Computational Partial Differential Equations: Numerical Methods and Diffpack Programming
apr, 2013 · Lecture Notes in Computational Science and Engineering 2-kitob · Springer Science & Business Media
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During the last decades there has been a tremendous advancement of com puter hardware, numerical algorithms, and scientific software. Engineers and scientists are now equipped with tools that make it possible to explore real world applications of high complexity by means of mathematical models and computer simulation. Experimentation based on numerical simulation has become fundamental in engineering and many of the traditional sciences. A common feature of mathematical models in physics, geology, astrophysics, mechanics, geophysics, as weH as in most engineering disciplines, is the ap pearance of systems of partial differential equations (PDEs). This text aims at equipping the reader with tools and skills for formulating solution methods for PDEs and producing associated running code. Successful problem solving by means of mathematical models inscience and engineering often demands a synthesis of knowledge from several fields. Besides the physical application itself, one must master the tools of math ematical modeling, numerical methods, as weH as software design and im plementation. In addition, physical experiments or field measurements might play an important role in the derivation and the validation of models. This book is written in the spirit of computational sciences as inter-disciplinary activities. Although it would be attractive to integrate subjects like mathe matics, physics, numerics, and software in book form, few readers would have the necessary broad background to approach such a text.
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