厚冲积层立井井筒破坏的发生机理及防治技术研究
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摘要
立井井筒非采动破坏是一种特殊类型的工程地质灾害,是人类采矿活动和地质环境相互作用的结果。作者立足于广大科研人员十几年来的研究成果,采用力学分析、数值模拟、神经网络等方法,建立了立井井筒破坏的快速分析计算方法及立井井筒破坏的神经网络预测系统,且给出了新的治理方法设计,为彻底的根治立井井筒破坏的工程地质灾害提供了新的思路与理论依据。本文的主要结论为:
1、基于立井井筒具体的工程地质及水文地质条件建立立井井筒破坏的数值模拟计算模型,对井筒破坏过程中的水、土、井筒三者的相互作用进行耦合模拟计算分析,确定立井井筒非采动破坏(初次破坏与重复破坏)的发生过程及发生机理,形成一套有效的立井井简破坏过程数值模拟计算方法与流程;
2、根据立井井筒非采动破坏的工程地质力学模型,建立立井井筒非采动破坏过程的力学分析计算方法,对已建立井井筒破坏进行预防与治理,对类似工程地质条件下的矿区的新建立井设计提供计算依据;
3、基于模糊神经网络理论与立井井筒具体的工程地质及水文地质条件建立立井井筒破坏的模糊神经网络的预测与判别系统,用此结果来指导矿山生产,形成一套有效的立井井筒破坏预测与判别方法;
4、在充分研究现有的立井井筒破坏治理方法的基础上,结合底含加固、土体水平应力的卸荷及立井井筒保护三方面的支护机理提出一种立井井筒非采动破坏地质灾害的治理新方法,为有效的治理立井井筒破坏提供新的理论。
Non-mining fracturing of shaft lining is a special engineering geologic hazard and is caused by interaction between mining and geological environment. The neural network forecast system and new harnessing method were established based on the achievements of researchers before. The main conclusions of this thesis are:1. The numerical simulation model was built based on practical engineering geologic and hydrogeologic conditions of shaft fracturing. The simulation was carried out by three-dimensional coupling numerical simulation method. The result revealed the changing laws of different factors in the process of shaft-lining fracturing, and would play an important role in the fracturing mechanism analysis and prevention and harness for shaft lining.2. The calculation methods of mechanism analysis was founded for the forecast and harnessing of shaft fracture, and the new shaft could be designed according as this methods.3. The forecast system was established based on the fuzzy neural network theory. The forecast results indicated that the approach combining fuzzy logical judgment with artificial neural network could distinguish better the developing of shaft-lining non-mining fracture hazard and the results were reliable and could meet the practical requirement.4. The new harnessing method is drawn for the shaft lining fracture based on the mechanism analysis of harnessing methods for shaft lining fracture before, and the new theory was provided for harnessing shaft effectively according to this new harnessing method.
1、基于立井井筒具体的工程地质及水文地质条件建立立井井筒破坏的数值模拟计算模型,对井筒破坏过程中的水、土、井筒三者的相互作用进行耦合模拟计算分析,确定立井井筒非采动破坏(初次破坏与重复破坏)的发生过程及发生机理,形成一套有效的立井井简破坏过程数值模拟计算方法与流程;
2、根据立井井筒非采动破坏的工程地质力学模型,建立立井井筒非采动破坏过程的力学分析计算方法,对已建立井井筒破坏进行预防与治理,对类似工程地质条件下的矿区的新建立井设计提供计算依据;
3、基于模糊神经网络理论与立井井筒具体的工程地质及水文地质条件建立立井井筒破坏的模糊神经网络的预测与判别系统,用此结果来指导矿山生产,形成一套有效的立井井筒破坏预测与判别方法;
4、在充分研究现有的立井井筒破坏治理方法的基础上,结合底含加固、土体水平应力的卸荷及立井井筒保护三方面的支护机理提出一种立井井筒非采动破坏地质灾害的治理新方法,为有效的治理立井井筒破坏提供新的理论。
Non-mining fracturing of shaft lining is a special engineering geologic hazard and is caused by interaction between mining and geological environment. The neural network forecast system and new harnessing method were established based on the achievements of researchers before. The main conclusions of this thesis are:1. The numerical simulation model was built based on practical engineering geologic and hydrogeologic conditions of shaft fracturing. The simulation was carried out by three-dimensional coupling numerical simulation method. The result revealed the changing laws of different factors in the process of shaft-lining fracturing, and would play an important role in the fracturing mechanism analysis and prevention and harness for shaft lining.2. The calculation methods of mechanism analysis was founded for the forecast and harnessing of shaft fracture, and the new shaft could be designed according as this methods.3. The forecast system was established based on the fuzzy neural network theory. The forecast results indicated that the approach combining fuzzy logical judgment with artificial neural network could distinguish better the developing of shaft-lining non-mining fracture hazard and the results were reliable and could meet the practical requirement.4. The new harnessing method is drawn for the shaft lining fracture based on the mechanism analysis of harnessing methods for shaft lining fracture before, and the new theory was provided for harnessing shaft effectively according to this new harnessing method.
引文
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