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Titlebook: Nanoelectronic Coupled Problems Solutions; E. Jan W. ter Maten,Hans-Georg Brachtendorf,Herber Book 2019 Springer Nature Switzerland AG 201

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Bond Wire Modelse bond wire properties, e.g., its time to failure. Secondly, a more accurate model using the finite integration technique for spatial discretisation is constructed. This model is also used to study the impact of manufacturing uncertainties, e.g., variable bond wire lengths, on the performance of bon
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Discretizationspproach. Furthermore the set up of coupled problems is addressed. Finally, it is shown that discretization requires a careful handling of the various terms in the discretization procedure, otherwise numerical unstable equations will appear.
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Automated Generation of Netlists from Electrothermal Field Modelsut of field models is presented. Such netlists can be used by standard circuit simulators. The field-to-netlist extraction is organised for coupled electrothermal field models. The resulting circuit model is an exact representation of the semi-discrete field model. A 3D electrothermal field model of
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Holistic / Monolithic Time Integrationtic field equations. We briefly summarize the modified nodal analysis for the lumped modeling of circuits. Then we discuss the coupling relations for including EM models into the circuit simulation systems and combine them with the spatially discretized Maxwell equations. Finally, we apply an adapti
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Non-Intrusive Methods for the Cosimulation of Coupled Problemses in space and time and different requirements on simulation accuracy and efficiency. In many cases, the coupling necessitates a decoupling of the time-stepping procedure, either because different software packages each have their own time stepper, or in order to improve the overall simulation effi
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Going from Parameter Estimation to Density Estimationlinear function of the input variables. Even for simple non-linear functional forms as quadratic polynomials this causes the variability to no longer be normally distributed. It is thus important to be able to estimate the probability distribution of the output. In this chapter we give a brief intro
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Parametric Model Order Reduction for Electro-Thermal Coupled Problemshow that the PMOR method based on multi-moment matching proposed in [2] can be applied to the discretized ET models. The error bound in [6] is used to check the accuracy of the reduced models. Based on the error bound, an adaptive algorithm for computing the reduced ET models is proposed in [7]. As
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