Reduced Order Approaches for Micromagnetics
Reduced Order Approaches for Micromagnetics
Disciplines
Mathematics (50%); Physics, Astronomy (50%)
Keywords
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Micromagnetics,
Low-rank tensor numerical methods,
Computer simulation,
Finite difference micromagnetics,
Permanent magnets,
Model order reduction
Computational micromagnetics is a discipline which describes and calculates magnetic phenomenons on nano- to micrometer scales using both classical and quantum physics. It emerged from applications like magnetic recording and magnetic material design and is nowadays a booster for the design of rare earth reduced high-performance magnets for green energy applications for electric/hybrid vehicles and electric wind and hydro-power generation. Among many others, further applications are random access memory, magnetic sensors and nanomagnetic materials and devices. However, the computer simulations which are used for the design of these applications encounter computational limits since the interplay of phenomenons of rather large length scales (classical electromagnetism) and very small (quantum physics) need both to be taken into account. This exceeds the available computational resources very easily. The project Reduced Order Approaches for Micromagnetics aims at providing applied physicists, theorists and engineers with novel and feasible mathematical tools for their materials and design simulations. The approaches concentrate on ways to reduce the complexity by underlying simplified (numerical) models, such as tensor product approaches, which reduce the dimensionality but still catch the essence. A main objective is the development of computer simulation methods which track the time-dependent change of magnetic states in materials of several microns in size, a task which is definitely not possible for conventional methods nowadays. The project is an example for enhancement of a discipline of computational science by innovative theoretical models and practical numerical methods and is directly linked and useful for applications in engineering.
- Wolfgang Pauli Institut - 100%
- Hossein Sepehri-Amin, The University of Tsukuba - Belgium
- Vitaliy Lomakin, University of California San Diego - USA
Research Output
- 239 Citations
- 25 Publications
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2024
Title Constraint free physics-informed machine learning for micromagnetic energy minimization DOI 10.1016/j.cpc.2024.109202 Type Journal Article Author Exl L Journal Computer Physics Communications -
2024
Title Image-based prediction and optimization of hysteresis properties of nanocrystalline permanent magnets using deep learning DOI 10.1016/j.jmmm.2024.171937 Type Journal Article Author Exl L Journal Journal of Magnetism and Magnetic Materials -
2020
Title Learning time-stepping by nonlinear dimensionality reduction to predict magnetization dynamics DOI 10.1016/j.cnsns.2020.105205 Type Journal Article Author Exl L Journal Communications in Nonlinear Science and Numerical Simulation Pages 105205 Link Publication -
2021
Title Machine learning methods for the prediction of micromagnetic magnetization dynamics Type Other Author Schaffer S -
2023
Title Numerical methods and machine learning in computational micromagnetism Type Other Author Exl L -
2018
Title Searching the weakest link: Demagnetizing fields and magnetization reversal in permanent magnets DOI 10.1016/j.scriptamat.2017.11.020 Type Journal Article Author Fischbacher J Journal Scripta Materialia Pages 253-258 Link Publication -
2018
Title Micromagnetics of rare-earth efficient permanent magnets DOI 10.1088/1361-6463/aab7d1 Type Journal Article Author Fischbacher J Journal Journal of Physics D: Applied Physics Pages 193002 Link Publication -
2018
Title Many-body physics in two-component Bose–Einstein condensates in a cavity: fragmented superradiance and polarization DOI 10.1088/1367-2630/aabc3a Type Journal Article Author Lode A Journal New Journal of Physics Pages 055006 Link Publication -
2018
Title A magnetostatic energy formula arising from the L 2-orthogonal decomposition of the stray field DOI 10.1016/j.jmaa.2018.07.018 Type Journal Article Author Exl L Journal Journal of Mathematical Analysis and Applications Pages 230-237 Link Publication -
2022
Title Conditional physics informed neural networks DOI 10.1016/j.cnsns.2021.106041 Type Journal Article Author Kovacs A Journal Communications in Nonlinear Science and Numerical Simulation Pages 106041 Link Publication -
2021
Title Micromagnetism DOI 10.1007/978-3-030-63210-6_7 Type Book Chapter Author Exl L Publisher Springer Nature Pages 347-390 -
2022
Title Magnetostatics and micromagnetics with physics informed neural networks DOI 10.1016/j.jmmm.2021.168951 Type Journal Article Author Kovacs A Journal Journal of Magnetism and Magnetic Materials Pages 168951 Link Publication -
2022
Title Bridging Fidelities to Predict Nanoindentation Tip Radii Using Interpretable Deep Learning Models DOI 10.1007/s11837-022-05233-z Type Journal Article Author Trost C Journal JOM Pages 2195-2205 Link Publication -
2021
Title Micromagnetism DOI 10.1007/978-3-030-63101-7_7-1 Type Book Chapter Author Exl L Publisher Springer Nature Pages 1-44 -
2021
Title Machine Learning Methods for the Prediction of Micromagnetic Magnetization Dynamics DOI 10.1109/tmag.2021.3095251 Type Journal Article Author Schaffer S Journal IEEE Transactions on Magnetics Pages 1-6 Link Publication -
2021
Title Prediction of magnetization dynamics in a reduced dimensional feature space setting utilizing a low-rank kernel method DOI 10.1016/j.jcp.2021.110586 Type Journal Article Author Exl L Journal Journal of Computational Physics Pages 110586 Link Publication -
2022
Title Unconditional well-posedness and IMEX improvement of a family of predictor-corrector methods in micromagnetics DOI 10.1016/j.apnum.2022.05.008 Type Journal Article Author Mauser N Journal Applied Numerical Mathematics Pages 33-54 Link Publication -
2023
Title Physics-informed machine learning and stray field computation with application to micromagnetic energy minimization DOI 10.1016/j.jmmm.2023.170761 Type Journal Article Author Schaffer S Journal Journal of Magnetism and Magnetic Materials Pages 170761 Link Publication -
2019
Title Preconditioned nonlinear conjugate gradient method for micromagnetic energy minimization DOI 10.1016/j.cpc.2018.09.004 Type Journal Article Author Exl L Journal Computer Physics Communications Pages 179-186 Link Publication -
2018
Title Magnetic microstructure machine learning analysis DOI 10.1088/2515-7639/aaf26d Type Journal Article Author Exl L Journal Journal of Physics: Materials Link Publication -
2019
Title An optimization approach for dynamical Tucker tensor approximation DOI 10.1016/j.rinam.2019.100002 Type Journal Article Author Exl L Journal Results in Applied Mathematics Pages 100002 Link Publication -
2019
Title Exploring Many-Body Physics with Bose-Einstein Condensates DOI 10.1007/978-3-030-13325-2_6 Type Book Chapter Author Alon O Publisher Springer Nature Pages 89-110 -
2019
Title Optimal control of the self-bound dipolar droplet formation process DOI 10.1016/j.cpc.2019.06.002 Type Journal Article Author Mennemann J Journal Computer Physics Communications Pages 205-216 Link Publication -
2019
Title Learning magnetization dynamics DOI 10.1016/j.jmmm.2019.165548 Type Journal Article Author Kovacs A Journal Journal of Magnetism and Magnetic Materials Pages 165548 Link Publication -
2020
Title Computational micromagnetics with Commics DOI 10.1016/j.cpc.2019.106965 Type Journal Article Author Pfeiler C Journal Computer Physics Communications Pages 106965 Link Publication