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A fractal kinetic model for heap leaching of uranium ore with fractal dimension of varied particle size distribution

机译:分形维数不同粒度分布的铀矿堆浸分形动力学模型

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The varied particle size distribution of uranium ore for heap leaching, with its particle sizes ranging from 0 to 9 mm, is taken from a uranium mine in South China. Five uranium ore samples with the fractal dimensions (D) of particle size distribution of 1.6,1.8,2.0,2.2 and 2.4, respectively, are further prepared by mixing different weights of the uranium ores for the size fractions of + 8/— 9, + 7/— 8, + 6/— 7, + 5/— 6, + 4/— 5, + 3/— 4, + 2/— 3, +1/— 2, + 0.5/— 1 and — 0.5 mm, respectively. The five samples are leached in columns to investigate the influences of the fractal dimensions of particle size distribution on their leaching performances. The leaching data are analyzed using the shrinking core model, and the whole process of the column leaching is divided into two phases based on the pH and the potential vs. saturated calomel electrode (SCE) of the pregnant leach solution (PLS) from the columns. When the value of pH is greater than 2.0 and the potential vs. SCE is less than 400 mV, the leaching is in the first phase, the rate constant during the first phase k_1 is controlled by initial rate constant k_0 and the increase rate parameter A, and k_0, λ and the length of the period for the first phase T_1, all have linear relationships with D. When the value of pH is less than or equal to 2.0 and the potential vs. SCE is greater than or equal to 400 mV, the leaching is in the second phase, and the rate constant during the second phase k_2 has non-linear relationship with D. From these analytical results, a fractal kinetic model for heap leaching of the uranium ore with fractal dimension of varied particle size distribution is established. And the experimental results show that the model is capable of predicting the recovery of uranium for heap leaching of uranium ore with fractal dimension of varied particle size distribution.
机译:用于堆浸的铀矿石的粒径分布各异,其粒径范围为0至9 mm,取自中国南方的铀矿。通过混合不同重量的铀矿石(尺寸分数为+ 8 /-9),进一步制备了五种铀矿样品,其分形维数(D)的粒度分布分别为1.6、1.8、2.0、2.2和2.4。 + 7 / — 8,+ 6 / — 7,+ 5 / — 6,+ 4 / — 5,+ 3 / — 4,+ 2 / — 3,+ 1 / — 2,+ 0.5 / — 1和— 0.5毫米,分别。将五个样品分列进行淋滤,以研究粒度分布的分形维数对其淋溶性能的影响。使用收缩核模型对浸出数据进行分析,然后根据pH值和柱中浸出液(PLS)的电位与饱和甘汞电极(SCE)的关系,将柱浸的整个过程分为两个阶段。 。当pH值大于2.0并且相对于SCE的电势小于400 mV时,浸出处于第一阶段,第一阶段k_1的速率常数由初始速率常数k_0和增加速率参数A控制,并且k_0,λ和第一阶段T_1的周期长度都与D呈线性关系。当pH值小于或等于2.0且电势对SCE大于或等于400 mV时,浸出处于第二阶段,第二阶段的速率常数k_2与D呈非线性关系。根据这些分析结果,可以得到分形维数不同的粒度分布的铀矿石堆浸分形动力学模型。成立。实验结果表明,该模型能够预测具有不同粒度分布的分形维数的铀矿石堆浸铀的回收率。

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