Abstract
Using a cyclotron-based model problem, we demonstrate for the first time the applicability and usefulness of an uncertainty quantification (UQ) approach in order to construct surrogate models. The ...
Highlights
Uncertainty quantification (UQ) describes the origin, propagation, and interplay of different sources of uncertainties in the analysis and behavioral prediction of generally complex and high-dimensional systems, such as particle accelerators
The application of charged particle accelerators ranges from material science to biology to fundamental physics questions, currently addressed, for example, with the LHC or in the future maybe with experiments like DAEδALUS/Isotope Decay-At-Rest experiment (IsoDAR) [40, 25]
A particular, but complex, example in the form of a high-intensity cyclotron was used to demonstrate the usefulness of the surrogate model as well as the global sensitivity analysis via computing the total Sobol’ indices
Summary
Uncertainty quantification (UQ) describes the origin, propagation, and interplay of different sources of uncertainties in the analysis and behavioral prediction of generally complex and high-dimensional systems, such as particle accelerators. Particle accelerators, polynomial chaos, surrogate model, sensitivity analysis, UQTk
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