the observationse.g., measurements in the nanoworld;measurements of very fast or very slow events[combustion in a engine; flow of a glacier]
• experiments only provide measurable quantities
ETH ZürichDepartments of Mathematics and Physics
CSERechnergestützte WissenschaftenComputational Science and Engineering
M.H. Gutknecht, Sep. 2002, page 6
Astrophysics:e.g., stars, galaxies, ...
Physics of the Atmosphere:e.g., weather, climate change, ...
Biochemistry / Chemistry / Pharmacy:e.g., molecules, genes, viruses, ...
Solid State Physics:e.g., supra coductivity, ...
Geology:e.g., oil, ground water contamination, ...
Particle Physics:e.g., quarks -> QCD, ...
Environmental Science:e.g., pollution, ...
Electrical Engineering:e.g., semiconductor devices, ...
Mechanical Engineering:e.g., fluid dynamics: turbines, cars, ...
Material Sciences:e.g., polymer molecules, ...
Chemical Engineering:e.g., production of chemicals, ...
Civil Engineering:e.g., earthquake resistance, ...
Architecture:e.g., virtuel spaces, ...
Medical Engineering:e.g., tomography, remote surgery, ...
Areas with a computational branch
Science Engineering
ETH ZürichDepartments of Mathematics and Physics
CSERechnergestützte WissenschaftenComputational Science and Engineering
M.H. Gutknecht, Sep. 2002, page 7
New opportunities in studying CSE
• Interdisciplinary education in--- mathematics (including modelling and algorithms)--- computer science (including visualization and parallel computing)--- minimum one application area in science or engineeering
• The broad interdisciplinary studies provide an excellent starting pointfor a job in industry or academia
• One of the first curricula of this kind in Europe
• Excellent job perspectives
Rechnergestützte WissenschaftenComputational Science and Engineering
ETH ZürichDepartments of Mathematics and Physics
B/M CSE
M.H. Gutknecht / K. Nipp, Sep. 2002, page 8
Computational Science and Engineering:the Bacholor / Master Curriculum at ETH Zurich
http://www.cse.ethz.ch/
Rechnergestützte WissenschaftenComputational Science and Engineering
ETH ZürichDepartments of Mathematics and Physics
B/M CSE
M.H. Gutknecht / K. Nipp, Sep. 2002, page 9
Design principles of the curriculum
• Emphasis on Science and Engineering, not just on computing
• Computation is an essential part of the methodology
• Interdisciplinary education
• Broad view and knowledge of different fields
• In depth study of at least one application area
• Team work
• Development of communication abilities
Rechnergestützte WissenschaftenComputational Science and Engineering
ETH ZürichDepartments of Mathematics and Physics
B/M CSE
M.H. Gutknecht / K. Nipp, Sep. 2002, page 10
Organizational structure of the CSE curriculum:• The Bachelor / Master Curriculum in CSE is attached to the
Departments of Mathematics and Physics
• Several other departments are involved
Contact persons for the CSE curriculum:Rolf Jeltsch, advisor of studiesKaspar Nipp
More information:http: //www.cse.ethz.ch/
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Bachelor
M.H. Gutknecht / K. Nipp, Sep. 2002, page 11
Bachelor ProgramComputational Science and Engineering
http://www.cse.ethz.ch/(not yet up to date)
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Bachelor
M.H. Gutknecht / K. Nipp, Sep. 2002, page 12
Basic studies (1st year) to be chosen from:
Choose your favorite subject.
Prerequisite: Passed basic exam.Without passed basic exam: Tentative admission only.
• Mecanical Engineering• Electrical Engineering• Computer Science• Material Sciences• Chemistry• Mathematics• Physics
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Bachelor
M.H. Gutknecht / K. Nipp, Sep. 2002, page 13
Basic principles:
Basic Courses: Basic knowledge in Mathmatics, Science and Engineering, Computer Science
Core Courses: Methodology in Mathematics and Computer Science
Field of Specialisation: Specialisation in one computational application area
Elective Courses: CSE related
Term Paper: Application orientated work in a team,computational
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Bachelor
M.H. Gutknecht / K. Nipp, Sep. 2002, page 14
Bachelor in Computational Science and Engineering
Course type KEBasic Courses 61Core Courses 13Field of Specialisation 8Elective Courses 6Case Studies 6Term Paper 10GESS 4Bachelor Thesis (4 weeks) 10Requirement for Bachelor 120
(2nd and 3rd year)KE = Mininum number of Credit Points
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Bachelor
M.H. Gutknecht / K. Nipp, Sep. 2002, page 15
Core Courses:
a. Numerical methods in differential equations 8 KEb. Computational statistics 6 KEc. Software design 5 KEd. Visualisation and graphics 5 KE
total number of KE core courses 24 KE
Bachelor: 2 core courses to be taken (a. included)
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Bachelor
M.H. Gutknecht / K. Nipp, Sep. 2002, page 16
List of fields of specialisation:
• Astrophysics• Physics of the atmosphere• Computational chemistry• Fluid dynamics• Control theory• Robotics• Theoretical physics
Bachelor: 2 courses to be taken in one field of specialisation
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Bachelor
M.H. Gutknecht / K. Nipp, Sep. 2002, page 17
Elective courses:• 2 courses to be chosen• Choice out of more than 60 courses
Case studies:Case studies in application areas; seminars by experts from ETHand from outside (to be chosen twice after the 2nd year)Students have to give short seminar talks
Term paper:• approx. 160 hours (i.e., approx. 3 afternoons per week per semester)
• written report and seminar talk
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Master
M.H. Gutknecht / K. Nipp, Sep. 2002, page 18
Master ProgramComputational Science and Engineering
http://www.cse.ethz.ch/(not yet up to date)
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Master
M.H. Gutknecht / K. Nipp, Sep. 2002, page 19
Basic principles:Core Courses: Methodology in Mathematics and
Computer Science
Field of Specialisation: Specialisation in one computational application area
Elective Courses: CSE related
Term Paper: Application orientated work in a team, computational
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Master
M.H. Gutknecht / K. Nipp, Sep. 2002, page 20
Master in Computational Science and Engineering
Course type KECore Courses 10Field of Specialisation 24Elective Courses 6Case Studies 6Term Paper 10GESS 2Master Thesis (4 months) 30Requirement for Master 90
(1 year followed by Master thesis)KE = Mininum number of Credit Points
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Master
M.H. Gutknecht / K. Nipp, Sep. 2002, page 21
Core Courses:
a. Numerical methods in differential equations 8 KEb. Computational statistics 6 KEc. Software design 5 KEd. Visualisation and graphics 5 KE
total number of KE core courses 24 KE
Master: required are the 2 core courses not taken for the Bachelor
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Master
M.H. Gutknecht / K. Nipp, Sep. 2002, page 22
List of fields of specialisation:
• Astrophysics• Physics of the atmosphere• Computational chemistry• Fluid dynamics• Control theory• Robotics• Theoretical physics
Master: 4 courses to be taken plus a student seminar in 1 or 2 of the fields of specialisation
CSEComputational Science and EngineeringRechnergestützte Wissenschaften
ETH ZürichDepartments of Mathematics and Physics
Master
M.H. Gutknecht / K. Nipp, Sep. 2002, page 23
Elective courses:• 2 courses to be chosen• Choice out of more than 60 courses
Case studies:Case studies in application areas; seminars by experts from ETHand from outside (to be chosen twice)Students have to give short seminar talks
Term paper:• approx. 160 hours (i.e., approx. 3 afternoons per week per semester)
• written report and seminar talk