Numerical simulation of optimum mining design for high stress hard-rock deposit based on inducing fracturing mechanism

The 3D numerical simulation model of deep hard-rock deposit in Kaiyang Phosphate Mine of Guiyang was established based on the practical engineering using 3DEC numerical simulation software. The distribution characteristics of displacement fields and plastic zones of the orebody were simulated in three different excavation cases, including the case of excavation artificial inducted roadway in the orebody, the case of horizontal or vertical excavation direction and the case of the upward or downward excavation order. The simulation results indicate that the plastic zone and displacement field of surrounding rock around the inducted roadway are continuously increasing with the increase of the exposure time after digging an artificial inducted roadway in the orebody. Thus the raw rock ore becomes easier to be fragmented, which provides advantageous conditions for roadheader to cut high stress hard-rock. It is worthy noting that there is a large difference in effective utilization of deep ground pressure between horizontal and vertical excavation directions. The later can produce larger deformation and fracture zone than the former on the rock mass around the deduced roadway, which means that the later may utilize the high ground pressure more effectively to break hard-rock. And the obtained results also show that upward excavation order is more helpful for ground pressure to break rock than downward excavation order.

Classification methods of association rules with linguistic terms

A partition of intervals method is adopted in current classification based on associations (CBA), but this method cannot reflect the actual distribution of data and exists the problem of sharp boundary problem. The classification system based on the longest association rules with linguistic terms is discussed, and the shortcoming of this classification system is analyzed. Then, the classification system based on the short association rules with linguistic terms is presented. The example shows that the accuracy of the classification system based on the association rules with linguistic terms is better than two popular classification methods: C4.5 and CBA.

Numerical investigation of water-entry of flatted-bottom seafloor mining tool in ocean waves

A numerical wave load model based on two-phase(water-air) Reynolds-Averaged Navier Stokes(RANS) type equations is used to evaluate hydrodynamic forces exerted on flatted-bottom seafloor mining tool during its entering ocean waves of deploying process.The discretization of the RANS equations is achieved by a finite volume approach(FV).The volume of fluid method(VOF) is employed to track the complicated free surface.A numerical wave tank is built to generate the ocean waves which are suitable for deploying seafloor mining tool.A typical deploying condition is employed to reflect the process of flatted-bottom body impacting with waves,and the pressure distribution of bottom is also presented.Four different lowering velocities are applied to obtain the time histories of maximum pressure of bottom,and it can be concluded that the pressure coefficient decreases with water velocity increasing,which is similar with ordinary water entry case.The numerical results clearly demonstrate the characteristics of flatted-bottom body entering ocean waves.

A combined 2D and 3D numerical modeling approach to provide adequate roof support in complex 3D excavations

Traditional methods for assessing effective roof support can be difficult to apply to complex three-dimensional excavations. Through worked examples,the approach of combined two-dimensional and three-dimensional numerical modeling has been shown to be successful in understanding mechanisms of rock failure for unique excavation geometries and geotechnical properties and,in turn,provides adequate roof support recommendations for complex three-dimensional excavations in Australian coal mines. An interactive approach of monitoring and model review during the excavation process is an important part of model support recommendations to ensure rock failure and deformation in the model are representative of actual conditions,to provide effective and practical controls.

Experimental study and numerical simulation of gas/particle flow in tunneling of mine

Respiration particles can be collected into a dust catcher by an inside inhalingand outside pressing particle collector. The work environment of the grab operator in tunneling mining was improved when a dust catcher is placed before the working face of thegrab operator. The particle movement was affected by the gas flow. The flow field insideand outside the dust collector was simulated. The effect of the operating parameter wasanalyzed. The numerical results show a good approach to predict the gas flow and particledistribution in the inside and outside of the particle collector.

Distribution of lateral floor abutment pressure in a stope

In order to study the distribution of lateral floor abutment pressure at a working face,we first used elasticity theory to establish a distribution model of lateral floor abutment pressure and then analysed its distribution.Second,we established a three-dimensional numerical simulation model of the Haizi Coal Mine No.86 mining area by using FLAC^（3D）（ITASCA Consulting Group） software.We investigated the distribution of lateral floor abutment pressure of a stope,which indicated that the position of abutment pressure peak varies at different floor depths.We then determined the rational reinforcement range of a floor roadway,based on the conclusion reached earlier.Finally,we used our conclusions in support of the No.86 mining area crossing-roadway.The supported crossing-roadway remained stable when mining the upper workface,which validates the accuracy of our numerical simulation and provides a future reference for the support of span-roadways under similar conditions.

Numerical Modeling of Giant Badu Landslide Reactivated by Excavation in China

In southwest of China, landslide reactivation caused by excavation has caused huge property and human losses, and posed severely threaten to the construction and operation of the man-made linear structures. A reactivated landslide is a complex process. The engineering practices have shown that a correct understanding of the reactivated mechanism of an ancient giant landslide is significant for the landslide mitigation. In this paper, a case study of the ancient Badu landslide that underwent multiple reactivations during the construction of Nanning-Kunming railway was discussed. The landslide characteristics are described and the reactivated features and progressive failure of the landslide are revealed. The reactivated mechanism of the landslide is analyzed by use of geological process analysis method and is simulated using the 3D FEM （finite element method）. At last, the reactivated mechanism mode of Badu giant landslide is put forward, namely ＂creeping-tensile cracking-shear breaking with zoning and grading features＂. The understanding of this kind of reactivated mechanism had helped engineers to take efficient and economic mitigation measures to stabilize the landslide.

基于定量关联规则树的分类及回归预测算法

为了解决基于Apriori的分类关联规则算法挖掘数值型数据时效率和准确率偏低的问题,提出基于定量关联规则树的分类及回归预测算法.采用改进的定量关联规则算法挖掘数值型数据生成关联规则库,并基于关联规则树结构实现分类及回归预测.研究结果表明:改进的Apriori定量关联规则挖掘算法提高了分类预测的准确率并降低了计算复杂度;而采用关联规则树结构可使分类与回归预测时间明显加快,提高了样本匹配学习的速度.

Integrating OWA and Data Mining for Analyzing Customers Churn in E-Commerce

Customers are of great importance to E-commerce in intense competition.It is known that twenty percent customers produce eighty percent profiles.Thus,how to find these customers is very critical.Customer lifetime value(CLV) is presented to evaluate customers in terms of recency,frequency and monetary(RFM) variables.A novel model is proposed to analyze customers purchase data and RFM variables based on ordered weighting averaging(OWA) and K-Means cluster algorithm.OWA is employed to determine the weights of RFM variables in evaluating customer lifetime value or loyalty.K-Means algorithm is used to cluster customers according to RFM values.Churn customers could be found out by comparing RFM values of every cluster group with average RFM.Questionnaire is conducted to investigate which reasons cause customers dissatisfaction.Rank these reasons to help E-commerce improve services.The experimental results have demonstrated that the model is effective and reasonable.