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铀矿堆浸,溶浸液在铀矿堆中的渗流对浸出效果有非常重要的影响,研究堆浸铀矿堆的渗透特性,对改善铀矿堆浸效果具有重要的意义。采用取自我国南方某铀矿山的堆浸铀矿石,配制10组不同粒径分维数的试样,利用自制的饱和渗流试验装置,对其液体饱和渗流的规律进行试验研究,获得相应的渗透率和流态指数。利用试验结果,分析粒径分维数对渗透率的影响。采用支持向量机(SVM)模型,以粒径分维数和孔隙率作为输入量,建立渗透率和流态指数预测模型。结果表明,(1)在文中试验条件下,堆浸铀矿堆的液体饱和渗流遵循非Darcy指数定律,流态指数在1.1～1.5之间,且渗透率随着粒径分维数的增加而逐渐减小;(2)渗透率的SVM预测模型和流态指数的SVM预测模型给出预测值的相对误差分别低于8%和7%,可以满足工程应用的要求。
The heap leaching of uranium and the infiltration of the leaching solution in the uranium heap have a very important influence on the leaching effect. Studying the infiltration characteristics of the heap leaching uranium deposit is of great significance to improving the heap leaching effect of the uranium deposit. Using heap leaching uranium ore from a uranium mine in southern China, 10 samples with different particle size fractal dimensions were prepared. The saturated seepage test device was used to study the law of liquid saturated seepage, and the corresponding infiltration Rate and flow index. Using the test results, the influence of particle size fractal dimension on permeability is analyzed. The support vector machine (SVM) model was used to establish the prediction model of permeability and fluidity index based on the fractal dimensions of particle size and porosity. The results show that: (1) Under the experimental conditions, the saturated liquid seepage of the heap leaching uranium deposit follows the non-Darcy index law and the flow index is between 1.1 and 1.5, and the permeability increases with the increase of the fractal dimension (2) The SVM prediction model of permeability and the SVM prediction model of flow index give the relative error of prediction value less than 8% and 7%, respectively, which can meet the requirements of engineering application.