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Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis
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Simulation-Driven Modeling and Optimization - ASDOM, Reykjavik, August 2014 (Paperback, Softcover reprint of the original 1st ed. 2016)
Loot Price: R4,476
Discovery Miles 44 760
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Simulation-Driven Modeling and Optimization - ASDOM, Reykjavik, August 2014 (Paperback, Softcover reprint of the original 1st ed. 2016)
Series: Springer Proceedings in Mathematics & Statistics, 153
Expected to ship within 10 - 15 working days
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This edited volume is devoted to the now-ubiquitous use of
computational models across most disciplines of engineering and
science, led by a trio of world-renowned researchers in the field.
Focused on recent advances of modeling and optimization techniques
aimed at handling computationally-expensive engineering problems
involving simulation models, this book will be an invaluable
resource for specialists (engineers, researchers, graduate
students) working in areas as diverse as electrical engineering,
mechanical and structural engineering, civil engineering,
industrial engineering, hydrodynamics, aerospace engineering,
microwave and antenna engineering, ocean science and climate
modeling, and the automotive industry, where design processes are
heavily based on CPU-heavy computer simulations. Various
techniques, such as knowledge-based optimization, adjoint
sensitivity techniques, and fast replacement models (to name just a
few) are explored in-depth along with an array of the latest
techniques to optimize the efficiency of the simulation-driven
design process. High-fidelity simulation models allow for accurate
evaluations of the devices and systems, which is critical in the
design process, especially to avoid costly prototyping stages.
Despite this and other advantages, the use of simulation tools in
the design process is quite challenging due to associated high
computational cost. The steady increase of available computational
resources does not always translate into the shortening of the
design cycle because of the growing demand for higher accuracy and
necessity to simulate larger and more complex systems. For this
reason, automated simulation-driven design-while highly
desirable-is difficult when using conventional numerical
optimization routines which normally require a large number of
system simulations, each one already expensive.
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