Design and Uncertainty Analysis of an AC Loss Measuring Instrument for Superconducting Magnets

A novel instrument was designed and numerically validated for measuring AC losses in ramped superconducting magnets. These power losses are expected to be in the 1 W to 100 W range. The instrument improves metrological performance compared to existing instruments by reaching a target power loss uncertainty in the order of 0.1 watt. This allows accurate measurement of the power losses to improve magnet modeling. A Monte Carlo analysis is used to evaluate the measurement uncertainty. Such an analysis addresses the lack of uncertainty investigation in the literature for this kind of measurement, and the proposed approach can be applied to various magnet models. The physical design of the instrument is carried out by relying on an FPGA-based acquisition platform. Results on a representative case study reveal that the target uncertainty can be reached without any compensation or correction mechanism. Instead, when aiming to use compensation or correction of the inductive magnet voltage, the sensitivity analysis points out that offset errors and time delays must be limited. This also suggests that the magnet’s inductance estimation should be improved more than the metrological performance of the instrumentation.

Authors

Institutions

Publication Details

Journal
Instruments
Published
2025-04-08
DOI
https://doi.org/10.3390/instruments9020008
Primary Topic
Superconducting Materials and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design and Uncertainty Analysis of an AC Loss Measuring Instrument for Superconducting Magnets

Pedro M. Ramos, Antonio Espósito, E. De Matteis, Pasquale Arpaïa et al.
Instruments
Superconducting Materials and Applications
article

Design and Uncertainty Analysis of an AC Loss Measuring Instrument for Superconducting Magnets

Pedro M. Ramos, Antonio Espósito, E. De Matteis, Pasquale Arpaïa, Davide Cuneo
article en

Abstract

A novel instrument was designed and numerically validated for measuring AC losses in ramped superconducting magnets. These power losses are expected to be in the 1 W to 100 W range. The instrument improves metrological performance compared to existing instruments by reaching a target power loss uncertainty in the order of 0.1 watt. This allows accurate measurement of the power losses to improve magnet modeling. A Monte Carlo analysis is used to evaluate the measurement uncertainty. Such an analysis addresses the lack of uncertainty investigation in the literature for this kind of measurement, and the proposed approach can be applied to various magnet models. The physical design of the instrument is carried out by relying on an FPGA-based acquisition platform. Results on a representative case study reveal that the target uncertainty can be reached without any compensation or correction mechanism. Instead, when aiming to use compensation or correction of the inductive magnet voltage, the sensitivity analysis points out that offset errors and time delays must be limited. This also suggests that the magnet’s inductance estimation should be improved more than the metrological performance of the instrumentation.

InstrumentsVol. 9(2)
University of Lisbon (PT), Lawrence Berkeley National Laboratory (US), Istituto Nazionale di Fisica Nucleare, Sezione di Napoli (IT), Instituto de Telecomunicações (PT), Istituto Nazionale di Fisica Nucleare, Laboratori Acceleratori e Superconduttività Applicata (IT), University of Naples Federico II (IT)
Openalex Percentile: Top 93%
Superconducting Materials and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.