J.David Logan – författare
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2 produkter
2 produkter
Inbunden, Engelska, 2001
540 kr
Skickas inom 10-15 vardagar
This book develops the basic ideas of transport models in hydrogeology, including diffusion-dispersion processes, advection, and adsorption or reaction. While balancing the mathematical and physical concepts, it is written in a scientific pedagogical style that is accessible to graduate students and researchers in applied mathematics, the geosciences, civil engineering, and other environmental sciences. The book is organized into six chapters that focus on the diffusion equation, the transport of contaminants and other solutes through porous media, the existence of traveling wave fronts in such systems, filtration theory, the kinematics and dynamics of ground water transport, and the flow and reactions in permeable rocks.Analytic methods for both elementary linear and nonlinear partial differential equations are discussed in detail. Appendices develop numerical methods for partial differential equations, including the method of lines and finite difference methods, and numerical methods for inverting Laplace transforms. Exercises are interspersed throughout the book and over one hundred and twenty references are cited.The book serves as an excellent text or supplementary reading in courses in applied mathematics, contaminant hydrology, ground water modeling, or hydrogeology.
Del 15 - Interdisciplinary Applied Mathematics
Transport Modeling in Hydrogeochemical Systems
Häftad, Engelska, 2010
542 kr
Skickas inom 10-15 vardagar
The subject of this monograph lies in the joint areas of applied mathematics and hydrogeology. The goals are to introduce various mathematical techniques and ideas to applied scientists while at the same time to reveal to applied math ematicians an exciting catalog of interesting equations and examples, some of which have not undergone the rigors of mathematical analysis. Of course, there is a danger in a dual endeavor-the applied scientist may feel the mathematical models lack physical depth and the mathematician may think the mathematics is trivial. However, mathematical modeling has established itself firmly as a tool that can not only lead to greater understanding of the science, but can also be a catalyst for the advancement of science. I hope the presentation, written in the spirit of mathematical modeling, has a balance that bridges these two areas and spawns some cross-fertilization. Notwithstanding, the reader should fully understand the idea of a mathe matical model. In the world of reality we are often faced with describing and predicting the results of experiments. A mathematical model is a set of equa tions that encapsulates reality; it is a caricature of the real physical system that aids in our understanding of real phenomena. A good model extracts the essen tial features of the problem and lays out, in a simple manner, those processes and interactions that are important. By design, mathematical models should have predictive capability.