Fusion-DeepONet data

This data has been used to generate all the results publihsed in our paper titled:"Fusion-DeepONet: A data-efficient neural operator for geometry-dependent hypersonic and supersonic flows."Published in the Journal of Computational Physics (2026). The DOI for the paper is: https://doi.org/10.1016/j.jcp.2025.114432

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-13
DOI
https://doi.org/10.5281/zenodo.17603114
Primary Topic
Model Reduction and Neural Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

Fusion-DeepONet data

Zenodo (CERN European Organization for Nuclear Research)
Model Reduction and Neural Networks
article

Fusion-DeepONet data

article en

Abstract

This data has been used to generate all the results publihsed in our paper titled:"Fusion-DeepONet: A data-efficient neural operator for geometry-dependent hypersonic and supersonic flows."Published in the Journal of Computational Physics (2026). The DOI for the paper is: https://doi.org/10.1016/j.jcp.2025.114432

Zenodo (CERN European Organization for Nuclear Research)
John Brown University (US)
Openalex Percentile: Top 43%
Model Reduction and Neural Networks
DOIOpen Access PDFOpenAlex
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Fusion-DeepONet data · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS