Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Tianzi Shi"'
Publikováno v:
Frontiers in Energy Research, Vol 11 (2023)
A deep learning-based multi-node framework is constructed in this work to provide a data-driven platform that provides predictions for the operation condition of the primary heat transfer (PHT) loop in nuclear power plants (NPPs). Several deep learni
Externí odkaz:
https://doaj.org/article/67fac3f6e8764cffac34f3442bad9209
Publikováno v:
Frontiers in Earth Science, Vol 10 (2022)
In this paper, the adaptability characteristics of the packer to three types of common clastic rock reservoirs (mudstone, shale, sandstone) are analyzed systematically. Moreover, the identification and structural design of the packer in hydraulic fra
Externí odkaz:
https://doaj.org/article/7d214699a5c644babad7e9e7fe495e17
Publikováno v:
Frontiers in Energy Research, Vol 9 (2021)
A combination of Convolutional Neural Network (CNN), Long-Short Term Memory (LSTM), and Convolutional LSTM (ConvLSTM) is constructed in this work for the fault diagnosis and post-accident prediction for Loss of Coolant Accidents (LOCAs) in Nuclear Po
Externí odkaz:
https://doaj.org/article/af3d6f557ebd488dad20438cc61a6c1a
Autor:
Yang Li, Dan Zhang, Tianzi Shi, Yulin Yu, Yinmei Tian, Qi Xie, Jingyu Shi, Li Kong, Conglian Yang, Zhiping Zhang
Publikováno v:
Nano Research. 16:5279-5291
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75ee9db67c9537ee72cd201a1c647229
https://doi.org/10.1007/s12274-022-5199-0
https://doi.org/10.1007/s12274-022-5199-0
Publikováno v:
2021 International Conference on Computational Science and Computational Intelligence (CSCI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed9bd448d6507bcab07966a99d61246b
https://doi.org/10.1109/csci54926.2021.00032
https://doi.org/10.1109/csci54926.2021.00032
Publikováno v:
Fresenius Environmental Bulletin. Dec2022, Vol. 31 Issue 12, p11736-11744. 9p.
Publikováno v:
Frontiers in Energy Research, Vol 9 (2021)
A combination of Convolutional Neural Network (CNN), Long-Short Term Memory (LSTM), and Convolutional LSTM (ConvLSTM) is constructed in this work for the fault diagnosis and post-accident prediction for Loss of Coolant Accidents (LOCAs) in Nuclear Po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9455939e69616fe5b649c2d5e0126fb5
https://www.frontiersin.org/articles/10.3389/fenrg.2021.665262/full
https://www.frontiersin.org/articles/10.3389/fenrg.2021.665262/full