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This book presents a systematic methodology for the development of
parallel multi-physics models and its implementation in geophysical
and biomedical applications. The methodology includes conservative
discretization methods for partial differential equations on
general meshes, as well as data structures and algorithms for
organizing parallel simulations on general meshes. The structures
and algorithms form the core of the INMOST (Integrated Numerical
Modelling Object-oriented Supercomputing Technologies) platform for
the development of parallel models on general meshes. The authors
consider applications for addressing specific geophysical and
biomedical challenges, including radioactive contaminant
propagation with subsurface waters, reservoir simulation, and clot
formation in blood flows. The book gathers all the components of
this methodology, from algorithms and numerical methods to the
open-source software, as well as examples of practical
applications, in a single source, making it a valuable asset for
applied mathematicians, computer scientists, and engineers alike.
This book presents a systematic methodology for the development of
parallel multi-physics models and its implementation in geophysical
and biomedical applications. The methodology includes conservative
discretization methods for partial differential equations on
general meshes, as well as data structures and algorithms for
organizing parallel simulations on general meshes. The structures
and algorithms form the core of the INMOST (Integrated Numerical
Modelling Object-oriented Supercomputing Technologies) platform for
the development of parallel models on general meshes. The authors
consider applications for addressing specific geophysical and
biomedical challenges, including radioactive contaminant
propagation with subsurface waters, reservoir simulation, and clot
formation in blood flows. The book gathers all the components of
this methodology, from algorithms and numerical methods to the
open-source software, as well as examples of practical
applications, in a single source, making it a valuable asset for
applied mathematicians, computer scientists, and engineers alike.
This book provides an overview of current activities in the
fascinating area between computer science and sports, presenting
the state of the art in utilising the latest developments in
computer science to support sports coaches and athletes. It covers
a broad range of topics reflecting the diversity of this
interdisciplinary field, including concepts in informatics like
expert systems, modelling, simulation, machine learning, robotics,
and sensor integration. Further, it describes applications of
computer science in sports, such as alpine skiing, badminton,
football, rowing, and table tennis, as well as interesting
applications areas of sport like dementia, physiology, training,
and space flights. The appeals to informaticians interested in the
application field of sports as well as for sports scientists and
practitioners looking for advanced methods in their particular
sport.
Personalized Computational Hemodynamics: Models, Methods, and
Applications for Vascular Surgery and Antitumor Therapy offers
practices and advances surrounding the multiscale modeling of
hemodynamics and their personalization with conventional clinical
data. Focusing on three physiological disciplines, readers will
learn how to derive a suitable mathematical model and personalize
its parameters to account for pathologies and diseases. Written by
leading experts, this book mirrors the top trends in mathematical
modeling with clinical applications. In addition, the book features
the major results of the "Research group in simulation of blood
flow and vascular pathologies" at the Institute of Numerical
Mathematics of the Russian Academy of Sciences. Two important
features distinguish this book from other monographs on numerical
methods for biomedical applications. First, the variety of medical
disciplines targeted by the mathematical modeling and computer
simulations, including cardiology, vascular neurology and oncology.
Second, for all mathematical models, the authors consider
extensions and parameter tuning that account for vascular
pathologies.
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