Zhizhong Qiao

Mr. Zhizhong Qiao


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

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

Representative Publications

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4 September 2024 in Processes
Verified
Journal Article
Open access
PDF file
ZLZhen Li
Zhen Li
ZLZhao Lei
Zhao Lei
SXSheng Xu
Sheng Xu
SHSun Hengyang
Sun Hengyang
BLBin Li
Bin Li
ZQZhizhong Qiao
Zhizhong Qiao
Grey cast iron releases energy in the form of stress waves when damaged. To analyse the evolution of the physical and mechanical properties and acoustic emission characteristics of grey cast iron under uniaxial compression, acoustic emission signals were collected at different rates (0.5, 1, and 2 mm/s). Combined with load-time curves, damage modes were identified and classified using the parametric RA-AF correlation analysis method. The results indicate the loading rate effects on the strength, deformation, acoustic emission (AE), and energy evolution of grey cast iron specimens. The acoustic emission counts align with the engineering stress–strain response. To better illustrate the entire failure process of grey cast iron, from its internal microstructure to its macroscopic appearance, X-ray diffraction (XRD) and optical microscopy (OM) were employed for qualitative and quantitative analyses of the material’s internal microstructural characteristics. The equivalent crystal model of grey cast iron was constructed using a Particle Flow Software PFC2D 6.00.30 grain-based model (GBM) to simulate uniaxial compression acoustic emission tests. The calibration of fine parameters with indoor test results ensured good agreement with numerical simulation results. Acoustic emission dynamically monitors the compression process, while discrete element particle flow software further analyses the entire damage process from the inside to the outside. It provides a new research method and idea for the study of crack extension in some metal materials such as grey cast iron.