Proceedings of the 3rd International Conference Resources and Technology (RESAT 2025)

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Advanced Uncertainty Modeling to Enhance Resource Efficiency in High-Voltage Material Engineering

Authors
Daniel Fiss1, *, Stefan Kühnel2, Alexander Kratzsch1, Stefan Kornhuber2
1Institute of Process Technology, Process Automation and Measurement Technology (IPM), Zittau/Görlitz University of Applied Science, Zittau, 0273, Germany
2Faculty of Electrical Engineering and Informatics - Department for High-Voltage Engineering/Materials/Electromagnetic Theory, Zittau/Görlitz University of Applied Science, Zittau, 0273, Germany
*Corresponding author. Email: d.fiss@hszg.de
Corresponding Author
Daniel Fiss
Available Online 25 December 2025.
DOI
10.2991/978-94-6463-928-5_15How to use a DOI?
Keywords
Uncertainty analysis; Fuzzy set theory; Low current high-voltage arc (DC); Dynamic process modelling
Abstract

This study offers a comprehensive overview of a range of mathematical methods designed to address uncertainties in engineering calculations and assesses their suitability. The focus is on fuzzy set theory, which has proven to be particularly effective and offers a robust solution package for modelling and analyzing uncertainties. Additionally, a detailed model for analyzing the dynamic behavior of the surface temperature of insulating materials under high-voltage arcs is presented, systematically incorporating uncertainties and imprecision. The model is divided into three sub-models: a current-voltage model, a three-cylinder model, and a temperature-heat model. Through Monte Carlo simulations and correlation analyses, the key influencing parameters on surface temperature were identified, with material and heat transfer properties being recognized as particularly significant. The model was validated through cooling experiments by observing the cooldown process after heating, which showed a high degree of agreement with the simulation results. The application of fuzzy set theory for modelling uncertain parameters enabled precise consideration of uncertainties, making the model a reliable basis for predicting surface temperature under various test conditions and for better understanding the behavior of insulating materials under low current high-voltage arcs (DC).

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference Resources and Technology (RESAT 2025)
Series
Advances in Engineering Research
Publication Date
25 December 2025
ISBN
978-94-6463-928-5
ISSN
2352-5401
DOI
10.2991/978-94-6463-928-5_15How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Daniel Fiss
AU  - Stefan Kühnel
AU  - Alexander Kratzsch
AU  - Stefan Kornhuber
PY  - 2025
DA  - 2025/12/25
TI  - Advanced Uncertainty Modeling to Enhance Resource Efficiency in High-Voltage Material Engineering
BT  - Proceedings of the 3rd International Conference Resources and Technology (RESAT 2025)
PB  - Atlantis Press
SP  - 186
EP  - 212
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-928-5_15
DO  - 10.2991/978-94-6463-928-5_15
ID  - Fiss2025
ER  -