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Designs in nanoelectronics often lead to challenging simulation problems and include strong feedback couplings. Industry demands provisions for variability in order to guarantee quality and yield. It also requires the incorporation of higher abstraction levels to allow for system simulation in order to shorten the design cycles, while at the same time preserving accuracy. The methods developed here promote a methodology for circuit-and-system-level modelling and simulation based on best practice rules, which are used to deal with coupled electromagnetic field-circuit-heat problems, as well as coupled electro-thermal-stress problems that emerge in nanoelectronic designs. This book covers: (1) advanced monolithic/multirate/co-simulation techniques, which are combined with envelope/wavelet approaches to create efficient and robust simulation techniques for strongly coupled systems that exploit the different dynamics of sub-systems within multiphysics problems, and which allow designers to predict reliability and ageing; (2) new generalized techniques in Uncertainty Quantification (UQ) for coupled problems to include a variability capability such that robust design and optimization, worst case analysis, and yield estimation with tiny failure probabilities are possible (including large deviations like 6-sigma); (3) enhanced sparse, parametric Model Order Reduction techniques with a posteriori error estimation for coupled problems and for UQ to reduce the complexity of the sub-systems while ensuring that the operational and coupling parameters can still be varied and that the reduced models offer higher abstraction levels that can be efficiently simulated. All the new algorithms produced were implemented, transferred and tested by the EDA vendor MAGWEL. Validation was conducted on industrial designs provided by end-users from the semiconductor industry, who shared their feedback, contributed to the measurements, and supplied both material data and process data. In closing, a thorough comparison to measurements on real devices was made in order to demonstrate the algorithms’ industrial applicability.

Mathematical models. --- Mathematical optimization. --- Mathematical Modeling and Industrial Mathematics. --- Continuous Optimization. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Models, Mathematical --- Coupled problems (Complex systems) --- Nanoelectronics --- Mathematics. --- Nanoscale electronics --- Nanoscale molecular electronics --- Electronics --- Nanotechnology --- Coupled field problems (Complex systems) --- Problems, Coupled (Complex systems) --- Dynamics

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This PhD describes a novel working principle for small electromechanical machines. The goal of the novel working principle is to increase the efficiency of these small electromechanical machines. In traditional electromechanical machines, a rotating magnetic field is used which is generated by time-varying currents in a set of stator coils. The stator Joule losses are responsible for 50 % of all losses when the power output is smaller than 1 kW. Using a configuration combining permanent magnets and a composite of piezoelectric and magnetostrictive materials, the stator Joule losses are annihilated. The stator Joule losses are replaced with dielectric losses, but they take only 20 % of the input power. The composite of piezoelectric and magnetostrictive materials, forming the anisotropic controllable ferromagnetic composite, converts electrostatic energy into magnetic energy. The internal stress, obtained by the piezoelectric material, changes the magnetic behaviour of the anisotropic controllable ferromagnetic composite, giving it the function of a variable reluctance. Such variable reluctances combined with permanent magnets are implemented in a permanent magnet switched reluctance machine design, preferably an axial-flux machine. The novel working principle is demonstrated using a magneto-mechanical finite element solver. This magneto-mechanical finite element solver is built around the improved energy based material model. The magneto-mechanical finite element solver consists of two solvers: (i) the radially symmetric magnetic solver and (ii) the Cartesian structural mechanical solver. The exploitation of radial symmetry in a dedicated 2D FE solver is new. The extension to the radially symmetric magnetic solver and the energy based material model were crucial to simulate and study the novel working principle. Because the novel working principle is preferably implemented in an axial-flux machine, a radially symmetric 2D finite element solver is set up. The radial symmetry is non-standard, which requires the development of a set of dedicated shape functions. The requires shape function has a particular dependency on the radial coordinate in order to guarantee the partion-of-unity property, the consistency property and the convergence of the scheme. Such a dependency does not occur in the standard 2D Cartesian and the 2D axi-symmetric finite element solver. The novel working principle uses the magnetostrictive material properties to convert magnetic energy into mechanical energy. This requires a proper understanding and simulation of the magneto-elastic material behaviour, which requires a physical material model instead of a phenological material model. The multi-scale approach suggested by L. Daniel et. al., is followed, because it still relies on microscopic approaches, but with a lower computational cost. This material model uses the micromagnetic theory based on a statistical distribution, which results in the anhysteretic behaviour. During a three month research visit to the RWTH Aachen, the hysteresis effect influenced by the stress has been implemented in this material model by introducing a new energy function, which models the hysteretic effect. These achievements allowed the finite element simulation of the novel motor. The simulation confirms the initial assumptions and shows that the novel motor concept is a reliable alternative for small, traditional electric machines with stator coils. Moreover, the simulation shows that the performance of such a motor is comparable with a commercially available motor. This shows that the novel motor principle has a great potential.

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