抗滑桩在限制性航道岸坡整体稳定中的计算方法

针对抗滑桩在限制性航道岸坡整体稳定中受力复杂、计算方法种类多样且各方法中桩及土各自提供的抗滑作用不易量化等问题,依托长湖申线(浙江段)航道扩建工程中抗滑桩的应用实例,通过对实例中的典型护岸断面建立多组模型数据进行受力分析及比较,总结归纳出抗滑桩在限制性航道岸坡整体滑移稳定中的各种破坏模式、最不利滑弧形成的位置、特性等规律进行分析及探讨,并借鉴抗滑桩理论研究中的相关成果给出抗滑桩在岸坡整体稳定中的简易计算方法,得出抗滑过程中桩及土各自提供的有效作用力。

Deformation mechanism and stability control of roadway along a fault subjected to mining

It is difficult to maintain the roadway around a fault because of the fractured surroundings, complex stress environment, and large and intense deformation in the mining process. Based on a tailgate of panel $2205 in Tunliu colliery, in Shanxi province, China, we investigated the evolution of stress and displace- ment of rocks surrounding the roadway during the drivage and mining period using theoretical analysis, numerical simulation and field trial methods. We analyzed the deformation and failure mechanisms of the tailgate near a fault. The deformation of surrounding rock caused by unloading in the drivage period is large and asymmetric, the roadway convergence increases with activation of the fault and secondary fracture develops in the mining period. Therefore, we proposed a specific control technique of the road- way along a fault as follows： （1） High-strength yielding bolt not only supports the shallow rock to load- bearing structures, but also releases primary deformation energy by use of a pressure release device in order to achieve high resistance to the pressure retained： （2） Grouting of near-fault ribside after initial stabilization of the rock deformation is used to reinforce the broken rock, and to improve the integral load-bearing capacity ol~ the roadway. The research results were successfully applied to a field trial.

Optimal design for buckets layout based on muck removal analysis of TBM cutterhead

The layout of the buckets for tunnel boring machine(TBM)directly affects the muck removal efficiency of cutterhead during excavation.In order to improve the muck removal performance for TBM,the optimal design of bucket layout was investigated.The whole muck transfer process was simulated by discrete-element method(DEM),including the muck falling,colliding,pilling up,shoveling and transferring into the hopper.The muck model was established based on size distribution analysis of muck samples from the water-supply tunnel project in Jilin Province,China.Then,the influence of the bucket number and the interval angle between buckets on muck removal performance was investigated.The results indicated that,as the number of buckets increased from four to eight,the removed muck increased by 29%and the residual volume decreased by 40.5%,and the process became steadier.Different interval angles between buckets were corresponding to different removed muck irregularly,but the residual muck number increased generally with the angles.The optimal layout of buckets for the cutterhead in this tunnel project was obtained based on the simulation results,and the muck removal performance of the TBM was verified by the actual data in the engineering construction.

Researches on the key technology and equipment for rapid construction of long tunnels with large section

Excavation and lining are two main important tasks in tunnel construction. Conventional sequential operations may not be appropriate due to time limit for a project and the high cost of construction. The authors developed a new mode of tunnel construction that excavation and lining can be operated simultaneously. The new mode of tunnel construction has been successfully applied to Dahuofang Water Conveyance Project in Liaoning Province. This paper makes a comparison of Main Beam TBMs and Double Shield TBMs used in Dahuofang Water Conveyance Project, and the features of Full-ring Inner-through Lining Shutter Jumbo which solves the problem of interference between excavation and lining.

岩巷防误揭煤方法的探析

十三矿地质构造极其复杂,己组煤层瓦斯低位抽采巷(以下简称低抽巷)施工过程中,遵循"物探、钻探加标志层",并严格执行"三探两防一对比分析"的管控模式,解决了防止误揭煤及突水问题。通过对岩巷遇到断层的分析,优化了探测方案,不仅加快生产进度,保证了安全生产,同时节约生产成本。

Research on Text Mining of Syndrome Element Syndrome Differentiation by Natural Language Processing

Objective Natural language processing (NLP) was used to excavate and visualize the core content of syndrome element syndrome differentiation (SESD). Methods The first step was to build a text mining and analysis environment based on Python language, and built a corpus based on the core chapters of SESD. The second step was to digitalize the corpus. The main steps included word segmentation, information cleaning and merging, document-entry matrix, dictionary compilation and information conversion. The third step was to mine and display the internal information of SESD corpus by means of word cloud, keyword extraction and visualization. Results NLP played a positive role in computer recognition and comprehension of SESD. Different chapters had different keywords and weights. Deficiency syndrome elements were an important component of SESD, such as "Qi deficiency""Yang deficiency" and "Yin deficiency". The important syndrome elements of substantiality included "Blood stasis""Qi stagnation", etc. Core syndrome elements were closely related. Conclusions Syndrome differentiation and treatment was the core of SESD. Using NLP to excavate syndromes differentiation could help reveal the internal relationship between syndromes differentiation and provide basis for artificial intelligence to learn syndromes differentiation.

Rough set and radial basis function neural network based insulation data mining fault diagnosis for power transformer

Rough set (RS) and radial basis function neural network (RBFNN) based insulation data mining fault diagnosis for power transformer is proposed. On the one hand rough set is used as front of RBFNN to simplify the input of RBFNN and mine the rules. The mined rules whose “confidence” and “support” is higher than requirement are used to offer fault diagnosis service for power transformer directly. On the other hand the mining samples corresponding to the mined rule, whose “confidence and support” is lower than requirement, are used to be training samples set of RBFNN and these samples are clustered by rough set. The center of each clustering set is used to be center of radial basis function, i.e., as the hidden layer neuron. The RBFNN is structured with above base, which is used to diagnose the case that can not be diagnosed by mined simplified valuable rules based on rough set. The advantages and effectiveness of this method are verified by testing.