102 citations · 718 across the 60 of their papers we have counts for
63 papers
Fast Uncertainty Quantification of Spent Nuclear Fuel with Neural Networks
Arnau Albà, Andreas Adelmann, Lucas Münster +2
The accurate calculation and uncertainty quantification of the characteristics of spent nuclear fuel (SNF) play a crucial role in ensuring the safety, efficiency, and sustainabilit…
JulianA: An automatic treatment planning platform for intensity-modulated proton therapy and its application to intra- and extracerebral neoplasms
Renato Bellotti, Jonas Willmann, Antony J. Lomax +3
Creating high quality treatment plans is crucial for a successful radiotherapy treatment. However, it demands substantial effort and special training for dosimetrists. Existing aut…
Forecasting Particle Accelerator Interruptions Using Logistic LASSO Regression
Sichen Li, Jochem Snuverink, Fernando Perez-Cruz +1
Unforeseen particle accelerator interruptions, also known as interlocks, lead to abrupt operational changes despite being necessary safety measures. These may result in substantial…
Computational Models for High-Power Cyclotrons and FFAs
Andreas Adelmann, Chris T. Rogers
A summary of numerical modeling capabilities regarding high power cyclotrons and fixed field alternating gradient machines is presented. This paper focuses on techniques made avail…
Lasso Monte Carlo, a Variation on Multi Fidelity Methods for High Dimensional Uncertainty Quantification
Arnau Albà, Romana Boiger, Dimitri Rochman +1
Uncertainty quantification (UQ) is an active area of research, and an essential technique used in all fields of science and engineering. The most common methods for UQ are Monte Ca…
Review of Time Series Forecasting Methods and Their Applications to Particle Accelerators
Sichen Li, Andreas Adelmann
Particle accelerators are complex facilities that produce large amounts of structured data and have clear optimization goals as well as precisely defined control requirements. As s…