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原地爆破浸出采场的铀矿堆,是一种由凿岩爆破法构筑而成的矿堆,是一种松散破碎介质,其粒径服从Rosin-Rammler分布,其特征粒径、粒径分布指数和孔隙率随所采用的爆破参数和爆破工艺的不同而不同。为了研究这类铀矿堆的特征粒径、粒径分布指数和孔隙率对其中液体饱和渗流的影响,根据Rosin-Rammler分布,选配了7组具有不同颗粒级配的试样,采用自制的松散破碎介质液体饱和渗流试验装置,对其中液体饱和渗流的规律进行了试验研究,并利用试验结果,采用自适应神经模糊推理系统(ANFIS),建立了根据特征粒径、粒径分布指数和孔隙率预测渗透率和流态指数的ANFIS模型。结果表明:松散破碎介质中的液体饱和渗流满足非Darcy指数定律;所建立的预测渗透率和流态指数的ANFIS模型,能够给出具有足够精度的预测结果,这为渗透率和流态指数的预测开辟了新的途径。
The in-situ blasting and leaching of uranium mound from the stope is a type of rock mass constructed by the rock blasting method. It is a loosely crushed medium with particle size obeying the Rosin-Rammler distribution. Its characteristic particle size and particle size distribution The index and porosity vary with the blasting parameters used and the blasting process used. In order to study the influence of characteristic particle size, particle size distribution index and porosity on the saturation seepage of liquid in this type of uranium heap, seven groups of samples with different particle sizes were selected according to Rosin-Rammler distribution. In this paper, the law of liquid saturation seepage in loose medium is studied experimentally. Based on the experimental results and the adaptive neuro-fuzzy inference system (ANFIS), this paper establishes a new method based on characteristic particle size, particle size distribution index and porosity ANFIS model predicting permeability and fluidity index. The results show that the liquid saturated seepage flow in loosely crushed medium meets the non-Darcy index law. The established ANFIS model of predictive permeability and fluidity index can give prediction results with sufficient accuracy, which can be used to predict the permeability and fluid index Forecast opens up new avenues.