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- 저자 : Chuang Jiang (검색결과 13 건)
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Chuang Jiang,Lei Wang,Xuexiang Yu,Weicai Lv,Xu Yang 대한토목학회 2022 KSCE JOURNAL OF CIVIL ENGINEERING Vol.26 No.5
3D surface deformation monitoring methods based on the current single-track Interferometric Synthetic Aperture Radar (InSAR) technology are constructed by integrating the deformation laws of mining horizontal or gently inclined coal seams in plain areas, which are not suitable for monitoring the 3D deformation of mining in mountainous areas. Therefore, we developed a new method of extracting 3D deformation of mining in mountainous areas by using single-track InSAR technology. Firstly, the Line of Sight (LOS) deformation equations were established based on geometric relations between the InSAR monitored LOS deformation and 3D surface deformation. Secondly, they were fused with basic principles of surface deformation and movement of mining in mountainous areas. Then they were solved based on relevant boundary conditions. Simulation results of this novel method showed that the accuracy values of extracted deformation along vertical section, East-West (EW) and North-South (NS) were better than 8.86 mm, 8.29 mm and 18.01 mm, respectively. Compared with Wang method, this method is suitable for surface deformation monitoring of mining subsidence in mountainous areas. Finally, the proposed method was successfully used to monitor the 3D deformation of mining in the mountainous area of Tangjiahui Coal Mine in Ordos, Inner Mongolia, China.
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Chuang Jiang,Lei Wang,Xuexiang Yu,Shenshen Chi,Tao Wei,Xuelin Wang 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.2
The mining subsidence in mining area could cause large-gradient deformation in a short period of time. When the deformation gradient exceeds the threshold value of the Differential Interferometry Synthetic Aperture Radar (D-InSAR) technology monitoring gradient, D-InSAR technology is likely to cause the failure of InSAR phase unwrapping algorithm. At this time, the InSAR technology is unable to monitor the 3D surface deformation. Aiming at these problems, an dynamic probability integral method (DPIM)-based InSAR phase unwrapping model and a method of extracting 3D surface deformation were proposed. The phase unwrapping model firstly used the empirical parameters of the probability integral of the mining face to predict the line of sight (LOS) direction deformation phase of the mining subsidence surface. Secondly, the phase of differential interferogram was unwrapped with the assist of the predicted LOS deformation phase under the constraint of DPIM, and the true LOS deformationphase was obtained, then the true LOS deformation phase transformed into LOS deformation. Finally, according to the geometric projection relationship between the LOS deformation and 3D deformation of mining subsidence surface, the probability integral prior model was brought into the equation of the geometric projection relationship. On the basis of relevant boundary conditions, the 3D surface deformation was extracted from the LOS direction deformation field of mining subsidence. The feasibility of the method was verified by the simulation experiment results. The differential interferogram of the subsidence basin was obtained by the differential interference processing of image data of Sentinel-1A on Nov. 16, 2017 and Dec. 10, 2017 of 1613 working face of Guqiao South Mine. By using the DPIM-based phase unwrapping model, the phase of differential interferogram was unwrapped and the 3D surface deformation during this period as well as the deformation extraction method were developed. The results showed that the maximum fitting error value of subsidence was 79 mm, about 8.33% of the maximum value of subsidence, and the fitting error of mean square of subsidence was ±33.5 mm. The results showed that the DPIM-based phase unwrapping model and the method of extracting 3D surface deformation proposed in this paper have certain engineering application values.
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Jiang, Shui-Hua,Li, Dian-Qing,Zhou, Chuang-Bing,Zhang, Li-Min Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.49 No.1
The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.
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Chiuchu Chuang,채기병,Jiang-miao Wu,Seana Pernice-Kowalcyzk 한국상담학회 2017 Journal of Asia Pacific counseling Vol.7 No.1
The purpose of this study was the development and initial validation of the Chinese version of College Stress Inventory (C-CSI) using a sample of 806 undergraduate and graduate students in China. The C-CSI was examined through a two- step procedures: (1) translation and back translation and (2) psychometrics analysis using internal consistency and exploratory factor analysis. The initial validation of the 18-item C-CSI yielded three subscales: Academic Stress, Financial Stress, and Social Stress. The C-CSI demonstrates good reliability for its intended informal applications, and initial estimates of validity suggest the scale has good preliminary validity. Implications, limitations, and suggestions for further research directions are discussed.
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Lei Wang,Chuang Jiang,Tao Wei,Nan Li,Shenshen Chi,Jianfeng Zha,Suyang Fang 대한토목학회 2020 KSCE JOURNAL OF CIVIL ENGINEERING Vol.24 No.1
The data of surface movement observation points could be used to obtain the synthetic angles of draw and critical deformation of surface movement basin in the mining area with unconsolidated thick layers. However, they couldn’t be used to get the angles of draw and critical deformation of unconsolidated layers and rock layers, which are called angular parameters of surface movement basin and can be used to describe the outermost boundary and the dangerous boundary. Therefore, the paper presented an estimation method of angular parameters of surface moving basin based on least squares of Huber selecting weight iteration (LSHSWI). The method firstly classified the surface movement observation points with similar geological and mining conditions as the same kinds. Then, the synthetic angles of critical deformation and draw obtained by the observation points were taken as observation values, and angular parameters of surface movement basin were taken as unknown parameters.According to the geometric relationship between the synthetic angles and the angular parameters, the observation equation was established. Finally, the parameters estimation method based on LSHSWI was constructed with consideration of errors in the synthetic angles of draw and critical deformation. The simulation experiments show that the LSHSWI estimation method of angular parameters of surface movement basin has a strong anti-interference ability to errors of observation values. The engineering application shows that the parameter estimation method based on LSHSWI is scientific and practical.
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Shui-Hua Jiang,Dian-Qing Li,Chuang-Bing Zhou,Li-Min Zhang 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.49 No.1
The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.
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Li, Dian-Qing,Jiang, Shui-Hua,Cheng, Yong-Gang,Zhou, Chuang-Bing Techno-Press 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.45 No.5
This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.
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Lei Wang,Shangjun Zhu,Chuang Jiang,Jingyu Li,Kegui Jiang,Chaoqun Teng,Tao Wei,Qing-biao Guo 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.11
When 3D laser scanning technology is used to monitor the surface deformation of mining subsidence in mining area, the surface of the working face is covered with a large number of vegetation, and the surface water accumulates above the working face, which makes the point cloud data obtained by the 3D laser scanning difficult to denoise, or even missing. At this time, the conventional 3D laser scanning technology can not obtain the surface deformation field of mining subsidence. Aiming at the above problems, the 3D laser scanning monitoring method for mining subsidence based on the auxiliary for PIM proposed (3DLS-PIM). Firstly, this paper introduces the PIM prediction model. Secondly, the mining subsidence observation equation based on 3DLS-PIM is constructed, and then the prediction parameters of PIM are solved based on quantum particle swarm optimization (QPSO). Finally, according to the PIM and its parameters, the mining subsidence surface deformation basin is predicted and obtain the surface deformation field of mining subsidence. Robust experiments show that QPSO has a certain ability to resist random errors and gross errors. The results of engineering application show that the mining area 3D deformation monitoring method proposed in this paper has certain engineering application value.
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System Reliability Analysis of Rock Slope Stability Involving Correlated Failure Modes
Dian-Qing Li,Shui-Hua Jiang,Yi-Feng Chen,Chuang-Bing Zhou 대한토목학회 2011 KSCE JOURNAL OF CIVIL ENGINEERING Vol.15 No.8
This paper aims to propose a systematic quantitative method for system reliability evaluation of rock slope with plane failure involving multiple correlated failure modes. A probabilistic fault tree approach is presented to model system reliability of rock slope. An n-dimensional equivalent reliability method is employed to perform the system reliability analysis of the slope involving multiple correlated failure modes. Reliability sensitivity analyses at three different levels, namely, the single limit state function level, single failure mode level, and system reliability level, are carried out to study the effect of variables on reliability. An example is presented to demonstrate the validity and capability of the proposed approach. The results indicate that the system reliability of rock slope involving multiple correlated failure modes can be evaluated efficiently using the proposed approach. The system probability of failure is overestimated if the correlations between different failure modes are ignored. The relative importance of different failure modes to the system reliability can differ considerably. The sensitivity coefficients of basic random variables strongly depend on the selected sensitivity analysis level. The system reliability is sensitive to the location of the tension crack and the percentage of the tension crack filled with water.
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Dian-Qing Li,Shui-Hua Jiang,Yong-Gang Cheng,Chuang-Bing Zhou 국제구조공학회 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.45 No.5
This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.
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