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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Multigrid Methods for Process Simulation

Multigrid Methods for Process Simulation

Joppich, Wolfgang
Mijalkovic, Slobodan

Paperback

Series: Computational Microelectronics

Technology & EngineeringGeneral MathematicsProgramming

ISBN10: 3709192552
ISBN13: 9783709192559
Publisher: Springer Nature
Published: Jan 22 2012
Pages: 309
Weight: 1.17
Height: 0.69 Width: 6.69 Depth: 9.61
Language: English
It was about 1985 when both of the authors started their work using multigrid methods for process simulation problems. This happened in- dependent from each other, with a completely different background and different intentions in mind. At this time, some important monographs appeared or have been in preparation. There are the three classical ones, from our point of view: the so-called 1984 Guide [12J by Brandt, the Multi-Grid Methods and Applications [49J by Hackbusch and the so-called Fundamentals [132J by Stiiben and Trottenberg. Stiiben and Trottenberg in [132J state a delayed acceptance, resent- ments with respect to multigrid algorithms. They complain: Nevertheless, even today's situation is still unsatisfactory in several respects. If this is true for the development of standard methods, it applies all the more to the area of really difficult, complex applications. In spite of all the above mentioned publications and without ignoring important theoretical and practical improvements of multigrid, this situa- tion has not yet changed dramatically. This statement is made under the condition that a numerical principle like multigrid is accepted, if there exist professional programs for research and production purposes. Professional in this context stands for solving complex technical prob- lems in an industrial environment by a large community of users. Such a use demands not only for fast solution methods but also requires a high robustness with respect to the physical parameters of the problem.

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