5 papers · 1 filter
Multivariate Sensitivity Analysis of Electric Machine Efficiency Maps and Profiles Under Design Uncertainty
Aylar Partovizadeh, Sebastian Schöps, Dimitrios Loukrezis
This work introduces the use of multivariate global sensitivity analysis for assessing the impact of uncertain electric machine design parameters on efficiency maps and profiles. C…
Maximum-Projection-Based Bayesian Optimization Utilizing Sensitivity Analysis for High-Efficiency Radial Turbine Design with Scarce Data
Eric Diehl, Adem Tosun, Dimitrios Loukrezis
We propose a data-efficient workflow to optimize the efficiency of a radial turbine design under a strict budget of high-fidelity computational fluid dynamics simulations. Assuming…
Multi-patch isogeometric neural solver for partial differential equations on computer-aided design domains
Moritz von Tresckow, Ion Gabriel Ion, Dimitrios Loukrezis
This work develops a computational framework that combines physics-informed neural networks with multi-patch isogeometric analysis to solve partial differential equations on comple…
Fourier-enhanced reduced-order surrogate modeling for uncertainty quantification in electric machine design
Aylar Partovizadeh, Sebastian Schöps, Dimitrios Loukrezis
This work proposes a data-driven surrogate modeling framework for cost-effectively inferring the torque of a permanent magnet synchronous machine under geometric design variations.…
Multivariate sensitivity-adaptive polynomial chaos expansion for high-dimensional surrogate modeling and uncertainty quantification
Dimitrios Loukrezis, Eric Diehl, Herbert De Gersem
This work develops a novel basis-adaptive method for constructing anisotropic polynomial chaos expansions of multidimensional (vector-valued, multi-output) model responses. The ada…