In top coal caving mining, the coal rock collapse will cause an irregular impact on the tail beam jack of the caving control mechanism. The severe impact will lead to jack failure. The bidirectional fluid-structure coupling model is built on Fluent and Mechanical software to study the impact response of the tail beam jack. The dynamic flow velocity streamlines, hydraulic pressure distribution, stress field, and strain field of the jack under impact load are extracted. The response characteristics of the jack in the stationary state and motion state are analyzed. The conclusions are as follows: the stress and strain of the rodless cavity are much larger than those of the rod cavity, which is more likely to be damaged. The hydraulic pressure in the jack cavity is in vertical layered distribution. The flow velocity streamlines present spiral shapes. The response degree of the hydraulic pressure signal in the rodless cavity is stronger than that in the rod cavity, and the response degree of the flow velocity signal in the rod cavity is stronger than that in the rodless cavity. The impact response of the jack in the motion state is more sensitive and stronger than that in the stationary state. The coal rock collapse situation can be most effectively identified only by comprehensively analyzing the rodless cavity's pressure signal and the rod cavity's velocity signal. This paper innovatively visualizes the flow velocity streamlines and pressure distribution together. The bidirectional fluid-structure coupling method is innovatively applied to the tail beam jack. The findings of this study can help for better understanding of the tail beam jack's structural design and failure prevention. This study provides a certain research basis for the intelligent coal rock identification technology in mining coal based on jack vibration signals.
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http://dx.doi.org/10.1021/acsomega.3c01303 | DOI Listing |
Acc Chem Res
January 2025
Laboratory for Chemistry and Life Science (CLS), Institute of Integrated Research, Institute of Science Tokyo, 4259 Nagatsuta, Midori-ku, Yokohama 226-8501, Japan.
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View Article and Find Full Text PDFSci Rep
January 2025
College of Intelligent Equipment, Shandong University of Science and Technology, Taian, 271000, Shandong, China.
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View Article and Find Full Text PDFSci Rep
December 2024
School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China.
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View Article and Find Full Text PDFSensors (Basel)
November 2024
Hubei Key Laboratory of Optical Information and Pattern Recognition, Wuhan Institute of Technology, Wuhan 430205, China.
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December 2024
College of Intelligent Equipment, Shandong University of Science and Technology, Taian, Shandong, 271000, China.
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