Buried water-conducting and water-bearing structures in front of the driving head may easily lead to water bursts in coal mines. Therefore,it is very important for the safety of production to make an accurate and time...Buried water-conducting and water-bearing structures in front of the driving head may easily lead to water bursts in coal mines. Therefore,it is very important for the safety of production to make an accurate and timely forecast about water bursts. Based on the smoke ring effect of transient electromagnetic fields,the principle of transient electro-magnetic method used in detecting buried water-bearing structures in coal mines in advance,is discussed. Small multi-turn loop configurations used in coal mines are proposed and a field procedure of semicircular sector scanning is presented. The application of this method in one coal mine indicates that the technology has many advantages compared with others. The method is inexpensive,highly accurate and efficient. Suggestions are presented for future solutions to some remaining problems.展开更多
The infiltration of water into soil is one of the most important soil physical properties that affect soil erosion and the eco-environment, especially in the Pisha sandstone area on the Chinese Loess Plateau. We studi...The infiltration of water into soil is one of the most important soil physical properties that affect soil erosion and the eco-environment, especially in the Pisha sandstone area on the Chinese Loess Plateau. We studied the one-dimensional vertical infiltration of water in three experimental soils, created by mixing Pisha sandstone with sandy soil, irrigation-silted soil, and loessial soil, at mass ratios of 1：1, 1：2, 1：3, 1：4, and 1：5. Our objective was to compare water infiltration in the experimental soils and to evaluate the effect of Pisha sandstone on water infiltration. We assessed the effect by measuring soil bulk density（BD）, porosity, cumulative infiltration, infiltration rate and saturated hydraulic conductivity（Ks）. The results showed that Pisha sandstone decreased the infiltration rate and saturated hydraulic conductivity in the three experimental soils. Cumulative infiltration over time was well described by the Philip equation. Sandy soil mixed with the Pisha sandstone at a ratio of 1：3 had the best water-holding capacity. The results provided experimental evidence for the movement of soil water and a technical support for the reconstruction and reclamation of mining soils in the Pisha sandstone area.展开更多
This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty...This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty in heterogeneous soil parameter estimates and quantification of reliability. This review is limited to methods based on coupled simulation-optimization (S-O) models. In this context, the design of WRSs is mainly affected by hydraulic design variables such as seepage quantities, which are difficult to determine from closed-form solutions or approximation theories. An S-O model is built by integrating numerical seepage modeling responses to an optimization algorithm based on efficient surrogate models. The surrogate models (meta-models) are trained on simulated data obtained from finite element numerical code solutions. The proposed methodology is applied using several machine learning techniques and optimization solvers to optimize the design of WRS by incorporating different design variables and boundary conditions. Additionally, the effects of several scenarios of flow domain hydraulic conductivity are integrated into the S-O model. Also, reliability based optimum design concepts are incorporated in the S-O model to quantify uncertainty in seepage quantities due to uncertainty in hydraulic conductivity estimates. We can conclude that the S-O model can efficiently optimize WRS designs. The ANN, SVM, and GPR machine learning technique-based surrogate models are efficiently and expeditiously incorporated into the S-O models to imitate the numerical responses of simulations of various problems.展开更多
基金Project 40674074 supported by the National Natural Science Foundation of China20050290501 by the Specialized Research Fund for the Doctoral Programof Higher EducationD200409 by the Scientific Research Fund for Youth of China University of Mining & Technology
文摘Buried water-conducting and water-bearing structures in front of the driving head may easily lead to water bursts in coal mines. Therefore,it is very important for the safety of production to make an accurate and timely forecast about water bursts. Based on the smoke ring effect of transient electromagnetic fields,the principle of transient electro-magnetic method used in detecting buried water-bearing structures in coal mines in advance,is discussed. Small multi-turn loop configurations used in coal mines are proposed and a field procedure of semicircular sector scanning is presented. The application of this method in one coal mine indicates that the technology has many advantages compared with others. The method is inexpensive,highly accurate and efficient. Suggestions are presented for future solutions to some remaining problems.
基金supported by the Key Technology and Demonstration of Damaged Ecosystem Restoration and Reconstruction in Shanxi–Shaanxi–Inner Mongolia Energy Base Location (KZCX2-XB3-13-02)
文摘The infiltration of water into soil is one of the most important soil physical properties that affect soil erosion and the eco-environment, especially in the Pisha sandstone area on the Chinese Loess Plateau. We studied the one-dimensional vertical infiltration of water in three experimental soils, created by mixing Pisha sandstone with sandy soil, irrigation-silted soil, and loessial soil, at mass ratios of 1：1, 1：2, 1：3, 1：4, and 1：5. Our objective was to compare water infiltration in the experimental soils and to evaluate the effect of Pisha sandstone on water infiltration. We assessed the effect by measuring soil bulk density（BD）, porosity, cumulative infiltration, infiltration rate and saturated hydraulic conductivity（Ks）. The results showed that Pisha sandstone decreased the infiltration rate and saturated hydraulic conductivity in the three experimental soils. Cumulative infiltration over time was well described by the Philip equation. Sandy soil mixed with the Pisha sandstone at a ratio of 1：3 had the best water-holding capacity. The results provided experimental evidence for the movement of soil water and a technical support for the reconstruction and reclamation of mining soils in the Pisha sandstone area.
文摘This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty in heterogeneous soil parameter estimates and quantification of reliability. This review is limited to methods based on coupled simulation-optimization (S-O) models. In this context, the design of WRSs is mainly affected by hydraulic design variables such as seepage quantities, which are difficult to determine from closed-form solutions or approximation theories. An S-O model is built by integrating numerical seepage modeling responses to an optimization algorithm based on efficient surrogate models. The surrogate models (meta-models) are trained on simulated data obtained from finite element numerical code solutions. The proposed methodology is applied using several machine learning techniques and optimization solvers to optimize the design of WRS by incorporating different design variables and boundary conditions. Additionally, the effects of several scenarios of flow domain hydraulic conductivity are integrated into the S-O model. Also, reliability based optimum design concepts are incorporated in the S-O model to quantify uncertainty in seepage quantities due to uncertainty in hydraulic conductivity estimates. We can conclude that the S-O model can efficiently optimize WRS designs. The ANN, SVM, and GPR machine learning technique-based surrogate models are efficiently and expeditiously incorporated into the S-O models to imitate the numerical responses of simulations of various problems.
