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Multiphase systems dominate nearly every area of science and technology, and the method of volume averaging provides a rigorous foundation for the analysis of these systems. The development is based on classical continuum physics, and it provides both the spatially smoothed equations and a method of predicting the effective transport coefficients that appear in those equations. The text is based on a ten-week graduate course that has been taught for more than 20 years at the University of California at Davis and at other universities around the world. Problems dealing with both the theoretical foundations and the applications are included with each chapter, and detailed solutions for all problems are available from the author. The course has attracted participants from chemical engineering, mechanical engineering, civil engineering, hydrologic science, mathematics, chemistry and physics.
This book deals with neutral particle flow in a stochastic mixture consisting of two or more immiscible fluids. After giving an introduction to linear kinetic theory and particle transport in a nonstochastic setting, it discusses recent formulations for particle flow through a background material whose properties are only known in a statistical sense. The mixing descriptions considered are both Markovian and renewal statistics. Various models and exact results are presented for the ensemble average of the intensity in such stochastic mixtures. In the Markovian case, the underlying kinetic description is the integro-differential transport equation, whereas for renewal statistics the natural starting point is the purely integral formulation of transport theory.
The heat equation can be derived by averaging over a very large number of particles. Traditionally, the resulting PDE is studied as a deterministic equation, an approach that has brought many significant results and a deep understanding of the equation and its solutions. By studying the heat equation and considering the individual random particles, however, one gains further intuition into the problem. While this is now standard for many researchers, this approach is generally not presented at the undergraduate level. In this book, Lawler introduces the heat equations and the closely related notion of harmonic functions from a probabilistic perspective. The theme of the first two chapters of the book is the relationship between random walks and the heat equation. This first chapter discusses the discrete case, random walk and the heat equation on the integer lattice; and the second chapter discusses the continuous case, Brownian motion and the usual heat equation. Relationships are shown between the two. For example, solving the heat equation in the discrete setting becomes a problem of diagonalization of symmetric matrices, which becomes a problem in Fourier series in the continuous case. Random walk and Brownian motion are introduced and developed from first principles. The latter two chapters discuss different topics: martingales and fractal dimension, with the chapters tied together by one example, a random Cantor set. The idea of this book is to merge probabilistic and deterministic approaches to heat flow. It is also intended as a bridge from undergraduate analysis to graduate and research perspectives. The book is suitable for advanced undergraduates, particularly those considering graduate work in mathematics or related areas.
Computational models are invaluable in understanding the complex effects of physical processes and environmental factors which interact to influence landform evolution of geologic time scales. This book provides a holistic guide to the construction of numerical models to explain the co-evolution of landforms, soil, vegetation and tectonics, and describes how the geomorphology observable today has been formed. It explains the science of the physical processes and the mechanics of how to solve them, providing a useful resource for graduates studying geomorphology and sedimentary and erosion processes. It also emphasises the methods for assessing the relative importance of different factors at field sites, enabling researchers to select the appropriate processes to model. Integrating a discussion of the fundamental processes with mathematical formulations, it guides the reader in understanding which processes are important and why; and creates a framework through which to study the interaction of soils, vegetation and landforms over time.