Weijie Chen

Mr. Weijie Chen

Changsha University of Science & Technology

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

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

Representative Publications

View All Publications
18 January 2021 in Sensors
Verified
Journal Article
Open access
PDF file
WCWeijie Chen
Weijie Chen
YZYou Zhou
You Zhou
EZEnze Zhou
Enze Zhou
ZXZhun Xiang
Zhun Xiang
WZWentao Zhou
Wentao Zhou
JLJunhan Lu
Junhan Lu
Considering the complexity of the physical model of wildfire occurrence, this paper develops a method to evaluate the wildfire risk of transmission-line corridors based on Naïve Bayes Network (NBN). First, the data of 14 wildfire-related factors including anthropogenic, physiographic, and meteorologic factors, were collected and analyzed. Then, the relief algorithm is used to rank the importance of factors according to their impacts on wildfire occurrence. After eliminating the least important factors in turn, an optimal wildfire risk assessment model for transmission-line corridors was constructed based on the NBN. Finally, this model was carried out and visualized in Guangxi province in southern China. Then a cost function was proposed to further verify the applicability of the wildfire risk distribution map. The fire events monitored by satellites during the first season in 2020 shows that 81.8% of fires fall in high- and very-high-risk regions.

17 April 2019 in Nanomaterials
Verified
Journal Article
Open access
PDF file
ZWZiyi Wang
Ziyi Wang
YZYou Zhou
You Zhou
WLWu Lu
Wu Lu
NPNeng Peng
Neng Peng
WCWeijie Chen
Weijie Chen
The insulation of mineral oil-based nanofluids was found to vary with different concentration level of nanoparticles. However, the mechanisms behind this research finding are not well studied. In this paper, mineral oil-based nanofluids were prepared by suspending TiO2 nanoparticles with weight percentages ranging from 0.0057% to 0.0681%. The breakdown voltage and chop time of nanofluids were observed under standard lightning impulse waveform. The experimental results show that the presence of TiO2 nanoparticles increases the breakdown voltage of mineral oil under positive polarity. The enhancement of breakdown strength tends to saturate when the concentration of nanoparticle exceeds 0.0227 wt%. Electronic traps formed at the interfacial region of nanoparticles, which could capture fast electrons in bulk oil and reduce the net density of space charge in front of prebreakdown streamers, are responsible for the breakdown strength enhancement. When the particle concentration level is higher, the overlap of Gouy–Chapman diffusion layers results in the saturation of trap density in nanofluids. Consequently, the breakdown strength of nanofluids is saturated. Under negative polarity, the electrons are likely to be scattered by the nanoparticles on the way towards the anode, resulting in enhanced electric fields near the streamer tip and the decrement of breakdown voltage.