磷尾矿充填体中有害元素的溶出行为研究

发布时间：2018-05-11 16:44

本文选题：磷尾矿 + 充填体　；参考：《贵州大学》2015年硕士论文

【摘要】：近年来,尾矿充填法作为一种高效、安全的开采方法被许多矿山应用,为了考察磷尾矿充填体填充到井下后对井下环境的污染情况,本文以贵州某磷矿尾矿为骨料制作充填体,对充填体进行有害元素的溶出试验。结合充填原料磷尾矿、粉煤灰和水泥性质分析的结果,选取总硬度、硫酸盐、氟化物、总磷和Fe作为溶出试验指标,通过对磷尾矿及充填体的静态浸泡试验,得出磷尾矿和磷尾矿充填体各元素的溶出规律相似,具体结果如下:(1)随时间的增加、温度的升高和液固比的降低,充填体及磷尾矿中总硬度、硫酸盐、总磷和氟化物的溶出浓度呈上升趋势。在浸泡前10天各溶出浓度快速增加,随后各溶出浓度增加逐渐缓慢,30天后各溶出浓度基本趋于平稳。(2)随着pH值的降低,总硬度、硫酸盐、总磷的溶出浓度呈上升趋势,在pH值低于3时,总硬度、硫酸盐、总磷的溶出浓度增高趋势明显。而氟化物的溶出浓度则随pH值的升高而增加。(3)改变浸泡时间、液固比及温度,Fe的溶出规律不明显,但当浸泡液pH值为2时,Fe的溶出浓度增高趋势明显,说明pH值较低的条件利于Fe溶出。(4)对比磷尾矿和磷尾矿充填体溶出试验数据,结果表明,充填体中总磷和氟化物的溶出浓度低于磷尾矿总磷和氟化物的溶出浓度,而充填体中硫酸盐的溶出浓度高于磷尾矿硫酸盐的溶出浓度。为考察浸泡温度、液固比、pH值、时间4种因素对充填体总硬度、硫酸盐、总磷和氟化物溶出浓度的整体影响程度,设计正交试验,选取内梅罗指数作为试验考察指标,试验结果表明,对溶出浓度影响最大的因素为液固比,其次为pH、时间和温度。以国家地下水质量标准为评价标准,采用模糊综合评价法对充填体泌水的9项因子进行评价,评价表明,充填体泌水对于地下水属于V类污染,对地下水的污染程度严重,主要污染因子为总硬度、硫酸盐和氟化物。将充填体的溶出试验数据作为训练样本,借助MATLAB补偿模糊神经网络工具箱,对总硬度、硫酸盐、总磷和氟化物的溶出浓度建立4个预测模型。对建立的模型进行检验得出,建立的补偿模糊神经网络模型预测数据与实测数据基本一致,具有一定的可行性。
[Abstract]:In recent years, tailings filling method has been used in many mines as an efficient and safe mining method. In order to investigate the pollution of underground environment caused by phosphorus tailings filling, a phosphate tailings from Guizhou province is used as aggregate to make backfill. The dissolving test of harmful elements was carried out on the filling body. Combined with the analysis of the properties of phosphorus tailings, fly ash and cement, the total hardness, sulfate, fluoride, total phosphorus and Fe were selected as the dissolution test indexes, and the static soaking test of phosphorus tailings and backfill was carried out. It is concluded that the dissolution law of each element in phosphorus tailings and phosphorus tailings is similar, and the specific results are as follows: 1) with the increase of time, the increase of temperature and the decrease of liquid-solid ratio, the total hardness and sulfate in the backfill and phosphorus tailings, The dissolved concentration of total phosphorus and fluoride showed an increasing trend. The dissolution concentration increased rapidly 10 days before soaking, and then gradually increased slowly after 30 days. After 30 days, the dissolved concentration tended to be stable. (2) with the decrease of pH value, the total hardness, sulfate and total phosphorus concentration increased, and the total hardness, sulfate and total phosphorus concentration increased with the decrease of pH value. When pH value is lower than 3, the total hardness, sulfate and total phosphorus concentration increase obviously. However, the dissolution concentration of fluoride increased with the increase of pH value. The soaking time was changed. The dissolution rate of liquid to solid and the temperature of Fe were not obvious, but the dissolution concentration of Fe increased obviously when the pH value of soaking solution was 2. The results showed that the dissolution concentration of total phosphorus and fluoride was lower than that of phosphorus tailings and fluoride, the results showed that the dissolution concentration of total phosphorus and fluoride was lower than that of phosphorus tailings. The dissolution concentration of sulfate in backfill is higher than that in phosphorus tailings. In order to investigate the overall influence of soaking temperature, liquid-solid ratio, pH value and time on the total hardness, sulfate, total phosphorus and fluoride dissolution concentration of the filling body, the orthogonal test was designed, and the Nemero index was selected as the test index. The results showed that the most important factors affecting dissolution concentration were liquid-solid ratio, pH, time and temperature. Taking the national groundwater quality standard as the evaluation standard, the fuzzy comprehensive evaluation method is used to evaluate the nine factors of the bleeding of the filling body. The evaluation shows that the bleeding of the filling body belongs to the class V pollution of the groundwater, and the pollution degree of the filling body to the groundwater is serious. The main pollution factors are total hardness, sulfate and fluoride. Taking the dissolution test data of the filling body as the training sample and using the MATLAB compensation fuzzy neural network toolbox, four prediction models were established for the total hardness, sulfate, total phosphorus and fluoride dissolution concentration. By testing the established model, it is concluded that the predicted data of the model are basically consistent with the measured data, and the proposed model is feasible.
【学位授予单位】：贵州大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TD926.4

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