Stochastic Tools in Turbulence

Stochastic Tools in Turbulence
Author: John L. Lumey
Publisher: Elsevier
Total Pages: 209
Release: 2012-12-02
Genre: Mathematics
ISBN: 0323162258

Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the characteristic function, and the Gaussian distribution from a more physical point of view. In considering fields, one must account for single-valued functions of one or more parameters, or collections of single-valued functions of one or more parameters such as time or space coordinates. The text also discusses multidimensional vector fields of finite energy, the characteristic eddies for a homogenous vector field, as well as, the distribution of solutions of an algebraic equation. Engineers, algebra students, and professors of statistics and advanced mathematics will find the book highly useful.

Stochastic Tools in Turbulence. Volume 12. Applied Mathematics and Mechanics

Stochastic Tools in Turbulence. Volume 12. Applied Mathematics and Mechanics
Author: John L. Lumley
Publisher:
Total Pages: 204
Release: 1970
Genre:
ISBN:

The monograph focuses on the mathematical tools available for describing and solving problems relating to stochastic vector fields. The book has applicability beyond problems relating to turbulence, although its orientation arises from these problems. The mathematical level rests between that customarily observed in books for physicists and that for mathematicians. The employment of generalized functions helps to resolve many of the mathematical questions in a relatively simple way. The extensive appendices on the subject, as well as on Fourier transforms, tensors, and invariant theory, are significant in making the book mathematically self-contained. (Author).

Stochastic Tools in Mathematics and Science

Stochastic Tools in Mathematics and Science
Author: Alexandre J. Chorin
Publisher: Springer Science & Business Media
Total Pages: 169
Release: 2009-07-24
Genre: Mathematics
ISBN: 1441910026

This introduction to probability-based modeling covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. Topics covered include conditional expectations, stochastic processes, Langevin equations, and Markov chain Monte Carlo algorithms. The applications include data assimilation, prediction from partial data, spectral analysis and turbulence. A special feature is the systematic analysis of memory effects.

Stochastic Methods in Fluid Mechanics

Stochastic Methods in Fluid Mechanics
Author: Sergio Chibbaro
Publisher: Springer Science & Business Media
Total Pages: 175
Release: 2013-09-05
Genre: Technology & Engineering
ISBN: 3709116228

Since their first introduction in natural sciences through the work of Einstein on Brownian motion in 1905 and further works, in particular by Langevin, Smoluchowski and others, stochastic processes have been used in several areas of science and technology. For example, they have been applied in chemical studies, or in fluid turbulence and for combustion and reactive flows. The articles in this book provide a general and unified framework in which stochastic processes are presented as modeling tools for various issues in engineering, physics and chemistry, with particular focus on fluid mechanics and notably dispersed two-phase flows. The aim is to develop what can referred to as stochastic modeling for a whole range of applications.

Stochastic Tools in Mathematics and Science

Stochastic Tools in Mathematics and Science
Author: Alexandre J Chorin
Publisher: Springer
Total Pages: 0
Release: 2010-11-16
Genre: Mathematics
ISBN: 9780387562834

This introduction to probability-based modeling covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. Topics covered include conditional expectations, stochastic processes, Langevin equations, and Markov chain Monte Carlo algorithms. The applications include data assimilation, prediction from partial data, spectral analysis and turbulence. A special feature is the systematic analysis of memory effects.

Turbulence

Turbulence
Author: Uriel Frisch
Publisher: Cambridge University Press
Total Pages: 314
Release: 1995-11-30
Genre: Science
ISBN: 9780521457132

This textbook presents a modern account of turbulence, one of the greatest challenges in physics. The state-of-the-art is put into historical perspective five centuries after the first studies of Leonardo and half a century after the first attempt by A.N. Kolmogorov to predict the properties of flow at very high Reynolds numbers. Such "fully developed turbulence" is ubiquitous in both cosmical and natural environments, in engineering applications and in everyday life. First, a qualitative introduction is given to bring out the need for a probabilistic description of what is in essence a deterministic system. Kolmogorov's 1941 theory is presented in a novel fashion with emphasis on symmetries (including scaling transformations) which are broken by the mechanisms producing the turbulence and restored by the chaotic character of the cascade to small scales. Considerable material is devoted to intermittency, the clumpiness of small-scale activity, which has led to the development of fractal and multifractal models. Such models, pioneered by B. Mandelbrot, have applications in numerous fields besides turbulence (diffusion limited aggregation, solid-earth geophysics, attractors of dynamical systems, etc). The final chapter contains an introduction to analytic theories of the sort pioneered by R. Kraichnan, to the modern theory of eddy transport and renormalization and to recent developments in the statistical theory of two-dimensional turbulence. The book concludes with a guide to further reading. The intended readership for the book ranges from first-year graduate students in mathematics, physics, astrophysics, geosciences and engineering, to professional scientists and engineers.

Stochastic Methods in Hydrology

Stochastic Methods in Hydrology
Author: Ole E. Barndorff-Nielsen
Publisher: World Scientific
Total Pages: 234
Release: 1998
Genre: Science
ISBN: 9789810233679

This book communicates some contemporary mathematical and statistical developments in river basin hydrology as they pertain to space-time rainfall, spatial landform and network structures and their role in understanding averages and fluctuations in the hydrologic water balance of river basins. While many of the mathematical and statistical nations have quite classical mathematical roots, the river basin data structure has led to many variations on the problems and theory.