Jin Xu

Mr. Jin Xu


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

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

Representative Publications

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26 July 2022 in Polymers
Verified
Journal Article
Open access
PDF file
QLQuanfeng Li
Quanfeng Li
Xiaodong JiXiaodong Ji
Xiaodong Ji
ZJZihao Jin
Zihao Jin
JXJin Xu
Jin Xu
SYShihan Yang
Shihan Yang
SLShumin Lv
Shumin Lv
As an ecological green building material, natural bamboo has many advantages such as a light weight, high strength, and short growth cycle. Natural bamboo is widely used in landscape architecture and fabricated structures. However, in bamboo building structures, the most common bolted joints often appear cleaved along the grain. In this paper, glass fiber-reinforced polymer (GFRP) is designed to wrap and improve the shear capacity of natural bamboo-bolt composite joints. According to the corresponding material parameters, the finite element model of composite joints is established, and the key influencing variables of the bearing capacity, namely the bolt diameter, bamboo tube outer diameter, and screw end distance, are analyzed. In addition, according to the European analytical yield model of bolted connections, the analytical calculation method of the bearing capacity is proposed and compared with the experimental and simulated values. The results showed that the numerical model and the modified analytical model can suitably describe the bearing capacity of composite joints, and a higher bolt diameter, along with the bamboo outer diameter, will lead to a higher ultimate load of the composite joints. Moreover, the bearing capacity of composite joints has no obvious relationship with the end spacing.

12 June 2024 in Applied Sciences
Verified
Journal Article
Open access
PDF file
JXJin Xu
Jin Xu
XXXinyue Xue
Xinyue Xue
BYBo Yang
Bo Yang
WWWen Wang
Wen Wang
WWWenxiang Wu
Wenxiang Wu
Xiaodong JiXiaodong Ji
Xiaodong Ji
As a frequent hazard, tropical cyclones have a great impact on the social and economic development of China, which is close to the origin of tropical cyclones in the western Pacific Ocean. The primary objective of this study was to construct a comprehensive risk assessment model for tropical cyclone hazards based on natural influencing factors, informing recommendations for hazard prevention and mitigation in affected regions. This research focused on tropical cyclones that made landfall in mainland China and Hainan from 1949 to 2023, utilizing hazard risk theory and classical extreme value theory. The wind speed and rainfall data during the peak cyclone periods (June to October) from 1997 to 2021 gathered from various meteorological stations, as well as altitude and vegetation cover data, were examined. Hierarchical analysis and ArcGIS spatial analysis methods were employed to study the characteristics of the spatiotemporal distribution of landfalling tropical cyclones and the comprehensive risk of tropical cyclone hazards, and the regions of China were delineated according to these methods. The results showed that, during the period from 1949 to 2023, the overall number of landfalling tropical cyclones decreased in a fluctuating manner, while the intensity of the cyclones increased. Furthermore, severe typhoons tended to occur more frequently in the summer than autumn with time, intensifying the challenge to resist short-term hazards. Moreover, the hazard-causing factors in areas affected by tropical cyclones displayed an increasing trend from north to south and from west to east. In detail, the regions sensitive to natural hazards were primarily located in the central part of Liaoning province, Tianjin, central and eastern Hebei province, Shandong province, eastern Henan province, central and northern Anhui province, Jiangsu province, and Shanghai, which are characterized by flat terrain and relatively low vegetation cover. Overall, the comprehensive risk of tropical cyclone hazards showed a geographical distribution that decreases from south to north and from east to west, with coastal cities in provinces such as Hainan, Guangdong, Guangxi, Fujian, and Zhejiang—including Haikou, Zhanjiang, Xiamen, Beihai, and Taizhou—exhibiting the highest levels of risk.