[HTML][HTML] Machine learning-powered performance monitoring of proton exchange membrane water electrolyzers for enhancing green hydrogen production as a …
Aviation is a major contributor to transportation carbon emissions but aims to reduce its
carbon footprint. Sustainable and environmentally friendly green hydrogen fuel is essential …
carbon footprint. Sustainable and environmentally friendly green hydrogen fuel is essential …
Artificial intelligence-driven model for resistive superconducting fault current limiter in future electric aircraft
D Yan, A Sadeghi, M Yazdani-Asrami… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Fast and accurate electrothermal characterization of superconducting fault current limiters
(SFCLs) is critically important for their performance evaluation. At the design stage of the …
(SFCLs) is critically important for their performance evaluation. At the design stage of the …
A comprehensive machine learning-based investigation for the index-value prediction of 2G HTS coated conductor tapes
Index-value, or so-called n-value prediction is of paramount importance for understanding
the superconductors' behaviour specially when modeling of superconductors is needed …
the superconductors' behaviour specially when modeling of superconductors is needed …
Estimation of magnetic levitation and lateral forces in MgB2 superconducting bulks with various dimensional sizes using artificial intelligence techniques
The advent of superconducting bulks, due to their compactness and performance, offers new
perspectives and opportunities in many applications and sectors, such as magnetic field …
perspectives and opportunities in many applications and sectors, such as magnetic field …
Design and Thermal Analysis of a 250 MVA HTS Transformer for Substation of Offshore Wind Farms
M Mahamed, S Seyyedbarzegar - Physica C: Superconductivity and its …, 2024 - Elsevier
Abstract In Offshore Substations (OSs), using High Temperature Superconducting (HTS)
transformers instead of conventional power transformers to reduce operational and …
transformers instead of conventional power transformers to reduce operational and …
[HTML][HTML] Enhancing the Predictive Modeling of n-Value Surfaces in Various High Temperature Superconducting Materials Using a Feed-Forward Deep Neural Network …
In this study, the prediction of n-value (index-value) surfaces—a key indicator of the field and
temperature dependence of critical current density in superconductors—across various high …
temperature dependence of critical current density in superconductors—across various high …