Christoph Zenger – författare

One of the main ways by which we can understand complex processes is to create computerised numerical simulation models of them. Modern simulation tools are not used only by experts, however, and reliability has therefore become an important issue, meaning that it is not sufficient for a simulation package merely to print out some numbers, claiming them to be the desired results. An estimate of the associated error is also needed. The errors may derive from many sources: errors in the model, errors in discretization, rounding errors, etc. Unfortunately, this situation does not obtain for current packages and there is a great deal of room for improvement. Only if the error can be estimated is it possible to do something to reduce it. The contributions in this book cover many aspects of the subject, the main topics being error estimates and error control in numerical linear algebra algorithms (closely related to the concept of condition numbers), interval arithmetic and adaptivity for continuous models.

One of the main ways by which we can understand complex processes is to create computerised numerical simulation models of them. Modern simulation tools are not used only by experts, however, and reliability has therefore become an important issue, meaning that it is not sufficient for a simulation package merely to print out some numbers, claiming them to be the desired results. An estimate of the associated error is also needed. The errors may derive from many sources: errors in the model, errors in discretization, rounding errors, etc. Unfortunately, this situation does not obtain for current packages and there is a great deal of room for improvement. Only if the error can be estimated is it possible to do something to reduce it. The contributions in this book cover many aspects of the subject, the main topics being error estimates and error control in numerical linear algebra algorithms (closely related to the concept of condition numbers), interval arithmetic and adaptivity for continuous models.

Dieses Buch gibt eine umfassende Einführung in die verschiedenen Aspekte der Computergraphik. Neben der Diskussion grundlegender Fragestellungen (Koordinatensysteme, Rasterung, Farbmodelle) werden dabei sowohl die geometrische Modellierung dreidimensionaler Objekte als auch deren graphische Darstellung behandelt. Weiterhin wird die Rolle der Computergraphik in aktuellen Anwendungen wie Animation, Visualisierung oder Virtual Reality beleuchtet. Unterstützt durch zahlreiche, z.T. farbige Illustrationen erhält der Leser so einen Überblick über die einzelnen Arbeitsschritte und Techniken auf dem Weg zum photorealistischen Bild.

In Douglas Adams' book 'Hitchhiker's Guide to the Galaxy', hyper-intelligent beings reached a point in their existence where they wanted to understand the purpose of their own existence and the universe. They built a supercomputer, called Deep Thought, and upon completion, they asked it for the answer to the ultimate question of life, the universe and everything else. The computer worked for several millennia on the answers to all these questions. When the day arrived for hyper-intelligent beings the to receive the answer, they were stunned, shocked and disappointed to hear that the answer was simply 42. The still open questions to scientists and engineers are typically much sim­ pler and consequently the answers are more reasonable. Furthermore, because human beings are too impatient and not ready to wait for such a long pe­ riod, high-performance computing techniques have been developed, leading to much faster answers. Based on these developments in the last two decades, scientific and engineering computing has evolved to a key technology which plays an important role in determining, or at least shaping, future research and development activities in many branches of industry. Development work has been going on all over the world resulting in numerical methods that are now available for simulations that were not foreseeable some years ago. However, these days the availability of supercomputers with Teraflop perfor­ mance supports extensive computations with technical relevance. A new age of engineering has started.

This volume contains the proceedings of an international conference on high performance scientific and engineering computing held in Munich in March 1998 and organized by FORTWIHR, the Bavarian Consortium for High Performance Scientific Computing. The 38 contributions cover engineering applications for numerical simulation from the fields fluid flow, optimal control, crystal growth and semiconductor technology, as well as numerical simulation in astrophysics or quantum chemistry. In contrast to related collections, the reader gets a really interdisciplinary spectrum of the state of the art of selected topics of scientific computing with recent results of research groups from applied mathematics, computer science, engineering, physics and chemistry.

In Douglas Adams'' book ''Hitchhiker''s Guide to the Galaxy'', hyper-intelligent beings reached a point in their existence where they wanted to understand the purpose of their own existence and the universe. They built a supercomputer, called Deep Thought, and upon completion, they asked it for the answer to the ultimate question of life, the universe and everything else. The computer worked for several millennia on the answers to all these questions. When the day arrived for hyper-intelligent beings the to receive the answer, they were stunned, shocked and disappointed to hear that the answer was simply 42. The still open questions to scientists and engineers are typically much sim­ pler and consequently the answers are more reasonable. Furthermore, because human beings are too impatient and not ready to wait for such a long pe­ riod, high-performance computing techniques have been developed, leading to much faster answers. Based on these developments in the last two decades, scientific and engineering computing has evolved to a key technology which plays an important role in determining, or at least shaping, future research and development activities in many branches of industry. Development work has been going on all over the world resulting in numerical methods that are now available for simulations that were not foreseeable some years ago. However, these days the availability of supercomputers with Teraflop perfor­ mance supports extensive computations with technical relevance. A new age of engineering has started.

When the DFG (Deutsche Forschungsgemeinschaft) launched its collabora­ tive research centre or SFB (Sonderforschungsbereich) 438 "Mathematical Modelling, Simulation, and Verification in Material-Oriented Processes and Intelligent Systems" in July 1997 at the Technische Vniversitat Munchen and at the Vniversitat Augsburg, southern Bavaria got its second nucleus of the still young discipline scientific computing. Whereas the first and older one, FORTWIHR, the Bavarian Consortium for High Performance Scientific Com­ puting, had put its main emphasis on the supercomputing aspect, this new initiative was now expected to focus on the mathematical part. Consequently, throughout all of the five main research topics (A) adaptive materials and thin layers, (B) adaptive materials in medicine, (C) robotics, aeronautics, and automobile technology, (D) microstructured devices and systems, and (E) transport processes in flows, mathematical aspects play a predominant role. The formation of the SFB 438 and its scientific program are inextricably linked with the name of Karl-Heinz Hoffmann. As full professor for applied mathematics in Augsburg (1981-1991) and in Munchen (since 1992) and as dean of the faculty of mathematics at the TV Munchen, he was the driv­ ing force of this fascinating, but not always easy-to-realize idea of bringing together scientists from mathematics, physics, engineering, informatics, and medicine for joint efforts in modern applied mathematics. However, scarcely work had begun when the successful captain was called to take command on a bigger boat.

Since the creation of the term "Scientific Computing" and of its German counterpart "Wissenschaftliches Rechnen" (whoever has to be blamed for that), scientists from outside the field have been confused about the some­ what strange distinction between scientific and non-scientific computations. And the insiders, i. e. those who are, at least, convinced of always comput­ ing in a very scientific way, are far from being happy with this summary of their daily work, even if further characterizations like "High Performance" or "Engineering" try to make things clearer - usually with very modest suc­ cess, however. Moreover, to increase the unfortunate confusion of terms, who knows the differences between "Computational Science and Engineering" , as indicated in the title of the series these proceedings were given the honour to be published in, and "Scientific and Engineering Computing", as chosen for the title of our book? Actually, though the protagonists of scientific com­ puting persist in its independence as a scientific discipline (and rightly so, of course), the ideas behind the term diverge wildly. Consequently, the variety of answers one can get to the question "What is scientific computing?" is really impressive and ranges from the (serious) "nothing else but numerical analysis" up to the more mocking "consuming as much CPU-time as possible on the most powerful number crunchers accessible" .

When the DFG (Deutsche Forschungsgemeinschaft) launched its collabora­ tive research centre or SFB (Sonderforschungsbereich) 438 "Mathematical Modelling, Simulation, and Verification in Material-Oriented Processes and Intelligent Systems" in July 1997 at the Technische Vniversitat Munchen and at the Vniversitat Augsburg, southern Bavaria got its second nucleus of the still young discipline scientific computing. Whereas the first and older one, FORTWIHR, the Bavarian Consortium for High Performance Scientific Com­ puting, had put its main emphasis on the supercomputing aspect, this new initiative was now expected to focus on the mathematical part. Consequently, throughout all of the five main research topics (A) adaptive materials and thin layers, (B) adaptive materials in medicine, (C) robotics, aeronautics, and automobile technology, (D) microstructured devices and systems, and (E) transport processes in flows, mathematical aspects play a predominant role. The formation of the SFB 438 and its scientific program are inextricably linked with the name of Karl-Heinz Hoffmann. As full professor for applied mathematics in Augsburg (1981-1991) and in Munchen (since 1992) and as dean of the faculty of mathematics at the TV Munchen, he was the driv­ ing force of this fascinating, but not always easy-to-realize idea of bringing together scientists from mathematics, physics, engineering, informatics, and medicine for joint efforts in modern applied mathematics. However, scarcely work had begun when the successful captain was called to take command on a bigger boat.