scholarly journals Physical Modeling of Displacement and Failure Monitoring of Underground Roadway in Horizontal Strata

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Dinggui Hou ◽  
Xiaojie Yang
Keyword(s):  
Real Time ◽  
Physical Modeling ◽  
Surrounding Rock ◽  
Image Correlation ◽  
Monitoring Data ◽  
Continuous Increase ◽  
The Real ◽  
Small Constant ◽  
Constant Resistance ◽  
Underground Roadway

Physical modeling of the underground roadway in horizontal strata is carried out by using a newly developed physical modeling approach, the so-called “physically finite elemental slab assemblage (PFESA).” The numerical 2D digital image correlation (DIC) technology is used to carry out the real-time monitoring of the surface displacement of the model in the experimental process, and the axial force monitoring devices called the small bolt (SB) and small constant resistance bolt (SCRB) are designed for the real-time detection of the roadway mechanics data. The displacement information of the whole physical model experiment process is obtained through the DIC technology. The SCRB can be well used to the mechanical monitoring of the deformation and failure of the roadway, though the analysis of the displacement and mechanical monitoring data can get that the change of the mechanical monitoring data of SCRB in advance of the displacement, the information of instability destruction precursor in roadway surrounding rock is the continuous increase of mechanical monitoring value in a short time. The experiment provides reference for the stability monitoring and early warning of the roadway surrounding rock based on a constant resistance and large deformation rock bolt (CRLB).

scholarly journals Significance of Parallel Computing on the Performance of Digital Image Correlation Algorithms in MATLAB

Designs ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 15
Author(s):  
Andreas Thoma ◽  
Abhijith Moni ◽  
Sridhar Ravi
Keyword(s):  
Digital Image Correlation ◽  
Real Time ◽  
Digital Image ◽  
Correct Choice ◽  
Image Correlation ◽  
Particle Swarm Algorithm ◽  
Processing Unit ◽  
Time Analysis ◽  
The Real ◽  
Real Time Analysis

Digital Image Correlation (DIC) is a powerful tool used to evaluate displacements and deformations in a non-intrusive manner. By comparing two images, one from the undeformed reference states of the sample and the other from the deformed target state, the relative displacement between the two states is determined. DIC is well-known and often used for post-processing analysis of in-plane displacements and deformation of the specimen. Increasing the analysis speed to enable real-time DIC analysis will be beneficial and expand the scope of this method. Here we tested several combinations of the most common DIC methods in combination with different parallelization approaches in MATLAB and evaluated their performance to determine whether the real-time analysis is possible with these methods. The effects of computing with different hardware settings were also analyzed and discussed. We found that implementation problems can reduce the efficiency of a theoretically superior algorithm, such that it becomes practically slower than a sub-optimal algorithm. The Newton–Raphson algorithm in combination with a modified particle swarm algorithm in parallel image computation was found to be most effective. This is contrary to theory, suggesting that the inverse-compositional Gauss–Newton algorithm is superior. As expected, the brute force search algorithm is the least efficient method. We also found that the correct choice of parallelization tasks is critical in attaining improvements in computing speed. A poorly chosen parallelization approach with high parallel overhead leads to inferior performance. Finally, irrespective of the computing mode, the correct choice of combinations of integer-pixel and sub-pixel search algorithms is critical for efficient analysis. The real-time analysis using DIC will be difficult on computers with standard computing capabilities, even if parallelization is implemented, so the suggested solution would be to use graphics processing unit (GPU) acceleration.

scholarly journals Research and Application of a Smart Monitoring System to Monitor the Deformation of a Dam and a Slope

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yongfei Wang ◽  
Dingbin Shen ◽  
Jiankang Chen ◽  
Liang Pei ◽  
Yanling Li ◽  
...  
Keyword(s):  
Real Time ◽  
Mean Square Error ◽  
Monitoring System ◽  
Deformation Monitoring ◽  
Monitoring Data ◽  
Large Field ◽  
Maximum Relative Error ◽  
Mean Square ◽  
Integrated Monitoring ◽  
The Real

Deformation monitoring is one of the most important means of providing feedback to ensure the safety of projects. Problems plague the existing automatic monitoring system, such as the small monitoring range of monitoring devices, the inadequate field safety protection, and the low accuracy under extreme weather conditions. These problems greatly reduce the real time and reliability of deformation monitoring data and restrict the real-time intelligent control of engineering safety risk. In this paper, a multitype instrument-integrated monitoring system based mainly on the total positioning station (TPS) and supplemented by the Global Navigation Satellite System (GNSS) was promoted with the methods of large field angle, data complementation, environmental perception and judgment, automatic status control, and baseline calibration-meteorological fusion correction. The application results of Pubugou Station show that the averages of mean square error of points (APMSE) for the dam are 0.41∼1.65 mm and the averages of mean square error of height (AHMSE) are 0.42∼0.89 mm. Moreover, the APMSE and AHMSE for the slope are less than 3 mm. The maximum relative error of the TPS and GNSS data compared with the artificial monitoring data is less than 10%. Besides, the system has good overall performance and is of significant comprehensive benefits. The proposed system realizes the all-weather real-time monitoring of deformation and enhances the emergency response capability of special conditions in dams during the operation period.

scholarly journals Monitoring, intelligent perception and early warning of vortex-induced vibration of suspension bridge

2021 ◽  
Author(s):  
Danhui Dan ◽  
Houjin Li
Keyword(s):  
Real Time ◽  
Hilbert Transform ◽  
Early Warning ◽  
Single Mode ◽  
Suspension Bridge ◽  
Monitoring Data ◽  
Vortex Induced Vibration ◽  
The Real ◽  
Whole Process ◽  
Service Period

Vortex-induced vibration(VIV) is a serious problem of suspension bridges and other long-span bridges during the service period. It can cause the excessive amplitude of the structure under low wind speed, which not only affects the driving comfortableness and safety but also makes the structure face the risk of fatigue failure. The previous research on the identification and evaluation of bridge VIV events during the service period is based on the offline batch processing and analysis of monitoring data, which can not realize real-time perception, calculation, and early warning online. In this paper, according to the vibration characteristics of single-mode sinusoidal-like vibration of engineering structure during VIV, an intelligent monitoring and early warning method for VIV of suspension bridge based on recursive Hilbert transform is proposed. Firstly, the real-time acceleration integral algorithm is used to realize the real-time calculation from the acceleration monitoring data to the dynamic displacement of the stiffening beam, and then the recursive Hilbert transform is used to obtain the real-time analytical signal of the structural displacement during VIV; based on its single-mode near-circular trajectory characteristic, the VIV index and the real-time analysis method are proposed to characterize the development trend of VIV events. This online extraction algorithm can realize the first time warning and the whole process tracking and perception of VIV events. Furthermore, this article also provides a real-time online identification method of key motion parameters such as the instantaneous frequency, phase and amplitude of the structure during VIV, which lays a foundation for real-time monitoring of the whole process of VIV and further evaluation and management decision-making. The accuracy, reliability and engineering feasibility of the proposed method are verified by numerical simulation and VIV monitoring data of a real bridge.

scholarly journals Real-time measurement of radionuclide concentrations and its impact on inverse modeling of <sup>106</sup>Ru release in the fall of 2017

2020 ◽  
Author(s):  
Ondřej Tichý ◽  
Miroslav Hýža ◽  
Václav Šmídl
Keyword(s):  
Real Time ◽  
Temporal Resolution ◽  
Inverse Modeling ◽  
Source Term ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Monitoring Data ◽  
The Real ◽  
Concentration Measurements ◽  
Atmospheric Transport Model

Abstract. Abstract Low concentrations of 106Ru were detected across Europe at the turn of September and October 2017. The origin of 106Ru has still not been confirmed; however, current studies agree that the release occurred probably near Mayak in the southern Urals. The source reconstructions are mostly based on an analysis of concentration measurements coupled with an atmospheric transport model. Since reasonable temporal resolution of concentration measurements is crucial for proper source term reconstruction, the standard one week sampling interval could be limiting. In this paper, we present an investigation of the usability of the newly developed AMARA and CEGAM real-time monitoring systems, which are based on the gamma-ray counting of aerosol filters. These high resolution data were used for inverse modeling of the 106Ru release. We perform backward runs of the Hysplit atmospheric transport model driven with meteorological data from the global forecast system (GFS) and we construct a source-receptor sensitivity (SRS) matrix for each grid cell of our domain. Then, we use our least-squares with adaptive prior covariance (LS-APC) method to estimate possible locations of the release and the source term of the release. On Czech monitoring data, the use of concentration measurements from the standard regime and from the real-time regime is compared and better source reconstruction for the real-time data is demonstrated in the sense of the location of the source and also the temporal resolution of the source. The estimated release location, Mayak, and the total estimated source term, 237 ± 107 TBq, are in agreement with previous studies. Finally, the results based on the Czech monitoring data are validated with the IAEA reported dataset with a much better spatial resolution, and the agreement between the IAEA dataset and our reconstruction is demonstrated.

Research of Surrounding Rock Classification Correction Method

2015 ◽  
Vol 777 ◽  
pp. 74-84
Author(s):  
Hong Liang Deng ◽  
Si Miao Wang ◽  
Ge Chen ◽  
Yang Guo
Keyword(s):  
Real Time ◽  
Measurement Data ◽  
Stable State ◽  
Principal Component ◽  
Correction Method ◽  
Surrounding Rock ◽  
Design Phase ◽  
Rock Classification ◽  
The Real ◽  
Tunnel Convergence

At present, both at home and abroad of tunnel surrounding rock classification methods and standards are all aimed at tunnel survey and design phase. It is the cause of that surrounding rock classification are very different between design phase and tunnel construction because of the limits of investigation techniques and geological data. It is the key to the real-time construction design problem that Sentenced to a stable state of surrounding rock based on the monitoring data. This paper determines the influence factors of tunnel convergence value clearance and obtained the tunnel convergence value clearance of principal component factor and power based on the statistical analysis of a lot of tunnel monitoring measurement data. It is put forward correction formula of dynamic classification of surrounding rock according to the theory of probability and statistics. The results show that based on the real-time monitoring of tunnel surrounding rock classification method is quite coincident with the actual situation of tunnel excavation in engineering applications.

The Roadway Surrounding Rock Delaminating Displacement Monitoring Technology Based on Moiré Technique

2011 ◽  
Vol 58-60 ◽  
pp. 2101-2104
Author(s):  
Fang Liang Luo ◽  
Li Qian An ◽  
Ling Tao Mao ◽  
Jian Cheng Xu ◽  
Lei Li ◽  
...  
Keyword(s):  
Real Time ◽  
Measurement Theory ◽  
Surrounding Rock ◽  
Rock Deformation ◽  
Displacement Monitoring ◽  
Monitoring Technology ◽  
The Real ◽  
Working Face ◽  
Roof Fall ◽  
Safety Production

With the coalface excavates, surrounding rock of roadway will occur deformation in different degrees. When the rock deformation exceeds a certain limit, roof fall and spalling would occur. To prevent such accidents, it is very important to monitor deformation of the surrounding rock in real-time. In this paper, Moiré measurement theory is elaborated. The displacement device (GWG200(C)), based on moiré technique, are applied in ventilation tunnel of 1015 working face in Xing Ge Zhang Mine to monitor deformation. The real time datum of deformation are obtained. The system provides technique safeguard for safety production.

Outburst Hazard Prediction Based on the Monitoring Data in Heading Face

2013 ◽  
Vol 734-737 ◽  
pp. 786-790
Author(s):  
Fu Sheng Wu ◽  
Shui Wen Liu
Keyword(s):  
Mechanical Properties ◽  
Real Time ◽  
Monitoring System ◽  
Physical And Mechanical Properties ◽  
Monitoring Data ◽  
The Real ◽  
Verification Test ◽  
Outburst Hazard ◽  
Good Agreement ◽  
Predictive Indicators

To analyse the outburst hazard of heading face in real time, based on the mechanism of coal and gas burst and its forecasting principle, four real-time predictive indicators were proposed, which involve three aspects: crustal stress, gas, physical and mechanical properties of coal, and had a verification test. The results show that the real-time predictive indicators are in good agreement with the traditional indicators, whose deviation are mainly caused by gas exceeded. With the monitoring data in monitoring system, the outburst hazard of heading face could be predicted in real time, which could help to prevent outburst.

scholarly journals Real-time measurement of radionuclide concentrations and its impact on inverse modeling of <sup>106</sup>Ru release in the fall of 2017

2021 ◽  
Vol 14 (2) ◽  
pp. 803-818
Author(s):  
Ondřej Tichý ◽  
Miroslav Hýža ◽  
Nikolaos Evangeliou ◽  
Václav Šmídl
Keyword(s):  
Real Time ◽  
Temporal Resolution ◽  
Inverse Modeling ◽  
Source Term ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Monitoring Data ◽  
The Real ◽  
Concentration Measurements ◽  
Atmospheric Transport Model

Abstract. Low concentrations of 106Ru were detected across Europe at the turn of September and October 2017. The origin of 106Ru has still not been confirmed; however, current studies agree that the release occurred probably near Mayak in the southern Urals. The source reconstructions are mostly based on an analysis of concentration measurements coupled with an atmospheric transport model. Since reasonable temporal resolution of concentration measurements is crucial for proper source term reconstruction, the standard 1-week sampling interval could be limiting. In this paper, we present an investigation of the usability of the newly developed AMARA (Autonomous Monitor of Atmospheric Radioactive Aerosol) and CEGAM (carousel gamma spectrometry) real-time monitoring systems, which are based on the gamma-ray counting of aerosol filters and allow for determining the moment when 106Ru arrived at the monitoring site within approx. 1 h and detecting activity concentrations as low as several mBq m−3 in 4 h intervals. These high-resolution data were used for inverse modeling of the 106Ru release. We perform backward runs of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) atmospheric transport model driven with meteorological data from the Global Forecast System (GFS), and we construct a source–receptor sensitivity (SRS) matrix for each grid cell of our domain. Then, we use our least squares with adaptive prior covariance (LS-APC) method to estimate possible locations of the release and the source term of the release. With Czech monitoring data, the use of concentration measurements from the standard regime and from the real-time regime is compared, and a better source reconstruction for the real-time data is demonstrated in the sense of the location of the source and also the temporal resolution of the source. The estimated release location, Mayak, and the total estimated source term, 237±107 TBq, are in agreement with previous studies. Finally, the results based on the Czech monitoring data are validated with the IAEA-reported (International Atomic Energy Agency) dataset with a much better spatial resolution, and the agreement between the IAEA dataset and our reconstruction is demonstrated. In addition, we validated our findings also using the FLEXPART (FLEXible PARTicle dispersion) model coupled with meteorological analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF).

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