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Название: Accuracy of Mathematical Models: Dimension Reduction, Homogenization, and Simplification
Автор: Sergey I. Repin, Stefan A. Sauter
Издательство: European Mathematical Society
Год: 2020
Страниц: 335
Размер: 10.44 МБ
Формат: PDF
Язык: English
The expansion of scientific knowledge and the development of technology are strongly connected with quantitative analysis of mathematical models. Accuracy and reliability are the key properties we wish to understand and control. This book presents a unified approach to the analysis of accuracy of deterministic mathematical models described by variational problems and partial differential equations of elliptic type.
It is based on new mathematical methods developed to estimate the distance between a solution of a boundary value problem and any function in the admissible functional class associated with the problem in question. The theory is presented for a wide class of elliptic variational problems. It is applied to the investigation of modelling errors arising in dimension reduction, homogenization, simplification, and various conversion methods (penalization, linearization, regularization, etc.). A collection of examples illustrates the performance of error estimates.
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Автор: ak5812 31-01-2021, 18:10 | Напечатать |
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Accuracy of Mathematical Models: Dimension Reduction, Homogenization, and Simplification 
