Analyzed the rule of the Water Flowing Fractured (WFF) zone's development during the fully mechanized top coal caving.Six influence factors of WFF's height were selected,viz.mining thickness,base rock thicknes...Analyzed the rule of the Water Flowing Fractured (WFF) zone's development during the fully mechanized top coal caving.Six influence factors of WFF's height were selected,viz.mining thickness,base rock thickness,dip angle,uniaxial compressing strength of roof,mudstone proportion in overlying rock,and structure of overlying rock. The height-forecasting model of WFF was established based on the Artificial Neural Net-work techniques,and was applied in the first fully mechanized top coal caving face under sea in China.展开更多
This paper mainly discusses the selection of the technical parameters of fully mechanized top coal caving mining using the neural network technique. The comparison between computing results and experiment data shows t...This paper mainly discusses the selection of the technical parameters of fully mechanized top coal caving mining using the neural network technique. The comparison between computing results and experiment data shows that the set up neural network model has high accuracy and decision making benefit.展开更多
基金National Science Support Plan of China(2006BAB16B04)
文摘Analyzed the rule of the Water Flowing Fractured (WFF) zone's development during the fully mechanized top coal caving.Six influence factors of WFF's height were selected,viz.mining thickness,base rock thickness,dip angle,uniaxial compressing strength of roof,mudstone proportion in overlying rock,and structure of overlying rock. The height-forecasting model of WFF was established based on the Artificial Neural Net-work techniques,and was applied in the first fully mechanized top coal caving face under sea in China.
基金National Natural Science Foundation of China( 5 97340 90 )
文摘This paper mainly discusses the selection of the technical parameters of fully mechanized top coal caving mining using the neural network technique. The comparison between computing results and experiment data shows that the set up neural network model has high accuracy and decision making benefit.
文摘针对龙口海域下开采的实际情况,分析了海域扩大区水文地质条件,收集整理国内13个矿区综放开采导水裂缝带高度实测数据,选取采厚、基岩柱厚度、倾角、顶板单轴抗压强度、泥岩比例和覆岩结构6种因素作为导水裂缝带发育高度预测模型的影响因子,建立导水裂缝带高度预测模型,并对不同采厚条件下导水裂缝带高度进行了预测;应用FLAC软件进行了断层条件下覆岩破坏规律的模拟,计算了不同落差、不同倾角的正断层对导水裂缝带发育高度的影响,得出在软弱覆岩类型综采工作面(采厚4.4 m)有正断层(倾角45-65°)、落差小于6.0 m的情况下,导水裂缝带发育高度较之正常地质条件下增大14.4%-22.2%.提出了综合考虑断层和正常条件的防水安全煤岩柱设计,确定在海域放顶煤开采正常覆岩条件下防水安全煤岩柱厚度为55.5 m;受断层影响条件下,防水煤岩柱厚度为62.5 m.