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This book presents methodologies for analysing large data sets
produced by the direct numerical simulation (DNS) of turbulence and
combustion. It describes the development of models that can be used
to analyse large eddy simulations, and highlights both the most
common techniques and newly emerging ones. The chapters, written by
internationally respected experts, invite readers to consider DNS
of turbulence and combustion from a formal, data-driven standpoint,
rather than one led by experience and intuition. This perspective
allows readers to recognise the shortcomings of existing models,
with the ultimate goal of quantifying and reducing model-based
uncertainty. In addition, recent advances in machine learning and
statistical inferences offer new insights on the interpretation of
DNS data. The book will especially benefit graduate-level students
and researchers in mechanical and aerospace engineering, e.g. those
with an interest in general fluid mechanics, applied mathematics,
and the environmental and atmospheric sciences.
This book presents methodologies for analysing large data sets
produced by the direct numerical simulation (DNS) of turbulence and
combustion. It describes the development of models that can be used
to analyse large eddy simulations, and highlights both the most
common techniques and newly emerging ones. The chapters, written by
internationally respected experts, invite readers to consider DNS
of turbulence and combustion from a formal, data-driven standpoint,
rather than one led by experience and intuition. This perspective
allows readers to recognise the shortcomings of existing models,
with the ultimate goal of quantifying and reducing model-based
uncertainty. In addition, recent advances in machine learning and
statistical inferences offer new insights on the interpretation of
DNS data. The book will especially benefit graduate-level students
and researchers in mechanical and aerospace engineering, e.g. those
with an interest in general fluid mechanics, applied mathematics,
and the environmental and atmospheric sciences.
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