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Summary  The temperature developed in bondwires of integrated circuits (ICs) is a possible source of malfunction and has to be taken into account during the design phase of an IC. Because of manufacturing tolerances, a bondwire's geometrical characteristics are uncertain parameters, and as such, their impact has to be examined with the use of uncertainty quantification methods. Considering a stochastic electrothermal problem featuring 12 bondwire‐related uncertainties, we want to quantify the impact of the uncertain inputs onto the temperature developed during the duty cycle of an IC. For this reason, we apply the stochastic collocation method on sparse grids, which is considered the current state‐of‐the‐art. We also implement an approach based on the recently introduced low‐rank tensor decompositions, in particular the tensor train decomposition, which in theory promises to break the curse of dimensionality. A comparison of both methods is presented, with respect to accuracy and computational effort.

international journal of numerical modelling: electronic networks, devices and fields

High‐dimensional uncertainty quantification for an electrothermal field problem using stochastic collocation on sparse grids and tensor train decompositions