Riemann Solvers and Numerical Methods for Fluid Dynamics e-bog
692,63 DKK
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In 1917, the British scientist L. F. Richardson made the first reported attempt to predict the weather by solving partial differential equations numerically, by hand! It is generally accepted that Richardson's work, though unsuccess- ful, marked the beginning of Computational Fluid Dynamics (CFD), a large branch of Scientific Computing today. His work had the four distinguishing characteristics...
E-bog
692,63 DKK
Forlag
Springer
Udgivet
17 april 2013
Genrer
Classical mechanics
Sprog
English
Format
pdf
Beskyttelse
LCP
ISBN
9783662034903
In 1917, the British scientist L. F. Richardson made the first reported attempt to predict the weather by solving partial differential equations numerically, by hand! It is generally accepted that Richardson's work, though unsuccess- ful, marked the beginning of Computational Fluid Dynamics (CFD), a large branch of Scientific Computing today. His work had the four distinguishing characteristics of CFD: a PRACTICAL PROBLEM to solve, a MATHEMATICAL MODEL to represent the problem in the form of a set of partial differen- tial equations, a NUMERICAL METHOD and a COMPUTER, human beings in Richardson's case. Eighty years on and these four elements remain the pillars of modern CFD. It is therefore not surprising that the generally accepted definition of CFD as the science of computing numerical solutions to Partial Differential or Integral Equations that are models for fluid flow phenomena, closely embodies Richardson's work. COMPUTERS have, since Richardson's era, developed to unprecedented levels and at an ever decreasing cost. PRACTICAL PROBLEMS to solved nu- merically have increased dramatically. In addition to the traditional demands from Meteorology, Oceanography, some branches of Physics and from a range of Engineering Disciplines, there are at present fresh demands from a dynamic and fast-moving manufacturing industry, whose traditional build-test-fix approach is rapidly being replaced by the use of quantitative methods, at all levels. The need for new materials and for decision-making under envi- ronmental constraints are increasing sources of demands for mathematical modelling, numerical algorithms and high-performance computing.