Yibo Ouyang

Dr. Yibo Ouyang


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

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

Representative Publications

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10 November 2022 in Scientific Reports
Verified
Journal Article
Open access
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LZLei Zhu
Lei Zhu
YOYibo Ouyang
Yibo Ouyang
FQFengqi Qiu
Fengqi Qiu
YOYibo Ouyang
Yibo Ouyang
To quantify the diffusion range of slurry in grouting engineering, an active heating optical fiber (AHFO) monitoring method is proposed. The AHFO is arranged on the coal seam floor. The temperature is taken as the monitoring parameter to monitor the diffusion range and state of slurry in the injected medium. Considering the time-varying characteristics of slurry rheological parameters, the theoretical calculation formula of spherical diffusion radius based on the power-law fluid is deduced. The relationship between the void ratio and grouting diffusion radius is discussed. Considering the influence of the seepage effect, the "water cement ratio change matrix" in the process of mud seepage is derived, and the influence of the space–time change of the slurry water cement ratio on the temperature gradient of the injected medium is studied. According to the factors affecting grouting diffusion, four groups of small three-dimensional simulation tests and one large three-dimensional grouting test are designed to verify the feasibility of the proposed method. The results show that the relative error of the AHFO monitoring radius is between 3.00 and 14.67%, based on the actual diffusion radius. In the large-scale three-dimensional grouting test, the data from AHFO is used to generate the two-dimensional surface of the grouting diffusion form, and the grouting diffusion range is asymmetric oval. Compared with the theoretical calculation results, the maximum relative error of grouting diffusion radius is 9.6%, and AHFO shows prediction accuracy. With the decrease in the water-cement ratio of slurry, the temperature gradient of the injection medium monitored by AHFO increases, showing an obvious space–time effect. The application of AHFO in the grouting simulation test can effectively analyze slurry diffusion in the injected medium.

28 August 2020 in Journal of Sensors
Verified
Journal Article
Open access
PDF file
WLWulin LEI
Wulin LEI
JCJing CHAI
Jing CHAI
ZDZhang Dingding
Zhang Dingding
YOYibo Ouyang
Yibo Ouyang
ZMZhe Ma
Zhe Ma
YLYongliang Liu
Yongliang Liu
In order to study the regularity of overburden deformation and mining pressure changes in the stope. Take the geological conditions of Hanglaiwan coal mine in Yushen mining area as the background, a 3000 mm×1340 mm×200 mm physical similar material model was established in laboratory. Eight fiber Bragg grating sensors were embedded in the model, used to monitor the movement and deformation of the overburden key stratum and the change of mining abutment pressure in real time and then to determine the influencing factors and strain transfer coefficients of the fiber grating through theoretical analysis and calibration experiments. The results show the following. (1) The changes in value, position, and shape of the strain can reflect the dynamic evolution process of bending deformation, breaking, and rotation of the key strata. When the key layer breaks for the first time, the strain curve shows a peak shape; when the key layer breaks periodically, the strain curve of the fiber grating sensor showed a plateau shape for a period of time. (2) The strain curve has a good corresponding relationship with the change in supporting pressure. When the strain curve of the fiber Bragg grating sensor was at the trough stage, the abutment pressure was at the peak stage, with the increase of sensor buried height, and the supporting pressure and the strain value had a linear relationship within the range of the advanced abutment pressure. The conclusion shows that the fiber Bragg grating sensor monitoring technology has good effect on the internal strain and key supporting pressure monitoring of the overburden in the model test; it provides new monitoring methods and means for the model tests.