An influence function method based subsidence prediction program for longwall mining operations in inclined coal seams

The distribution of the final surface subsidence basin induced by longwall operations in inclined coal seam could be significantly different from that in flat coal seam and demands special prediction methods. Though many empirical prediction methods have been developed, these methods are inflexible for varying geological and mining conditions. An influence function method has been developed to take the advantage of its fundamentally sound nature and flexibility. In developing this method, significant modifications have been made to the original Knothe function to produce an asymmetrical influence function. The empirical equations for final subsidence parameters derived from US subsidence data and Chinese empirical values have been incorporated into the mathematical models to improve the prediction accuracy. A corresponding computer program is developed. A number of subsidence cases for longwall mining operations in coal seams with varying inclination angles have been used to demonstrate the applicability of the developed subsidence prediction model.     

Calculation of maximum surface settlement induced by EPB shield tunnelling and introducing most effective parameter

This study aims to predict ground surface settlement due to shallow tunneling and introduce the most affecting parameters on this phenomenon.Based on data collected from Shanghai LRT Line 2 project undertaken by TBM-EPB method,this research has considered the tunnel's geometric,strength,and operational factors as the dependent variables.At first,multiple regression(MR) method was used to propose equations based on various parameters.The results indicated the dependency of surface settlement on many parameters so that the interactions among different parameters make it impossible to use MR method as it leads to equations of poor accuracy.As such,adaptive neuro-fuzzy inference system(ANFIS),was used to evaluate its capabilities in terms of predicting surface settlement.Among generated ANFIS models,the model with all input parameters considered produced the best prediction,so as its associated R~2 in the test phase was obtained to be 0.957.The equations and models in which operational factors were taken into consideration gave better prediction results indicating larger relative effect of such factors.For sensitivity analysis of ANFIS model,cosine amplitude method(CAM) was employed; among other dependent variables,fill factor of grouting(n) and grouting pressure(P) were identified as the most affecting parameters.     

Fracturing,caving propagation and influence of mining on groundwater above longwall panels——a review of predictive models

Historically there have been a number of different hypotheses and empirical models developed in an attempt to describe the nature of fracturing above longwall panels in underground coal mining. The motivation for such models varies, ranging from understanding the impact of mining on surface subsidence,to back-analysis of caving behaviour in the immediate roof behind the longwall face. One of the most critical motivating factors that is taking on increased importance in many coalfields, is the need for better understanding, and hence prediction of the impact of mining on overlying strata, particularly strata units acting as aquifers for different groundwater horizons. This paper reviews some of the major prediction models in the context of observed behaviour of strata displacement and fracturing above longwall panels in the southern coalfields of New South Wales, south of Sydney. The paper discusses the parameter often referred to as ‘‘height of fracturing" in terms of the critical parameters that influence it, and the relevance and appropriateness of this terminology in the context of overlying sub-surface subsidence and groundwater impact. The paper proposes an alternative terminology for this parameter that better reflects what it is and how it is used. The paper also addresses the potential role of major bedding shear planes mobilised by mining and their potential influence on overlying subsidence and groundwater interference.     

水平煤层半无限开采时沉陷参数误差对下沉预计结果精度的影响

本文依据误差理论，系统地分析了水平煤层半无限开采时概率积分法、威布尔分布法和样条概率积分法的参数误差对下沉预计结果精度的影响，弄清了预计结果精度的分布规律，评述了它们的优缺点，并指出了改进措施。本文的研究结果对开采沉陷观测站设计、开采沉陷参数及计算模型的识别具有指导意义。     

大采深巨厚砾岩综放开采地表沉陷规律

以常村煤矿工程地质资料和地表移动观测站资料为依据,详细分析了2113工作面地表终态下沉、动态下沉和终态水平移动的特征,从机理上研究了大采深巨厚砾岩开采条件下地表形变异常的原因.通过走向方向最大下沉点下沉速度的变化规律和工程实测资料,得出了地表形变与井下冲击地压的关系,确定了地表移动与变形的角量参数.结果表明,受关键层的控制,在整个观测过程中,地表始终处于缓慢下沉状态,且在沉降过程中不存在下沉突变点;下沉速度的反弹可以作为冲击地压危险的预报信息,巨厚砾岩层的运动是发生矿震的主要力源之一.     

时序分析在开采沉陷动态参数预计中的应用

应用时间序列分析法,对开采沉陷动态过程的概率积分法预计参数进行分析,建立动态预计模型。用该模型可对参数的未来值进行预计,然后利用预计结果进一步预计地表的移动变形,解决了开采沉陷的动态预计问题。应用此法,地表下沉的相对预计误差一般为４％左右,与传统方法相比,预计精度可提高５％～１５％。     

隧道开挖地表移动参数选取的自适应遗传算法

针对某地铁车站开挖引起地表沉降较大的问题,基于车站开挖引起地表沉降的实测数据,利用随机介质理论方法反演地铁车站初步开挖引起的地表移动参数,包括沉降槽影响范围以及断面收缩率,并利用所得的参数对该车站下一步开挖进行地表沉降预测;通过类似地层条件的地表沉降实测数据,利用数值模拟正交反分析法确定主要模型参数,预测了该地铁车站各施工阶段引起的地表沉降值。并结合洞内特征点的收敛发展规律,将地表沉降理论预测结果与数值模拟结果进行对比。结果表明:由于2种预测方法的不同导致最终的地表沉降值存在差异,但主要开挖阶段引起的地表沉降基本一致;主要的差异来源于数值模拟方法考虑了更为具体的衬砌施工工序,导致开挖过程中洞内收敛特征与理论预测方法明显不同。     

Subsidence control method by inversely-inclined slicing and upward mining for ultra-thick steep seams

Ultra-thick steep coal seam mining will inevitably lead to the increase of greater and violent ground subsidence and deformation. A subsidence control method by inversely-inclined slicing and upward mining is proposed in this paper. By this method, the sequence of collapse of overlying strata and the direction of propagation of strata movement are changed, the extent of roof-side deformation thereby is lessened, and boundary angle of roof-side subsidence is reduced by 5°–10°. The mechanism of this mining method for control of strata movement has been evidenced by numerical simulation and experiments with similarity materials. A subsidence prediction model based on the variation of mining influence propagation angle can be used to evaluate the surface movement and deformation of the mining method. The application of the method in No.3 Mine in Yaojie mining area has yielded the expected result.     

基于遗传规划的采空区地面沉陷预测分析

针对地下开采引起的岩层移动与变形,提出一种基于遗传规划的采空区地面沉陷预测新方法.基于MTLAB工具编制的遗传规划程序,选取影响地面沉陷的主要因素,搜集学习样本对程序进行了训练,建立了采空区地面沉陷预测的遗传规划模型.最后,利用有关实测数据,对模型进行了实例检验.结果表明,预测误差在工程允许范围之内,应用遗传规划方法进...     

开采沉陷岩移参数研究现状分析

开采沉陷岩移参数是表征岩层和地表移动规律的重要参数,其取值的准确与否直接影响到矿山生产设计的合理性和安全性.开采沉陷岩移参数的确定方法主要有实测数据拟合、回归分析、工程类比、神经网络、力学反演分析法和模糊数学方法.在综合分析大量文献的基础上,综述了开采沉陷岩移参数的研究现状,指出了可以应用相似理论确定不同地质采矿条件下开采沉陷岩移参数.     

裂缝天线缝制造精度对电性能影响的预测

为了避免传统方法在分析结构因素对电性能影响时需要假设和近似处理的弊端,提出了根据平板裂缝天线生产制造中的数据,使用支持向量回归建立缝制造精度对电性能指标影响的预测方法。给出了一种以最小化支持向量回归的拟合能力和泛化能力为目标函数来选择支持向量回归机参数的方法,以方便该方法的工程应用。案例研究表明,该方法能够较准确地预测缝制造精度对电性能的影响;与传统的BP神经网络和最小二乘法对比,该方法具有更好的泛化能力,可以应用到平板裂缝天线的计算机辅助制造中。     

基于混合响应面法的滚压成型回弹角预测控制及应用

为了解决板金属滚压成型回弹角预测精度不足以及滚压成型工艺参数的选定过多依赖于经验设计的问题,提出将参数响应面法与非参数响应面法结合形成混合响应面法,利用混合响应面法对滚压成型的加工工艺参数进行优化并预测控制板金属回弹角的大小.通过混合响应面法可以分段构建板金属滚压成型回弹角预测模型,将预测模型的回弹角响应值和滚压成型实验回弹角值进行误差分析比较,两者具有良好的一致性;最后通过优化求解回弹角预测模型得到回弹角的最小值,结果表明,选用适当的成型板料弯曲内半径、过弯角可以大大减小滚压成型回弹角.     

综采放顶煤地表移动规律特殊性

调查分析了兖州矿区鲍店矿综采放顶煤工作面和普通综采工作面地表移动观测站实测资料．研究结果表明：综放开采时地表移动更加剧烈,地表危险移动范围增大,超前影响范围超过常规分层开采约４０％,下沉活跃期占总移动时间的７１．４％,活跃期下沉量约占总下沉量的９５％．研究还表明,采厚是控制超前影响角和最大下沉速度滞后角的重要因素之一,地表充分采动区存在的残余变形现象更加明显     

Parametric optimization of friction stir welding process of age hardenable aluminum alloys-ANFIS modeling

A comparative approach was performed between the response surface method(RSM) and the adaptive neuro-fuzzy inference system(ANFIS) to enhance the tensile properties, including the ultimate tensile strength and the tensile elongation, of friction stir welded age hardenable AA6061 and AA2024 aluminum alloys. The effects of the welding parameters, namely the tool rotational speed, welding speed, axial load and pin profile, on the ultimate tensile strength and the tensile elongation were analyzed using a three-level, four-factor Box-Behnken experimental design. The developed design was utilized to train the ANFIS models. The predictive capabilities of RSM and ANFIS were compared based on the root mean square error, the mean absolute error, and the correlation coefficient based on the obtained data set. The results demonstrate that the developed ANFIS models are more effective than the RSM model.     

LS_ SVM和SVM在发酵过程建模中的比较

针对最小二乘支持向量机(LS_ SVM)不需要指定逼近精度ε的特点,比较了LS_ SVM与SVM两种方法利用生产数据为青霉素发酵过程建立的数学模型,改进型GA分别为LS_ SVM和SVM选择参数值.实验证明:LS_ SVM建立的模型具有较高的拟合精度和泛化能力.如果ε过大时,SVM建立的模型的拟合精度和泛化能力不高;当ε过小时,模型的拟合精度和泛化能力较高,但耗时多.因此,LS_SVM更适合为发酵过程建模.     

含水松散层固结对地表沉陷影响的数值分析

为了研究含水松散层固结对地表沉陷的影响,基于固结沉降量对预计参数确定的重要性,分析了影响含水层固结的因素,包括渗透系数、松散层厚度、采动程度和采煤方法.在分析现场实测资料的基础上,采用FLAC3D流-固耦合计算的方法,对覆岩内部位移场和渗流场进行了分析,研究了含水层固结压缩对地表沉降的影响.结果表明不考虑冲积层含水时,地面最大沉陷值为1220mm,考虑冲积层含水时,最大沉陷值为1306mm,下沉量增加86mm.地面沉陷盆地的外缘,沉陷量显著增加,增加量为160mm,最大沉降增加量为7%;走向方向和倾向方向松散层含水条件下均比不含水条件下水平移动量大,走向方向最大相差122 mm,倾向最大相差105 mm.     

开采沉陷动态参数预计的三次指数平滑法

在我国,概率积分法是应用最多的一种开采沉陷预计方法．该方法中的预计参数在不同采动程度下是变化的．能否准确获知动态参数的变化规律将决定着开采沉陷的预计精度．为较好地解决这一问题,引入了一种动态参数预计的新方法,即三次指数平滑法．应用此方法对实测资料进行了预计和比较,结果表明,各预计参数的平均相对误差都小于4％．由此可见,该方法对开采沉陷的预测具有一定的应用价值．     

开采沉陷动态参数预计的三次指数平滑法

在我国,概率积分法是应用最多的一种开采沉陷预计方法.该方法中的预计参数在不同采动程度下是变化的.能否准确获知动态参数的变化规律将决定着开采沉陷的预计精度.为较好地解决这一问题,引入了一种动态参数预计的新方法,即三次指数平滑法.应用此方法对实测资料进行了预计和比较,结果表明,各预计参数的平均相对误差都小于4%.由此可见,该方法对开采沉陷的预测具有一定的应用价值.     

Superposition model for analyzing the dynamic ground subsidence in mining area of thick loose layer

The dynamic ground subsidence due to underground mining is a complicated time-dependent and ratedependent process. Based on the theory of rock rheology and probability integral method, this study developed the superposition model for the prediction and analysis of the ground dynamic subsidence in mining area of thick loose layer. The model consists of two parts(the prediction of overlying bedrock and the prediction of thick loose layer). The overlying bedrock is regarded as visco-elastic beam, of which the dynamic subsidence is predicted by the Kelvin visco-elastic rheological model. The thick loose layer is regarded as random medium and the ground dynamic subsidence is predicted by the probability integral model. At last, the two prediction models are vertically stacked in the same coordinate system, and the bedrock dynamic subsidence is regarded as a variable mining thickness input into the prediction model of ground dynamic subsidence. The prediction results obtained were compared with actual movement and deformation data from Zhao I and Zhao II mine, central China. The agreement of the prediction results with the field measurements show that the superposition model(SM) is more satisfactory and the formulae obtained are more effective than the classical single probability integral model(SPIM), and thus can be effectively used for predicting the ground dynamic subsidence in mining area of thick loose layer.     

Sizing of rock fragmentation modeling due to bench blasting using adaptive neuro-fuzzy inference system (ANFIS)

One of the most important characters of blasting, a basic step of surface mining, is rock fragmentation because it directly effects on the costs of drilling and economics of the subsequent operations of loading, hauling and crushing in mines. Adaptive neuro-fuzzy inference system (ANFIS) and radial basis function (RBF) show potentials for modeling the behavior of complex nonlinear processes such as those involved in fragmentation due to blasting of rocks. We developed ANFIS and RBF methods for modeling of sizing of rock fragmentation due to bench blasting by estimation of 80% passing size (K₈₀) of Golgohar iron mine of Sirjan, Iran. Comparing the results of ANFIS and RBF models shows that although the statistical parameters RBF model is acceptable but ANFIS proposed model is superior and also simpler because ANFIS model is constructed using only two input parameters while seven input parameters used for construction of RBF model.