Print Email Facebook Twitter Using a Physics-Informed Neural Network to solve the Ideal Magnetohydrodynamic Equations Title Using a Physics-Informed Neural Network to solve the Ideal Magnetohydrodynamic Equations Author Bouma, Jort (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Applied Sciences) Contributor Möller, M. (mentor) Toshniwal, D. (mentor) Akhmerov, A.R. (mentor) Dubbeldam, J.L.A. (mentor) Kenjeres, S. (mentor) Degree granting institution Delft University of Technology Programme Applied Mathematics | Applied Physics Date 2020-08-28 Abstract In this work we investigate neural networks and subsequently physics-informed neural networks. Physicsinformed neural networks are away to solve physical models that are based on differential equations by using a neural network. The wave equation, Burgers’ equation, Euler’s equation, and the ideal magnetohydrodynamic equations are introduced and solved with physics-informed neural networks. The solutions to the first equations were captured well. The solution to the ideal magnetohydrodynamic equations contained some problems. These problems include transitions between different types of behaviour and exact values of constant sections. On the other hand, general shape and behaviour of the curve and locations of contact discontinuities were predicted well. Subject PINNsMHDNeural NetworksmagnetohydrodynamicFeed Forwardphysics-informed To reference this document use: http://resolver.tudelft.nl/uuid:96639fb6-0b15-4584-b019-74bd4257a9b9 Part of collection Student theses Document type bachelor thesis Rights © 2020 Jort Bouma Files PDF Bachelor_Thesis_Jort_Bouma.pdf 5.62 MB Close viewer /islandora/object/uuid:96639fb6-0b15-4584-b019-74bd4257a9b9/datastream/OBJ/view