zhenghai zhu

Prof. zhenghai zhu


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
18 November 2021 in New Journal of Chemistry
Verified
Journal Article
Closed access
PDF file
GYGuoliang Yin
Guoliang Yin
YJYulong Jia
Yulong Jia
YLYinhe Lin
Yinhe Lin
CZChenyang Zhang
Chenyang Zhang
ZZzhenghai zhu
zhenghai zhu
YMYing Ma
Ying Ma
This overview provides comprehensive understanding and development trends of hierarchical Bi 2 MoO 6 nanostructures as photocatalysts for efficient photocatalysis applications.

9 April 2018 in Acta Metallurgica Sinica (English Letters)
Verified
Journal Article
Closed access
PDF file
KZKe Zhang
Ke Zhang
HWHui Wang
Hui Wang
XSXinjun Sun
Xinjun Sun
FSFeng-Li Sui
Feng-Li Sui
ZLZhao-Dong Li
Zhao-Dong Li
QYQi-Long Yong
Qi-Long Yong

1 January 2022 in High Temperature Materials and Processes
Verified
Journal Article
Open access
PDF file
HFHe Fei
He Fei
CXChai Xianyi
Chai Xianyi
ZZzhenghai zhu
zhenghai zhu
In view of the characteristics of dynamic basic oxygen furnace (BOF) steelmaking process, prediction models based on backpropagation neural network and incremental learning (BPNN-IL) are proposed for total blow oxygen volume and second blow oxygen volume. The incremental learning is to adjust weights and thresholds of the BPNN according to the difference between the predicted value and actual value of each heat and to adapt to the change in furnace conditions. The combined BPNN-IL models are trained and tested by actual production data, and are further compared with multiple linear regression models and BPNN models. The results show that whether it is total blow oxygen volume or second blow oxygen volume, the BPNN-IL models could provide the most accurate prediction and the introduction of an incremental learning method could further improve the predictive accuracy. So the BPNN-IL method is effective in predicting the oxygen-blowing volume in the BOF steelmaking process.

22 February 2021 in Journal of Iron and Steel Research International
Verified
Journal Article
Closed access
PDF file
KZKe Zhang
Ke Zhang
XSXin-Jun Sun
Xin-Jun Sun
ZLZhao-Dong Li
Zhao-Dong Li
KXKun Xu
Kun Xu
TJTao Jia
Tao Jia
QYQi-Long Yong
Qi-Long Yong

29 August 2017 in Ironmaking & Steelmaking: Processes, Products and Applications
Verified
Journal Article
Closed access
HQHaitao Qian
Haitao Qian
FHFei HE
Fei HE
XXXi’aN Xie
Xi’aN Xie
ZZzhenghai zhu
zhenghai zhu
LZLingying Zhang
Lingying Zhang
JSJiashun Shi
Jiashun Shi
Sticking-type breakout is one of key factors which restrict the development of high-speed or wide-heavy plate continuous casting technology. In order to better heal and control the sticking-type breakout, this paper presents a comprehensive study for its recovery mechanism. First, according to force characteristics of solidified shell at mold exit, calculation method of safe shell thickness is proposed. Then, considering sticker propagation behaviour and safe shell thickness, a more practical recovery model of sticking-type breakout is established and verified by actual examples. The result shows the proposed recovery strategies avoid casting speed to be decreased too low or cast stop, thus save unnecessary operating time, and are better than original strategies. Furthermore, influencing factors of recovery behaviour are analyzed. The result shows hot spot location, operating casting speed, and mold oscillation frequency have a significant effect on minimum speed for the recovery and oscillation stoke has little influence on it.

18 February 2021 in Journal of Iron and Steel Research International
Verified
Journal Article
Closed access
PDF file
ZZzhenghai zhu
zhenghai zhu
LZLi Zhou
Li Zhou
FHFei HE
Fei HE
XSXiao-Fang Shi
Xiao-Fang Shi
LCLi-Zhong Chang
Li-Zhong Chang
HDHong-Biao Dong
Hong-Biao Dong