Pollutant Dispersion Prediction in Airports
A Lagrangian Stochastic Modeling (LSM) Approach
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This book is wholly based on the doctoral researchconducted by the author at Stanford University underthe guidance of Prof. Paul Durbin. Air pollution isone of the challenges faced by mankind today. Thereis a growing demand for accurate and efficientpredictive tools in the atmospheric and environmentalsciences. Modeling and simulation of dispersion ofpollutants in the atmosphere have interestedenvironmental scientists and meteorologists fordecades. However, the currently availabletechnologies that are sufficiently accurate arecomputationally expensive and not practicallyfeasible for many real ...
This book is wholly based on the doctoral research
conducted by the author at Stanford University under
the guidance of Prof. Paul Durbin. Air pollution is
one of the challenges faced by mankind today. There
is a growing demand for accurate and efficient
predictive tools in the atmospheric and environmental
sciences. Modeling and simulation of dispersion of
pollutants in the atmosphere have interested
environmental scientists and meteorologists for
decades. However, the currently available
technologies that are sufficiently accurate are
computationally expensive and not practically
feasible for many real life problems. This book is an
attempt to address that need. The science behind the
Lagrangian stochastic models (LSM's) is explored in
that regard and a new technique for constructing
LSM's by incorporating second moment closure
turbulence modeling theory is formulated. The
technology of applying this LSM for practical use in
an airport environment is demonstrated. Both
researchers and engineers in the stochastic
turbulence modeling community and the environmental
sciences will find direct relevance of the book in
their work.
conducted by the author at Stanford University under
the guidance of Prof. Paul Durbin. Air pollution is
one of the challenges faced by mankind today. There
is a growing demand for accurate and efficient
predictive tools in the atmospheric and environmental
sciences. Modeling and simulation of dispersion of
pollutants in the atmosphere have interested
environmental scientists and meteorologists for
decades. However, the currently available
technologies that are sufficiently accurate are
computationally expensive and not practically
feasible for many real life problems. This book is an
attempt to address that need. The science behind the
Lagrangian stochastic models (LSM's) is explored in
that regard and a new technique for constructing
LSM's by incorporating second moment closure
turbulence modeling theory is formulated. The
technology of applying this LSM for practical use in
an airport environment is demonstrated. Both
researchers and engineers in the stochastic
turbulence modeling community and the environmental
sciences will find direct relevance of the book in
their work.
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