Computational Sciences and Engineering (CSE): A New ...”Computational” Sciences and Engineering ( CSE ) ... seismic analysis − Reservoir and ... • Obtaining knowledge of applied

Computational Sciences and Engineering (CSE):A New Paradigm in Scientific

Research & Education

Abul K. M. Fahimuddin

Scientific Research Staff

Institute of Scientific Computing

Technical University Braunschweig

Germany

Technical University Braunschweig Institute of Scientific Computing

Motivation: Chemical Dispersion in Urban Areas


Motivation: Natural Disaster Simulation


Motivation: Crash Test for Automobiles


Motivation: Research Related to Defense


Driving Forces behind these Applications ?

• In depth understanding of the application problem,

• Advanced numerical techniques, and

• Tremendous growth in high performance computing (HPC)

⇓

”Computational” Sciences and Engineering( CSE )


Overview of the Presentation

• Evolution of Computational Sciences

• Definition & Scope of CSE

• Concrete Example of CSE Applications

• CSE Education

• Example CSE Education Program @ TU Braunschweig, Germany

• Research Challenges for Computational Scientists


First Part of the Presentation

Scope & Application of CSE


Scientific Research: Methods of Investigation

Many researchers claim that computing has become a third main method fordoing investigations, besides theory and experiments


Computation: The Third Research Method

• Computer simulation makes it possible to investigate regimes:

− Beyond current experimental capabilities

− Phenomena that cannot be replicated in laboratories


What is Computational Science and Engineering ?

• CSE is the practice of computer-based modeling and simulation for the study of

scientific phenomena and engineering designs.

• CSE research is multidisciplinary, as it requires:

− knowledge and methodologies from the application fields, from computerscience, and from mathematics;

− expertise in the use of the technologies that comprise today’s computingenvironments;

− the integration of the information technologies into new combinations thatprovide new capabilities.


CSE in a Nutshell !

MathCS

Application

hard/software techniques

science

C

ES


CSE Application Fields

• Various engineering disciplines :

− Computational Mechanics, Large-scale civil engg. problems

− Computational fluid dynamics, Industrial optimization problems

− Computational electromagnetics, Hydro-informatics, Reservoir simulation

• Basic Sciences :

− Computational chemistry, Computational physics, Astronomy

− Computational biology, Economics, Finance . . .


Super Computers and CSE

Knowledge of high-performance computer hardware and software is importantfor programming of computationally intensive applications


A Multi-disciplinary CSE Application Problem :

Reservoir History Matching


Statement of History Matching Problem

• History matching is a difficult inverse problem arising in the petroleum industry.

• History matching involves adjusting model parameters, with the aim of obtaininga model output, which is as close to the history (dynamic) data as possible.

• Mathemtically, the aim is to determine a spatial distribution r(x) and a set ofmodel parameters P, given the history data Θh, such that Θs − Θh ≈ 0, whereΘs = f(r,P) is the simulated/model output.

• If one assumes that the geological descriptions is true, then the history-matchingproblem reduces to determining the set of model parameters P.


Mathematical Model of History Matching

• The flow of oil in a fractured reservoir is described, in the simplest case, by alinear parabolic partial differential equation of the form:

∂u

∂t= ∇ · ( κ ∇ u ) + f (1)

where κ is the conductivity. The dependent variable u represents pressure and faccounts for the withdrawal or injection of fluid in the reservoir. Hence the histotymatching problem can be stated as:

Knowing the source term f and the initial condition and given a measurementof u(x, t) at a discrete set of points x1, · · · , xµ, determine the spatial varyingparameter κ (including the locations of discontinuities).


Multi-disciplinary Nature of History Mathching

• Required knowledge from the fields of:

− Geo-physics, seismic analysis

− Reservoir and chemical engineering

− Applied mathematics & numerical methods

− Large-scale software development, i.e. communication and programming

− Production, marketing, management & sales

• Researchers involved from :

− Geophysists & exploration experts

− Mathematicians & Statisticians

− Reservoir, civil, mechanical & chemical engineers

− Computer scientists & so on · · ·


Second Part of the Presentation

CSE Education Contents


Nature of CSE Education

• The traditional teaching of science tends to focus on theory. In contrast,CSE offers an understanding of science through the computer applications ofmathematical models.

• It also makes many science and mathematics concepts more easily accessibleto students who may otherwise not be reached; for example, those students notinterested in computer hardware, software, and algorithms for their own sake.

• In addition, by extending the examples used in education to include problemswhich may not have analytic solutions, CSE enriches the science curriculum byextending the range of problems open to study.


Nature of CSE Education . . .

Solved

ProblemEngineering &

Science

ComputerScience

NumericsMathematics

Computational Science


Intellectual Content of CSE Education

• Learning high-level computer languages and high-performance computing;

• Obtaining knowledge of applied mathematics and computational methods;

• Learning the basics of simulation and modeling;

• Learning how to interpret and analyze data visually;

• Applying acquired computing skills to at least one application area;

• Learning to communicate solution methods and results


Required Knowledge for CSE Education

EducationCSE

Computational

Tools

HighPerformance

Computing

MathematicsApplied

ApplicationScientific

Simulation

Modeling&

Visualization

Tools


Third Part of the Presentation

CSE Masters’ Program @ Germany


CSE Program at TU Braunschweig, Germany

• An international, interdisciplinary and bilingual Master’s program in Computa-tional Sciences in Engineering (CSE).

• CSE program is directed at students of engineering sciences, mathematicsand computer science.

• The program combines 3 semesters of instructions and one semester for theMaster’s Thesis.

• Each student has the greatest− possible freedom in choosing individuallyfrom the wide range of courses and lectures.


CSE Course Structure at TU Braunschweig

• Basic Core Course

− Mathematics & computer science e.g. scientific computing, PDEs, algorithm & program-

ming

− Basic engineering sciences e.g. solid mechanics, thermodynamics, electro-magnetic fields,

systemics, fluid mechanics

• Elective Core Course

− Mathematics & computer sciences e.g. parallel computing, sparse linear systems, discrete

mathematics, computer graphics, large nonlinear sysems etc.

− Basic engineering sciences e.g. finite element methods, CFD, continuum mechanics etc.

• In-depth Course

− Various fields Software management, computational bionics, model reduction etc.


Research Opportunities @ TU Braunschweig

• As a Master’s student of CSE:

− Possibilities to work as student-research worker

− Doing practical training in German industrial companies, e.g. VW, Siemens

• After finishing CSE studies:

− Working in the university as scientific research staff (Full time job)

− Start working as a PhD student in conjunction with industries

− Possibilities to begin career in various industries


An Example CSE Research Project:

PLATON Software Framework

Optimization Process

user integratedsimulation

Manager

GUI

Co

mm

un

icati

on

Mid

dle

ware

CT

L −

Co

mm

un

icati

on

Tem

pla

te L

ibra

ry(M

PI, P

VM

, T

CP

−IP

, etc

...)

Surrogate objfunc evaluation

Surrogate

Kriging

NM−Simplex

ObjectiveFunction

remote− control− steering

SimulationTasksmanages

Simulation

Simulation

Optimizer

Domain of the Thesis


Research Challenges for Computational Scientists

• Efficient portable parallel programming.

• Programming languages and libraries.

• Familiarity with partial differential equations describing physical phenomena

• Ability to carry out statistically meaningful analysis of data from both experiments

and simulations.

• Reduction of problem size

• Patience & passion for solving inter-disciplinary research problems


The End

• More information on CSE Education worldwide :

http://www.siam.org/students/resources/report.php

• Further Questions or Inquiries ?

Email to: a.fahimuddin @ tu-bs.de


Documents

Computational Sciences and Engineering (CSE): A New ...”Computational” Sciences and Engineering ( CSE ) ... seismic analysis − Reservoir and ... • Obtaining knowledge of applied