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Numerical Approximation of the Magnetoquasistatic Model with Uncertainties: Applications in Magnet Design (Softcover Reprint of the Original 1st 2016)

Numerical Approximation of the Magnetoquasistatic Model with Uncertainties

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"Numerical Approximation of the Magnetoquasistatic Model with Uncertainties" by Ulrich Römer is a astronomy book and space science reference focused on Cosmology. Best for students, researchers, and serious astronomy enthusiasts.

This book presents a comprehensive mathematical approach for solving stochastic magnetic field problems. It discusses variability in material properties and geometry, with an emphasis on the preservation of structural physical and mathematical properties. It especially addresses uncertainties in the computer simulation of magnetic fields originating from the manufacturing process. Uncertainties are quantified by approximating a stochastic reformulation of the governing partial differential equation, demonstrating how statistics of physical quantities of interest, such as Fourier harmonics in accelerator magnets, can be used to achieve robust designs. The book covers a number of key methods and results such as: a stochastic model of the geometry and material properties of magnetic devices based on measurement data; a detailed description of numerical algorithms based on sensitivities or on a higher-order collocation; an analysis of convergence and efficiency; and the application of the developed model and algorithms to uncertainty quantification in the complex magnet systems used in particle accelerators.

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Best For: Researchers and engineers working on magnetic field simulations and magnet design under uncertainty.
Focus: Mathematical and numerical methods for modeling and approximating stochastic magnetic field problems with variable material properties and geometry.
Covers: Stochastic modeling of geometry and materials, numerical algorithms for uncertainty quantification, convergence analysis, and applications to accelerator magnet systems.
Why It Matters: Provides tools to quantify and manage uncertainties in magnetic field simulations, supporting more reliable and robust magnet designs in particle accelerators and related technologies.

"Numerical Approximation of the Magnetoquasistatic Model with Uncertainties" by Ulrich Römer is a astronomy book and space science reference focused on Cosmology. Best for students, researchers, and serious astronomy enthusiasts.

Topic: Cosmology

Author: Ulrich Römer

Who this is for:

  • Astronomy students
  • Researchers and advanced hobbyists
  • Readers exploring space science topics

Why this book matters: It matters because it helps readers build a stronger understanding of astronomy concepts, observations, and scientific ideas related to space.

This book presents a comprehensive mathematical approach for solving stochastic magnetic field problems. It discusses variability in material properties and geometry, with an emphasis on the preservation of structural physical and mathematical properties. It especially addresses uncertainties in the computer simulation of magnetic fields originating from the manufacturing process. Uncertainties are quantified by approximating a stochastic reformulation of the governing partial differential equation, demonstrating how statistics of physical quantities of interest, such as Fourier harmonics in accelerator magnets, can be used to achieve robust designs. The book covers a number of key methods and results such as: a stochastic model of the geometry and material properties of magnetic devices based on measurement data; a detailed description of numerical algorithms based on sensitivities or on a higher-order collocation; an analysis of convergence and efficiency; and the application of the developed model and algorithms to uncertainty quantification in the complex magnet systems used in particle accelerators.

AuthorUlrich Römer
PublisherSpringer
Published2018-04-22
ISBN-139783319823164
BindingPaperback
Pages114
LanguageEnglish
SubjectsTechnology & Engineering
TopicCosmology
SeriesSpringer Theses

Format: Paperback

Length: 114 pages

Language: English

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