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This book deals with the application of spectral methods to
problems of uncertainty propagation and quanti?cation in
model-based computations. It speci?cally focuses on computational
and algorithmic features of these methods which are most useful in
dealing with models based on partial differential equations, with
special att- tion to models arising in simulations of ?uid ?ows.
Implementations are illustrated through applications to elementary
problems, as well as more elaborate examples selected from the
authors' interests in incompressible vortex-dominated ?ows and
compressible ?ows at low Mach numbers. Spectral stochastic methods
are probabilistic in nature, and are consequently rooted in the
rich mathematical foundation associated with probability and
measure spaces. Despite the authors' fascination with this
foundation, the discussion only - ludes to those theoretical
aspects needed to set the stage for subsequent applications. The
book is authored by practitioners, and is primarily intended for
researchers or graduate students in computational mathematics,
physics, or ?uid dynamics. The book assumes familiarity with
elementary methods for the numerical solution of time-dependent,
partial differential equations; prior experience with spectral me-
ods is naturally helpful though not essential. Full appreciation of
elaborate examples in computational ?uid dynamics (CFD) would
require familiarity with key, and in some cases delicate, features
of the associated numerical methods. Besides these shortcomings,
our aim is to treat algorithmic and computational aspects of
spectral stochastic methods with details suf?cient to address and
reconstruct all but those highly elaborate examples.
This book deals with the application of spectral methods to
problems of uncertainty propagation and quanti?cation in
model-based computations. It speci?cally focuses on computational
and algorithmic features of these methods which are most useful in
dealing with models based on partial differential equations, with
special att- tion to models arising in simulations of ?uid ?ows.
Implementations are illustrated through applications to elementary
problems, as well as more elaborate examples selected from the
authors' interests in incompressible vortex-dominated ?ows and
compressible ?ows at low Mach numbers. Spectral stochastic methods
are probabilistic in nature, and are consequently rooted in the
rich mathematical foundation associated with probability and
measure spaces. Despite the authors' fascination with this
foundation, the discussion only - ludes to those theoretical
aspects needed to set the stage for subsequent applications. The
book is authored by practitioners, and is primarily intended for
researchers or graduate students in computational mathematics,
physics, or ?uid dynamics. The book assumes familiarity with
elementary methods for the numerical solution of time-dependent,
partial differential equations; prior experience with spectral me-
ods is naturally helpful though not essential. Full appreciation of
elaborate examples in computational ?uid dynamics (CFD) would
require familiarity with key, and in some cases delicate, features
of the associated numerical methods. Besides these shortcomings,
our aim is to treat algorithmic and computational aspects of
spectral stochastic methods with details suf?cient to address and
reconstruct all but those highly elaborate examples.
This monograph provides in-depth analyses of vortex dominated flows
via matched and multiscale asymptotics, and demonstrates how
insight gained through these analyses can be exploited in the
construction of robust, efficient, and accurate numerical
techniques. The book explores the dynamics of slender vortex
filaments in detail, including fundamental derivations,
compressible core structure, weakly non-linear limit regimes, and
associated numerical methods. Similarly, the volume covers
asymptotic analysis and computational techniques for weakly
compressible flows involving vortex-generated sound and
thermoacoustics. The book is addressed to both graduate students
and researchers.
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