computational science and engineering rechnergestützte ...mhg/talks/rw/bac/cse_mhg.pdf ·...

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/




What is ‘‘Computational Science and Engineering’’?

Branches in Science and Engineering, where comput-ers contribute substantially to problem solving




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




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)




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




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




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


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/



B/M CSE


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



B/M CSE


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


Bachelor


Bachelor ProgramComputational Science and Engineering

http://www.cse.ethz.ch/(not yet up to date)



Bachelor


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



Bachelor


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



Bachelor


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



Bachelor


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)



Bachelor


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



Bachelor


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



Master


Master ProgramComputational Science and Engineering

http://www.cse.ethz.ch/(not yet up to date)



Master


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



Master


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



Master


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



Master


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



Master


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

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