松散破碎介质中气体渗流规律试验研究

EXPERIMENTAL STUDY OF LAWS OF GAS SEEPAGE IN LOOSE FRAGMENTED MEDIUM

原地爆破浸出采场的铀矿堆,是一种松散破碎介质,其颗粒级配服从Rosin-Rammler分布。这种介质中的气体渗流同时受到介质的特征粒径、粒径分布指数和孔隙率的影响。为了研究这种影响,根据Rosin-Rammler分布,选配具有不同颗粒级配的7组试样,采用自制的松散破碎介质气体渗流试验装置,对其中气体渗流的规律进行试验研究,并利用试验结果,采用自适应神经模糊推理系统,建立根据特征粒径、粒径分布指数和孔隙率预测渗透率和惯性系数的自适应神经模糊推理系统(ANFIS)模型。结果表明:松散破碎介质中的气体渗流不满足Darcy定律,而满足Darcy-Forchheimer定律;所建立的预测渗透率和惯性系数的ANFIS模型,能够给出具有足够精度的预测结果,这为渗透率和惯性系数的预测开辟新的途径。

For in place leaching of fragmented uranium ore by blasting, the ore heap is a loose fragmented medium, whose particle sizes follow the Rosin-Rammler distribution. The gas seepage in the medium is influenced by characteristic particle size, particle size distribution index and porosity simultaneously. To study the influence, seven samples are compound with different particle size gradations based on Rosin-Rammler distribution. The laws of gas seepage in seven samples are studied based on self-developed apparatus. On the basis of the test results, the adaptive neuro-fuzzy inference system（ANFIS） model for predicting seepage ratio and inertial coefficient is established using the adaptive neuro-fuzzy inference system based on characteristic particle size, particle size distribution index and porosity. The research results show that gas seepage in fragmented medium does not follow Darcy＇s law but follows Darcy-Forchheimer＇s law. Therefore, the ANFIS model provides predictions with high accuracy, which proves to be a new approach for estimation of permeability and inertial coefficient.