Chenchen Kang
11 Papers
5 Citations
Chenchen Kang is an academic researcher. The author has contributed to research in topics: Computer science & Tribology. The author has an hindex of 1, co-authored 1 publications.
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Papers
PCD after cobalt leaching reinforced by high temperature annealing: Tribological properties and graphitization evolution
Ru Yi Gou,Xun Luo,Kunyao Li,Chenchen Kang +3 more
TL;DR: In this article , an annealing experiment was conducted in a box-type resistance furnace, and the polycrystalline diamond was studied by X-ray diffraction, scanning electron microscopy, energy-dispersive spectrometry, and Raman spectroscopy.
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Study on the tribological properties of diamond and SiC interactions using atomic scale numerical simulations
TL;DR: In this article , the tribological properties between diamond and SiC balls were investigated at three different temperatures, and the simulation findings demonstrated that the diamond's wear ratio was increasing with the increase in temperature.
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Ground-Based Thermal Imaging for Assessing Crop Water Status in Grapevines over a Growing Season
Zheng Zhou,Geraldine Diverres,Chenchen Kang,Sushma Thapa,Manoj Karkee,Qin Zhang,Markus Keller +6 more
TL;DR: In this paper , a robust strategy to assess crop water status in grapevines is proposed, where a custom-developed algorithm was created to automatically derive canopy temperature (Tc) and calculate crop water stress index (CWSI) from the acquired thermal-RGB images.
High-temperature annealing of polycrystalline diamond compact with cobalt removal and evolution of tribological properties of grinding balls
Xun Luo,Ru Yi Gou,Kunyao Li,Chenchen Kang,Jian Chen,Gui Rong Kang +5 more
TL;DR: In this paper , a friction experiment was carried out after the high-temperature annealing of polycrystalline diamond compact (PDC) with cobalt removal and unused grinding balls.
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Decision-support system for precision regulated deficit irrigation management for wine grapes
TL;DR: In this article , a decision support system for managing precision RDI in vineyards is presented, consisting of a soil moisture prediction model and an RDI scheduling model developed based on artificial neural networks (ANN).
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